[100-days-of-writing] Think Watch Do: 3 Simple But Powerful Self-Awareness Exercises Think Watch Do: 3 Simple But Powerful Self-Awareness Exercises By janzeteachesit Assigned to Think, Watch, Do: 3 Simple, But Powerful Self-Awareness Exercises http://ift.tt/2tm98T5 GRIST4 Writing Think, Watch, Do: 3 Simple, But Powerful Self-Awareness Exercises Niklas GoekeJul 21 Writer, book summarizer & habit coach on coach.me. | Made http://time2read.co | Blog: http://niklasgoeke.com | 365+ book summaries on http://ift.tt/1kMo1so It never ceases to amaze me how much you can learn from movies, books and music, even if it’s completely fictional. Take Harry Potter, for example. No matter how many times I watch it, read it, or think about it, I always find something new that’s interesting. Here’s what I learned from it this week: In every trio there is a thinker, a watcher and a doer. Take our three aspiring magicians, for example. Source Who’s who is obvious: Ron’s the doer. He charges right ahead and he doesn’t know what he’s doing most of the time. Harry’s the watcher. He observes everything and tries to process it. If you’ve ever wondered why he spends so much time of the saga on the sidelines, either incapable of acting or reluctant in deciding, that’s why. Hermione’s the thinker. She doesn’t just observe things, but deliberately takes time to think about them before she gets more information. That’s what makes her so brilliant. When you try to identify these types for the people in your life, you’ll see the thinkers are the ones who seem to have it the easiest while the doers are frustrated a lot. That’s because this categorization corresponds to different levels of self-awareness: the thinkers know themselves best. This is not to say one is better than the other. In fact, we have to carry all of these types within us. It’s just that the thinkers tend to know best when to take on which role. At the same time, it’s the capacity most of us have developed the least. Whatever mode you spend the majority if your time in, there are certain things you can practice to get to the next level. Today, I’d like to show you three self-awareness exercises to achieve just that. Self-Awareness Exercise #1 — For Doers: Apologize Since he does first and thinks later, Ron is often wrong. That’s why he’s making a fair share of apologies. Apologies to Harry, apologies to Hermione, apologies to his family. Source As a doer, that’s one of the best things he can do. You can’t apologize without acknowledging you’ve made a mistake. This acknowledgement is where self-awareness comes from. Exercise: The next time you feel embarrassed because you know you just made a mistake, don’t brush off that feeling. Take it as a chance to quickly turn this obstacle around by apologizing. I used to hate apologies. Especially as a teenager. Over the years I’ve come to see that not only is the transparency and vulnerability of it liberating, but it actually helps you see the kinks in your armor — and how could you iron out what you can’t see? Apologize fast, apologize often. We hate admitting mistakes more than making them, but when you do, you won’t turn into a hypocrite and can reflect on how you can do better next time. Self-Awareness Exercise #2 — For Watchers: Journal When you observe so much, it’s hard to keep track of everything without writing it down. And write a lot Harry does. He writes letters to everyone, he writes in detention and he even had a diary that one time… Source This is a good idea for watchers in general. There’s a saying by Confucius: “You cannot open a book without learning something.” — Confucius Well, you also can’t write a sentence without learning something. The simplest form of journaling I know is the 1-sentence journal. Exercise: Take a thought-provoking question and answer it in one sentence, but answer differently each day. There are endless possibilities to design this exercise and you can change the question from each week or month to the next. Why did you get up this morning? What made you go “huh?” yesterday? Were you content before you fell asleep? You can also gear your questions towards when in the day you’re answering them. For example, here are some ideas for good questions to ask yourself in the morning: Do you feel ready to tackle the day? Why? Why not? What was the first thing you thought of after waking up? What’s one thing you’re grateful for? What’s the most important thing you want to achieve today? Did you sleep enough? What are you most excited about today? Then again, you might want to journal before bed. In that case, you could answer an evening question. Here are some examples: Why did you get out of bed this morning? What’s the best thing that happened today? When did you feel happy or content today? Which hour of the day was your favorite? What did you learn today? Did you do your best today? How could you make tomorrow an even better day than today? What thing are you most excited about for tomorrow? Even in this tiny format, journaling helps your brain structure the things you observe and get better at filtering what matters. That way you can take action in a more targeted way and have to apologize less. If you want to grow this habit over time and slowly spend some more time each day, there are a lot of pre-structured journals out there too. Here are a few some of my coaching clients and I have used: The 5 Minute Journal The SELF Journal The Productivity Planner The Freedom Journal The Bullet Journal You could also journal online, using an app like Day One or Penzu, but there’s something visceral to writing by hand, which I prefer. If you’re a watcher, you’re great at watching life. Might as well remember what’s important. Journaling helps you do just that. Self-Awareness Exercise #3 — For Thinkers: Read When you generally have a good sense of what’s going on, which events are most important and where action’s required, it’s up to you to now extend this knowledge at the right ends. That’s why Hermione’s favorite place is the library. Source Thinkers transform their good contributions to great contributions through selective and well-timed reading. Reading the right thing at the right time allows your neurons to find the best connections between the pictures in your mind. Exercise: Read at least one page a day. Wittgenstein prompted us to read many books to expand our language. You can only know if you’re an ambivalent person when you know what that means. But you don’t have to overdose either. Thinkers usually have a fairly ingrained reading habit as is, but here are some resources that have helped make mine better: Time 2 Read. A free, 14-day email course I made to get your reading habit off the ground when you’ve fallen off the wagon. The Complete Guide To Remembering What You Read. A post I wrote to help you retain more. A Kindle. Easy access to books on the go. It removes the friction of having to carry books around. Books first, rent second. Ryan Holiday never worries about money spent on books. I try to do the same. Four Minute Books. A stash of 400+ short non-fiction book summaries with three lessons each. The Daily Stoic. A great philosophy book by Ryan Holiday, which is literally set up to read one page day. Blinkist. An app that provides you with 15-minute summaries of non-fiction books. The extension of knowledge we get from reading always comes with a side of self-awareness: are you the kind of person who can put it to good use? A page a day goes a long way. Being able to tell what you need to learn next and where you can find it is one of the highest forms of self-awareness. Think, Watch, Do — The Path To Knowing Oneself Only the best of us carry multiple characters around in our chest that we can draw on at will. We all begin one way or another. Start looking around. You’ll find this 3-type pattern in all famous trios. Them… Source …them… Source …even those guys: Source Doers must learn to watch. Watchers must learn to think. Thinkers must learn to think better. The way you do that is by practicing. 1. If you’re a doer, apologize when you screw up. 2. If you’re a watcher, journal about the things you notice. 3. If you’re a thinker, master your reading habit. The question is: Which one are you and what do you need to find out about yourself to get to the next level? If you enjoyed this… …you’ll love Nik’s Newsletter, with the best of my weekly writings, ideas, and book summaries. I’ll even give you my top 3 out of 400+ so far. Get it here. Worth reading? Then it might be worth recommending. Hit the heart so someone else on Medium will do, watch or think. 💚 This was first published at niklasgoeke.com. Better Humans Real stories of success in productivity, health and leadership. Think, Watch, Do: 3 Simple, But Powerful Self-Awareness Exercises Label: grist Date: August 13, 2017 at 04:40PM Labeled: August 13, 2017 at 04:48PM via GitHub http://ift.tt/2vvSmo3 August 13, 2017 at 04:52PM via GitHub http://ift.tt/2vvSmo3 [100-days-of-writing] Run or Walk (Part 2): Collecting Device Motion Data the Right Way Run or Walk (Part 2): Collecting Device Motion Data the Right Way By janzeteachesit Assigned to Run or Walk (Part 2): Collecting Device Motion Data the Right Way http://ift.tt/2wHF7iE GRIST4 STEM Fitness Data Run or Walk (Part 2): Collecting Device Motion Data the Right Way Viktor MalyiAug 13 Read previous part: “Run or Walk (Part 1): Detecting Motion Data Activity with Machine Learning and Core ML” Being motivated to develop a machine learning model that accurately predicts whether the user walks or runs, I needed data. A quick search for the publicly available datasets which contain such activities gave no results. And the only option left was to collect data on my own. Everyone who took part in any data science competitions knows that dataset always needs to be processed to some extent before it can be fed into machine learning model. You can’t pass by this phase, otherwise, your model will suffer from missing, skewed data, outliers and a several other issues. Sometimes after finishing a competition and looking back to the time invested in it, you realize that nearly a half amount of your efforts were spent on processing a dataset! The reason? Datasets are based on the real-life data which is not ideal in a sense of continuity, homogeneity or statistical distribution. DIY data Things are better when you are solely responsible for collecting the data. It’s the most expensive way of getting data from the one side, but from the other side, you have a good chance to save yourself future efforts by collecting data in the way you need. Thinking carefully about the basics of the problem you’re trying to solve helps to find a proper approach to collecting data. I started from the essentials. If I wanted to know whether the person runs or walks I first needed to find a place on human’s body where each of these activities could be clearly distinguished in terms of sensor data. Simply put the iPhone in the pocket and collecting the data from there is not a good solution because each time the device can be differently positioned there. This could result in too variable results from the sensors even for the same activity. Given a limited amount of time I had to collect data, I preferred to sacrifice data variability for the simplicity. A perfect candidate for collecting people activity data is a hand wrist. And here’s why: Walking: hand wrist directed to the ground, moves with low to medium velocity Running: hand wrist directed mostly perpendicular to the ground, moves with medium to high velocity Considering most people have two hand wrists, the data for my 2-class classification model should be collected in following variations: Walking, right wrist; Walking, left wrist; Running, right wrist Running, left wrist; A valid question here would be “Wait, why mounting an iPhone on your wrist when Apple Watch is a more appropriate choice?!” Totally agree, but by that time I didn’t own one and assumed iPhone with its accelerometer and gyroscope will deliver equivalent sensor data. iPhone was always positioned with Home button pointing to the fingers What to collect? What first seems an easy to answer question, can lead you in the wrong direction. Having accelerometer, gyroscope, magnetometer, pedometer and even barometer in your iPhone doesn’t mean that collecting sensor data from all of them makes sense. The good starting point here is an official documentation which reveals the capabilities and limitations of each sensor. After carefully reading it I realized that the most valuable data comes from 2 sensors: accelerometer and gyroscope. Remember, I wanted to use as fewer data as possible? Limiting the number of sensors is the first step in this direction. Why those two? The accelerometer provides changes in device’s velocity along 3 axes which is a crucial piece of information about how one moves his hand. And a gyroscope delivers the rate at which a device rotates around a spatial axis which carries probably fewer insights for distinguishing running and walking activities, but, might still be helpful. Sensor axes for accelerometer (left) and gyroscope (right) Raw or processed data? Apple made a very good job providing different formats of motion data for different occasions. If one needs the accelerometer data limited to acceleration which was applied to the device only by the user, processed data is a valid option in this case. It doesn’t include different forms of bias like the acceleration caused by the gravity. From the other side, raw accelerometer data leaves it up to you how you process it, if at all. This kind of data is the perfect candidate to be used in my future machine learning model. Being unprocessed means that the data is free from any form of bias caused by implementation details of processing algorithms in iOS. This makes the data potentially reusable on other platforms and makes the risk getting hardly identifiable issues when training the model lower. Sensor update frequency Depending on hardware, Apple states impressive “at least 100 Hz” of a maximum sensor update frequency for accelerometer and gyroscope. It’s obvious: the more detailed information about device movement you need, the higher should be this value. But there is always some threshold when you get detailed enough data and getting even more detailed measurements don’t make sense. How to find an optimal sensor update frequency? Collect equivalent activity data at a maximum possible frequency, then at 70% of this value, and then 40%, and, finally, 10%. Plot the signal you received from each of those values and find a plot which keeps the important details of a signal and has the lowest sensor update frequency at the same time. Data collected at 50Hz The same data downsampled to 30Hz. Important signal details are lost. After experimenting with several values I identified 50Hz as an optimal sensor update frequency for the type of activities I was going to record. Collection interval Initially, I tried to collect data in an “uncontrolled” environment. I thought I will just stroll through the city on foot and endlessly record data for a walking activity. The same with running — I would just use my regular jogging sessions for data recording. Reality showed, however, that continuous recording of activities in the real environment like cities, where your movement is constantly interrupted by intersections, traffic lights, and other people, is a very bad idea. Data obtained during 30-minutes long walking session is full of noise from interruptions. I made an attempt to apply a few technics for removing outlying data samples, but none of them gave me a confidence that I preserve original data characteristics. The solution was to drastically shorten data collection intervals. When I evaluated recorded sessions which lasted only 10 seconds, I found out that only 3–4% of them contained outliers. Compared to 45% of data samples contained noise after continuous recording sessions, this is a clear improvement and a way to go. An app for a data collection I needed an app to collect data and temporarily store it before it’ll be uploaded to the environment where the samples will be processed. Staying pragmatic about the possible app features I refrained from developing fancy things and focused on the single goal — reliably collect data with fixed intervals and store it inside the app. The main questions regarding how often I want to collect data samples (50Hz) and for how long (10-second intervals) were answered. I had to implement an app which collects data samples and supplies them with meta information like date- and timestamp, username and a hand wrist on which a recording took place. Recorded sessions were stored in data recording app’s container in .csv format and then extracted and copied to my computer from it. Additionally, I implemented a haptic feedback within a regular time intervals in order to inform myself that recording still takes place and I don’t waste my time running somewhere without actually collecting a data. There were 2 recording modes: manual and continuous. I used the second one 95% of the time and it didn’t require me to start new recording session after every 10 seconds but was doing this automatically for me. Simplest possible UI Depending on whether “Walking” or “Running” was tapped, collected data has been accordingly labeled in the resulting .csv files. The final dataset After collecting walking and running data for about 5 hours in total, I could get an almost equal amount of data for each class including left/right wrist variations. This resulted in 88588 data samples with following structure: To prove that dataset I collected is robust and doesn’t suffer from typical dataset problems, I uploaded it to Kaggle and let others review and analyze it. I made my own analysis as well to make sure I will not face hard-to-analyze issues when training machine learning model on this dataset. The fact the dataset was featured by Kaggle team gave me confidence that the time spent recording this data worth it. And the biggest outcome, of course, is the fact that I could lose some weight during a couple of weeks when I was collecting the data. Follow me and stay tuned to know what machine learning techniques I applied to this dataset to predict user activity with >99% accuracy. Image/Video credits: http://ift.tt/2vvWDrBhttp://ift.tt/2wHktzf Videezy.com Run or Walk (Part 2): Collecting Device Motion Data the Right Way Label: grist Date: August 13, 2017 at 09:03PM Labeled: August 13, 2017 at 09:08PM via GitHub http://ift.tt/2hWMqQd August 13, 2017 at 09:12PM via GitHub http://ift.tt/2hWMqQd [100-days-of-writing] Conventional wisdom (course content) dawn pankonien Medium Conventional wisdom (course content) dawn pankonien Medium By janzeteachesit Assigned to Conventional wisdom (course content) – dawn pankonien – Medium http://ift.tt/2vTS1wB GRIST4 Writing Conventional wisdom (course content) dawn pankonienAug 11 Conventional wisdom, here, means knowledge that is popular (familiar or, even, taken for granted) but incorrect. Funny and harmless: If you swallow your gum, it stays in your stomach for seven years. More insidiously: Poor people are lazy, and that’s why they’re poor; most welfare recipients are black women with many children who can afford Cadillacs with their welfare funds. What at first appears positive but turns out to be socially detrimental (exclusionary and more) and its own form of racism: Asians are smart (this is called a model minority construct; also: the model minority myth). Previously: If women bathe while menstruating, they risk bleeding to death; everybody needs a tonsillectomy; different racial groups have different IQs… Here’s how economist John Kenneth Galbraith explained conventional wisdom: “As just noted, economic and social behaviour are complex and mentally tiring. Therefore we adhere, as though to a raft, to those ideas which represent our understanding. This is a prime manifestation of vested interest. For a vested interest in understanding is more preciously guarded than any other treasure. It is why men react, not infrequently with something akin to religious passion, to the defence of what they have so laboriously learned. Familiarity may breed contempt in some areas of human behaviour, but in the field of social ideas it is the touchstone of acceptability. Because familiarity is such an important test of acceptability, the acceptable ideas have great stability. They are highly predictable. It will be convenient to have a name for the ideas which are esteemed at any time for their acceptability, and it should be a term that emphasized this predictability. I shall refer to those ideas henceforth as the conventional wisdom” (from The Affluent Society 1958). Conventional wisdom (course content) – dawn pankonien – Medium Label: grist Date: August 13, 2017 at 09:22PM Labeled: August 13, 2017 at 09:23PM via GitHub http://ift.tt/2uByoJE August 13, 2017 at 09:27PM via GitHub http://ift.tt/2uByoJE [100-days-of-writing] The History of Programming Technicat on Software Medium The History of Programming Technicat on Software Medium By janzeteachesit Assigned to The History of Programming – Technicat on Software – Medium http://ift.tt/2vAvFxB GRIST4 CSP Women The History of Programming Philip ChuAug 12 On my list of things-I-want-to-do-but-I’m-not-serious-just-talking is a history of computers, or at least a history of computer programming, something like Bertrand Russell’s History of Western Philosophy or Will and Ariel Durant’s Story of Civilization. I got this interest during my one and only stint in academic teaching as an assistant to Computer Literacy 101 at Johns Hopkins University. The textbook included a decent history of computers, which was wasted on all the psych majors who only took the course because it was a requirement and raised their hands just to ask “Is this going to be on the test?” But I felt a really comprehensive history of computers would be fascinating and something both CS and non-CS majors should learn. Because it’s history, and it’s an interesting history that’s intertwined with everything from WWII codebreaking to the space race to just about everything you’re doing right now. And also it does help you learn how computers and computer programs actually work. I still haven’t seen any book or set of books like I’m envisioning, but I have been to a couple of computer history museums, most recently the one in Mountain View next to Google (there were some rather obvious Googlers sporting Google Glasses walking around), and I’ve read some biographies that collectively give you a sampling of computer history, like those of Countess Ada Lovelace, John Atanasoff, Alan Turing, John von Neumann… Wait a minute: Countess Ada Lovelace? Sounds like the heroine in a romance novel or a Lifetime movie. But real life is even better. She was the daughter of a rapscallion Lord Byron who left the family after she was born. Ada grew up a whiz at math and unfortunately was sick most of her life and died young, but in the meantime figured out how to program Charles Babbage’s (never-finished) Analytical Engine. She would have been a shoo-in for a 3o-under-30 list back then, or more like a 1-under-30 list if you narrowed the list to tech. In other words, Ada Lovelace was the first programmer, even without a functioning computer, and in general, hold on to your Google Glasses, women were the first programmers on real computers. I realized that after reading the Alan Turing biography and learning about the women at Bletchley Park who operated the machines he designed and decrypted German codes during World War II. They were even called “computers”. So, women representation in software development hasn’t just been dropping since the 1980's, it’s been dropping since the 1800's, where it started at 100%. After WWII, men started crowding into the field and getting those plum jobs at IBM, but there were still influential women like the colorful and later Admiral Grace Hopper, who developed the earliest compiled languages like COBOL and popularized bugs (just she and Countess Ada are enough for a new Bill and Ted movie where they go back in time and collect famous computing women to present at a Google diversity seminar). But even if you turn up your nose at COBOL (although that was a nice skill to have during the Y2K scare), every modern programming language, and concepts like GUIs, and design patterns like MVC, can be traced back to Adele Golderberg’s Smalltalk (if you’ve ever wondered why Objective-C is the way it is, look no further…). Less popularly known, one of my MIT profressors, Barbara Liskov, won the Turing Award and developed influential languages like CLU and Argus (CLU was used in the software engineering course she taught where I learned about data abstraction, commenting code, and not working with partners on your final project if you can possibly help it). In the meantime, Ada did get her own computer language. And she’s shown up here and there in pop culture among those in the know, for example in, appropriately, the William Gibson/Bruce Sterling steampunk novel The Difference Engine. So maybe a history of computing is too ambitious, but there’s still plenty of material for a History of Women in Computing. Someone, get on that! The History of Programming – Technicat on Software – Medium Label: grist Date: August 13, 2017 at 09:27PM Labeled: August 13, 2017 at 09:28PM via GitHub http://ift.tt/2w4LNcS August 13, 2017 at 09:32PM via GitHub http://ift.tt/2w4LNcS [100-days-of-writing] Claude Shannons Creative Thinking Speech: A Genius Reveals How To Be Creative Claude Shannons Creative Thinking Speech: A Genius Reveals How To Be Creative By janzeteachesit Assigned to Claude Shannon’s “Creative Thinking” Speech: A Genius Reveals How To Be Creative http://ift.tt/2feUtHb GRIST4 Writing Claude Shannon’s “Creative Thinking” Speech: A Genius Reveals How To Be Creative A speech from one of the 20th century’s most brilliant minds about how to be creative. Henry KimAug 3 As a part of writing the biography of Claude Shannon, we waded through papers — tons of them. At the Library of Congress alone, there were 21 boxes worth of Claude Shannon papers. We went through each carton, page by page. And that was just the beginning. Outside of what was in that collection, there were other published and unpublished volumes of Shannon’s work, totaling in the thousands of pages; never-before-seen interviews given to us by his family and others; letters and memos from countless collaborators and friends. We pored over several decades’ worth of the Otsego County Times, Shannon’s hometown paper, and a similar set of records produced by the Bell Laboratories. In our hunting, we found some gems. There was this 1953 letter from Alan Turing to Claude Shannon: (Courtesy of the Library of Congress, LC-MSS84831) Almost one year later to the day, Alan Turing would be dead. His death was ruled a suicide, though its circumstances remain in dispute to this day. Other letters were more light-hearted. We chuckled at the correspondence Shannon had with Dr. Carl Sagan (about, of all things, a poem about Rubik’s cubes that Shannon had written): (Courtesy of the Library of Congress, LC-MSS84831) Dr. Sagan’s response: (Courtesy of the Library of Congress, LC-MSS84831) There were items that didn’t necessarily speak to Shannon’s scientific collaborations but gave us a window into his personality. We found, for example, a purchase order Shannon made while at Bell Labs. It wasn’t the most consequential historical artifact, but after reading so many of Shannon’s serious academic papers, the detailed account of these purchases brought the tinkering Shannon to life: (Courtesy of the Library of Congress, LC-MSS84831) And so on. All of this wading through paper sounds like a lot of work, and it was — but it is also a thrill, the absolute best part of biographical research. Yes, you have to sift through a lot of historical hay, but every now and again, you find a needle in the palm of your hand. One example: the day we found the wedding announcement for Claude Shannon’s parents. It was front page news in 1909 Gaylord, MI (Shannon’s hometown), and the details — how Claude’s father caught a train in the middle of the night to the home of his future in-laws; what Claude’s mother’s wedding dress looked like the day of — added texture to our narrative. (Credit: Otsega County Library Newspaper Archive) Finding that nugget of news felt like hitting a game-winning shot. And there were enough moments like that to help us power through the five years it took to finish the book. But no day, no moment, was quite like the one when we found a 1952 Claude Shannon speech that had been all but forgotten. Claude Shannon thought about and wrote about many things — but he didn’t pontificate about creativity, or thinking, or genius. Better, he thought, to do those things than to talk about them. There was one exception, though, and it was a speech he gave in 1952 to his fellow Bell Labs engineers. The speech was in a volume of unpublished papers, buried toward the end. We’ve written about it elsewhere, adding our own interpretation to a genius’s musings on genius. But for the sake of giving Shannon fans — both old and new — the same thrill we had when we stumbled on this speech, we decided to put the full text of it here. “Creative Thinking” Claude Shannon March 20, 1952 Up to 100% of the amount of ideas produced, useful good ideas produced by these signals, these are supposed to be arranged in order of increasing ability. At producing ideas, we find a curve something like this. Consider the number of curves produced here — going up to enormous height here. A very small percentage of the population produces the greatest proportion of the important ideas. This is akin to an idea presented by an English mathematician, Turing, that the human brain is something like a piece of uranium. The human brain, if it is below the critical lap and you shoot one neutron into it, additional more would be produced by impact. It leads to an extremely explosive of the issue, increase the size of the uranium. Turing says this is something like ideas in the human brain. There are some people if you shoot one idea into the brain, you will get a half an idea out. There are other people who are beyond this point at which they produce two ideas for each idea sent in. Those are the people beyond the knee of the curve. I don’t want to sound egotistical here, I don’t think that I am beyond the knee of this curve and I don’t know anyone who is. I do know some people that were. I think, for example, that anyone will agree that Isaac Newton would be well on the top of this curve. When you think that at the age of 25 he had produced enough science, physics and mathematics to make 10 or 20 men famous — he produced binomial theorem, differential and integral calculus, laws of gravitation, laws of motion, decomposition of white light, and so on. Now what is it that shoots one up to this part of the curve? What are the basic requirements? I think we could set down three things that are fairly necessary for scientific research or for any sort of inventing or mathematics or physics or anything along that line. I don’t think a person can get along without any one of these three. The first one is obvious — training and experience. You don’t expect a lawyer, however bright he may be, to give you a new theory of physics these days or mathematics or engineering. The second thing is a certain amount of intelligence or talent. In other words, you have to have an IQ that is fairly high to do good research work. I don’t think that there is any good engineer or scientist that can get along on an IQ of 100, which is the average for human beings. In other words, he has to have an IQ higher than that. Everyone in this room is considerably above that. This, we might say, is a matter of environment; intelligence is a matter of heredity. Those two I don’t think are sufficient. I think there is a third constituent here, a third component which is the one that makes an Einstein or an Isaac Newton. For want of a better word, we will call it motivation. In other words, you have to have some kind of a drive, some kind of a desire to find out the answer, a desire to find out what makes things tick. If you don’t have that, you may have all the training and intelligence in the world, you don’t have questions and you won’t just find answers. This is a hard thing to put your finger on. It is a matter of temperament probably; that is, a matter of probably early training, early childhood experiences, whether you will motivate in the direction of scientific research. I think that at a superficial level, it is blended use of several things. This is not any attempt at a deep analysis at all, but my feeling is that a good scientist has a great deal of what we can call curiosity. I won’t go any deeper into it than that. He wants to know the answers. He’s just curious how things tick and he wants to know the answers to questions; and if he sees thinks, he wants to raise questions and he wants to know the answers to those. Then there’s the idea of dissatisfaction. By this I don’t mean a pessimistic dissatisfaction of the world — we don’t like the way things are — I mean a constructive dissatisfaction. The idea could be expressed in the words, This is OK, but I think things could be done better. I think there is a neater way to do this. I think things could be improved a little. In other words, there is continually a slight irritation when things don’t look quite right; and I think that dissatisfaction in present days is a key driving force in good scientists. And another thing I’d put down here is the pleasure in seeing net results or methods of arriving at results needed, designs of engineers, equipment, and so on. I get a big bang myself out of providing a theorem. If I’ve been trying to prove a mathematical theorem for a week or so and I finally find the solution, I get a big bang out of it. And I get a big kick out of seeing a clever way of doing some engineering problem, a clever design for a circuit which uses a very small amount of equipment and gets apparently a great deal of result out of it. I think so far as motivation is concerned, it is maybe a little like Fats Waller said about swing music — “either you got it or you ain’t.’’ if you ain’t got it, you probably shouldn’t be doing research work if you don’t want to know that kind of answer. Although people without this kind of motivation might be very successful in other fields, the research man should probably have an extremely strong drive to want to find out the answers, so strong a drive that he doesn’t care whether it is 5 o’clock — he is willing to work all night to find out the answers and al weekend if necessary. Well now, this is all well and good, but supposing a person has these three properties to a sufficient extent to be useful, are there any tricks, any gimmicks that he can apply to thinking that will actually aid in creative work, in getting the answers in research work, in general, in finding answers to problems? I think there are, and I think they can be catalogued to an certain extent. You can make quite a list of them and I think they would be very useful if one did that, so I am going to give a few of them which I have thought up or which people have suggested to me. And I think if one consciously applied these to various problems you had to solve, in many cases you’d find solutions quicker than you would normally or in cases where you might not find it at all. I thing that good research workers apply these things unconsciously; that is, they do these things automatically and if they were brought forth into the conscious thinking that here’s a situation where I would try this method of approach that would probably get there faster, although I can’t document this statement. The first one that I might speak of is the idea of simplification. Suppose that you are given a problem to solve, I don’t care what kind of a problem — a machine to design, or a physical theory to develop, or a mathematical theorem to prove, or something of that kind — probably a very powerful approach to this is to attempt to eliminate everything from the problem except the essentials; that is, cut it down to size. Almost every problem that you come across is befuddled with all kinds of extraneous data of one sort or another; and if you can bring this problem down into the main issues, you can see more clearly what you’re trying to do and perhaps find a solution. Now, in so doing, you may have stripped away the problem that you’re after. You may have simplified it to a point that it doesn’t even resemble the problem that you started with; but very often if you can solve this simple problem, you can add refinements to the solution of this until you get back to the solution of the one you started with. A very similar device is seeking similar known problems. I think I could illustrate this schematically in this way. You have a problem P here and there is a solution S which you do not know yet perhaps over here. If you have experience in the field represented, that you are working in, you may perhaps know of a somewhat similar problem, call it P’, which has already been solved and which has a solution, S’, all you need to do — all you may have to do is find the analogy from P’ here to P and the same analogy from S’ to S in order to get back to the solution of the given problem. This is the reason why experience in a field is so important that if you are experienced in a field, you will know thousands of problems that have been solved. Your mental matrix will be filled with P’s and S’s unconnected here and you can find one which is tolerably close to the P that you are trying to solve and go over to the corresponding S’ in order to go back to the S you’re after. It seems to be much easier to make two small jumps than the one big jump in any kind of mental thinking. Another approach for a given problem is to try to restate it in just as many different forms as you can. Change the words. Change the viewpoint. Look at it from every possible angle. After you’ve done that, you can try to look at it from several angles at the same time and perhaps you can get an insight into the real basic issues of the problem, so that you can correlate the important factors and come out with the solution. It’s difficult really to do this, but it is important that you do. If you don’t, it is very easy to get into ruts of mental thinking. You start with a problem here and you go around a circle here and if you could only get over to this point, perhaps you would see your way clear; but you can’t break loose from certain mental blocks which are holding you in certain ways of looking at a problem. That is the reason why very frequently someone who is quite green to a problem will sometimes come in and look at it and find the solution like that, while you have been laboring for months over it. You’ve got set into some ruts here of mental thinking and someone else comes in and sees it from a fresh viewpoint. Another mental gimmick for aid in research work, I think, is the idea of generalization. This is very powerful in mathematical research. The typical mathematical theory developed in the following way to prove a very isolated, special result, particular theorem — someone always will come along and start generalization it. He will leave it where it was in two dimensions before he will do it in N dimensions; or if it was in some kind of algebra, he will work in a general algebraic field; if it was in the field of real numbers, he will change it to a general algebraic field or something of that sort. This is actually quite easy to do if you only remember to do it. If the minute you’ve found an answer to something, the next thing to do is to ask yourself if you can generalize this anymore — can I make the same, make a broader statement which includes more — there, I think, in terms of engineering, the same thing should be kept in mind. As you see, if somebody comes along with a clever way of doing something, one should ask oneself “Can I apply the same principle in more general ways? Can I use this same clever idea represented here to solve a larger class of problems? Is there any place else that I can use this particular thing?” Next one I might mention is the idea of structural analysis of a problem. Suppose you have your problem here and a solution here. You may have two big a jump to take. What you can try to do is to break down that jump into a large number of small jumps. If this were a set of mathematical axioms and this were a theorem or conclusion that you were trying to prove, it might be too much for me try to prove this thing in one fell swoop. But perhaps I can visualize a number of subsidiary theorems or propositions such that if I could prove those, in turn I would eventually arrive at this solution. In other words, I set up some path through this domain with a set of subsidiary solutions, 1, 2, 3, 4, and so on, and attempt to prove this on the basis of that and then this one the basis of these which I have proved until eventually I arrive at the path S. Many proofs in mathematics have been actually found by extremely roundabout processes. A man starts to prove this theorem and he finds that he wanders all over the map. He starts off and prove a good many results which don’t seem to be leading anywhere and then eventually ends up by the back door on the solution of the given problem; and very often when that’s done, when you’ve found your solution, it may be very easy to simplify; that is, to see at one stage that you may have short-cutted across here and you could see that you might have short-cutted across there. The same thing is true in design work. If you can design a way of doing something which is obviously clumsy and cumbersome, uses too much equipment; but after you’ve really got something you can get a grip on, something you can hang on to, you can start cutting out components and seeing some parts were really superfluous. You really didn’t need them in the first place. Now one other thing I would like to bring out which I run across quite frequently in mathematical work is the idea of inversion of the problem. You are trying to obtain the solution S on the basis of the premises P and then you can’t do it. Well, turn the problem over supposing that S were the given proposition, the given axioms, or the given numbers in the problem and what you are trying to obtain is P. Just imagine that that were the case. Then you will find that it is relatively easy to solve the problem in that direction. You find a fairly direct route. If so, it’s often possible to invent it in small batches. In other words, you’ve got a path marked out here — there you got relays you sent this way. You can see how to invert these things in small stages and perhaps three or four only difficult steps in the proof. Now I think the same thing can happen in design work. Sometimes I have had the experience of designing computing machines of various sorts in which I wanted to compute certain numbers out of certain given quantities. This happened to be a machine that played the game of nim and it turned out that it seemed to be quite difficult. If took quite a number of relays to do this particular calculation although it could be done. But then I got the idea that if I inverted the problem, it would have been very easy to do — if the given and required results had been interchanged; and that idea led to a way of doing it which was far simpler than the first design. The way of doing it was doing it by feedback; that is, you start with the required result and run it back until — run it through its value until it matches the given input. So the machine itself was worked backward putting range S over the numbers until it had the number that you actually had and, at that point, until it reached the number such that P shows you the correct way. Well, now the solution for this philosophy which is probably very boring to most of you. I’d like now to show you this machine which I brought along and go into one or two of the problems which were connected with the design of that because I think they illustrate some of these things I’ve been talking about. In order to see this, you’ll have to come up around it; so, I wonder whether you will all come up around the table now. This piece was the by-product of work on this book: Yes, it’s out. And of course, we’d love for you to read it. Conveniently and fittingly, It’s available in both analog and digital formats: paperback, audiobook, Kindle. We figured the book needed to have one foot in the world Claude lived in and one in the world he helped create. (Plus, that’s how the publisher was planning to do it anyway, though it’s nice to pretend that we did it on purpose as some grand metaphor about our subject’s life.) If you enjoyed this story, please recommend and share to help others find it! Feel free to leave a comment below. The Mission publishes stories, videos, and podcasts that make smart people smarter. You can subscribe to get them here. Claude Shannon’s “Creative Thinking” Speech: A Genius Reveals How To Be Creative Label: grist Date: August 15, 2017 at 07:33PM Labeled: August 15, 2017 at 07:36PM via GitHub http://ift.tt/2v00edT August 15, 2017 at 07:41PM via GitHub http://ift.tt/2v00edT [100-days-of-writing] Alien Intelligences and discriminatory algorithms - Chris Stucchio Alien Intelligences and discriminatory algorithms - Chris Stucchio By janzeteachesit Assigned to Alien Intelligences and discriminatory algorithms - Chris Stucchio http://ift.tt/1LBf9D7 GRIST4 Writing Alien Intelligences and discriminatory algorithms Mon 21 March 2016 bias detection / frequentist statistics / statistics In the Star Trek episode Let That Be Your Last Battlefield the Enterprise encounters two human-looking aliens (as is the Star Trek custom) from the planet Cheron. These aliens are full of intense ethnic hatred towards each other based on historical issues on their planet. This episode was broadcast in 1969; to a 2016 TV watcher like myself it comes off as a ham-handed criticism of American racial attitudes at the time. We, the human viewers, are of course oblivious to whatever happened on Cheron prior to this episode - most likely the human readers of my blog didn't notice that the Cheronese are mirror images of each other. As a result we find the hatred and conflict between the two Cheronese completely nonsensical. As aliens to the Cheronese, we (either the viewer or Captain Kirk) just don't care. Insofar as we might favor one Cheronese over the other, that would only be due to the danger or reward to the Enterprise. Captain Kirk cares about protecting the ship and discovering new life and new civilizations - minor aesthetic differences between two people from the same civilization are irrelevant to him. On Star Trek the majority of the aliens are just humans with colored makeup. In real life aliens will be truly different. One very important category of "alien" is machine learning - machine learning algorithms are completely alien to us and this fact is unfortunately lost on a lot of innumerate journalists. As AI-driven decisions are becoming more commonplace (e.g. in predicting crime, creditworthiness, advertisement delivery), pundits and journalists have become increasingly concerned that such algorithms might be "discriminatory" against various special classes of humans. Typically these pundits attribute to algorithms various human qualities; the mere ability to discriminate by race is treated as an assumption that the algorithm is doing so and in the same way that humans would. Cathy O'Neil - aka mathbabe - is one of the foremost writers in this field. In spite of her blog's title, she uses negligible amounts of math but lots of emotional rhetoric to groundlessly criticize statistics in order to sell books. Unfortunately this is all a load of anthropomorphic nonsense. Algorithms aren't people. While humans are known to be easily biased on physical traits of other humans, algorithms aren't. To a human, "race" or "sex" is a fundamental trait of another person. An algorithm cares about the 26'th element of a 100 element array as much as Kirk cares about who is black on the left - if it's predictive of something he cares about he'll pay attention, otherwise he doesn't care. It's a fair criticism that algorithms can reproduce biases in their inputs. But the assumption that they will do this - just like humans do - is fundamentally flawed. In reality, if the inputs to an algorithm are sufficiently informative, the algorithm will correct the bias in the inputs! This post is going to be somewhat mathematical. Unfortunately, while it's easy to criticize algorithms on emotional and anthropomorphic terms, it's very hard to defend them on that basis. So I'm going to introduce and explain linear regression - the simplest machine learning algorithm that I can think of - and show what conditions lead to algorithmic discrimination. What this article is about This article is about when and why an algorithm would discriminate, and more importantly when it won't. To illustrate this I'm going to construct a few hypothetical worlds, run an algorithm on that hypothetical world, and illustrate the output. By inverting this process, we can conclude that if an algorithm behaves a certain way, that is evidence that the world behaves in a corresponding manner (this is the uncomfortable part). At the end I also discuss some ethical issues, but I take no particular position. My main goal here is to push discussion of this issue in a less innumerate direction. What this article is NOT about This article is strictly NOT about badly implemented algorithms. Most of the people commenting on algorithmic discrimination are not arguing that a specific algorithm has an off-by-one error or proposing that we switch from a random forest to a deep neural network. I've never seen any LaTeX on mathbabe.org. In the event that an algorithm is incorrectly predicting outcomes, we can all agree that statisticians should do their jobs better. All the simulation experiments in this article will be carefully tuned to avoid this situation. I'll be generating gaussian data and fitting a linear model to it via least squares. The key point here is to avoid methodological errors - because I'm setting up the problem to be simple and easily solvable, you can't get a significantly better result via better algorithm choices. Instead, we'll need to actually recognize and confront the reality that good algorithms might yield correct results we don't like. I'm very strictly NOT claiming that all real world models are perfect. I'm just assuming that bad models are a math problem with a math solution and therefore beyond the reach of Techcrunch and Mathbabe. Different kinds of discrimination To begin with, we need to define what we mean by discrimination, and unfortunately there are several definitions floating around. Direct Discrimination: This form of discrimination is basically traditional racism - you encode your preferences into a model. However, this is pretty uncommon in more formal predictive models. When writing code, very few data scientists will write this: if applicant.race == 'black': fico -= 100 That's certainly something that will be spotted in code review, and it's also pretty easy to prevent with automated tools, e.g.: for a in applicants: a.race = None predictive_algorithm(applicants) I'm going to call a data set without direct information on protected classes scrubbed. Disparate Impact: This is when you have an unbiased algorithm, but the outcome of that algorithm is affects different protected classes differently. Direct discrimination can certainly cause a disparate impact, but there are lots of other possible causes. For example, if black people are taller than white people, a basketball competition will have a disparate inpact in their favor. Redundant encoding: This is what happens when you give an algorithm lots of data, and ask it to learn hidden features of the underlying probability distribution. The redundant encoding may then rediscover (at least probabilistically) some data which has been scrubbed. An example of this, consider the following example from Delip Rao. A data set has race scrubbed from it. However, it includes location and income. A second order kernel might then discover Feature6578 = Loc=EastOakland && Income<10k. This feature is strongly correlated with race. So although race was scrubbed from the algorithm, this data was redundantly encoded in the data. One really important thing to recognize is that none of these forms of discrimination necessarily yield incorrect results. This means that if gambler A has a gambling strategy based on some sort of discriminatory algorithm, and gambler B has a non-discriminatory one, gambler A might be systematically taking money from gambler B. Bias: This is a statistical property of an algorithm, and there are a variety of fairly technical definitions in different contexts. The most useful one here is that bias is the difference between an estimator's expected value and the true value of a parameter. Linear regression For most of this discussion, I'm going to take linear regression as a toy model. Linear regression is one of the simplest algorithms for building a predictor. The basic idea is the following. Consider an output variable - a quantity I wish to predict. I'm given a set of points: The value is a d-dimensional vector representing the my input variables. In python terms, it's an array of floats of length d. The value is a real number which represents my output. In python terms, it's a single float. Linear regression is the process of coming up with a function of the following form which predicts given : The vector is another (fixed) d-dimensional vector, and is a scalar. In python terms, we want a predictor of the form: def y_predict(x): assert(len(x) == d) result = beta for i in range(d): result += alpha[i]x[i] return result Using the numpy library for python, one can also simplify this to return dot(alpha, x) + beta, but I wrote out the for-loop once for pedagogical purposes. The goal of linear regression is to find the values of alpha (an array of floats) and beta (a float) which fit the data as closely as possible, perhaps subject to specific constraints (e.g. sparsity, matching a prior). In this post I'll always be doing least squares fits - choosing to minimize Pythonic example Our first example is very simple. We have 3 variables and a true model alpha_true = [1,2,3]. We have a data set of 1000 3-dimensional vectors, together with outputs. The outputs are generated by simply taking the true model and adding random noise to it. In python code: from numpy import from numpy.linalg import lstsq from scipy.stats import norm nvars = 3 alpha_true = [1,2,3] N = 1000 data = norm(0,1).rvs((N, nvars)) output = dot(data, alpha_true) + norm(0,1).rvs(N) print lstsq(data, output) The output array is: array([ 0.98027674, 2.0033624 , 3.00109578]) This is pretty close to the true value used to generate the input, as it should be. Real world example Suppose we wish to predict first year GPA in college. The variable x[0] might represent an SAT Z-score and the variable x[1] might represent a high school exit exam Z-score. The variable y could represent first year GPA. Then linear regression might yield x[0] = 0.368 and x[1] = 0.287 (example is truncated from here). So the prediction would be: (Here is not directly listed in the paper, but it is a concrete and known value.) What if race/other protected class doesn't matter? Lets consider the following situation. Suppose we want to predict an output variable - say college GPA, following along the example above. Suppose we have two predictive variables - SAT z-score and exit exam Z-score. We also have race as a third variable. Lets assume that for each person, race has no causal relationship with GPA. Suppose we run a linear regression. What will we get? In python terms we've generated the data as follows: alpha_true = [0.368, 0.287, 0] N = 1000 data = norm(0,1).rvs((N, nvars)) data = zeros(shape=(N,nvars), dtype=float) data[:,0:2] = norm(0,1).rvs((N,2)) #Z-score variables data[:,2] = bernoulli(0.25).rvs(N) #Race, 1 if black output = dot(data, alpha_true) + norm(0,1).rvs(N) The output is something along the lines of alpha=[ 0.36679413, 0.32865146, 0.0110941 ] - we rediscover that SAT and exit exam matter, and race doesn't. Due to statistical noise, the coefficient on race (the third variable) isn't zero, but it's very close. Additionally, there is no particular sign on it - depending on how the noise looks, our predictor might slightly overpredict or underpredict black GPA. In this case, we have no significant discrimination, no disparate impact, and no redundant coding. We also have no bias. Most importantly, the algorithm had the opportunity to introduce bias but chose not to. That's hardly surprising; the algorithm's only desire in life is minimizing squared error - being unkind to black people a silly thing that humans seem to enjoy for no apparent reason. If race (or x[2] to the algorithm) is not useful in minimizing squared error then the square error minimizer will ignore it, just as Captain Kirk barely noticed the mirror image of the aliens. Another great essay on distinguishing algorithmic desires from human desires is Bostrom's parable of the paperclip maximizer (see also lesswrong). What if black people don't perform as well? Now lets consider the following situation. Due to various historical factors, black people perform worse at the pre-college level. At the college level, lets suppose they perform exactly as well as their pre-college scores predict. I.e., our causal model changes as follows: data = norm(0,1).rvs((N, nvars)) data = zeros(shape=(N,nvars), dtype=float) data[:,0:2] = norm(0,1).rvs((N,2)) #Z-score variables data[:,2] = bernoulli(0.25).rvs(N) #Race, 1 if black data[where(data[:,2] == 1),0:2] -= 0.5 # Black people have lower SAT/GPA alpha_true = [0.368, 0.287, 0] #But holding SAT/GPA fixed, race doesn't matter. output = dot(data, alpha_true) + norm(0,1).rvs(N) What we are assuming in this case is that race still doesn't matter holding academics constant. I.e., a black person with a 1300 SAT is likely to have the same GPA as a white person with a 1300 SAT. The output? alpha = [ 0.36904923, 0.29184296, 0.02953688]. Just like before, we've faithfully reproduced our input model. However, we've now found a model with a disparate impact. The model we have predicts that blacks will score, on average, 0.3278 points lower. The reason the model predicts this is because it's true: In [15]: mean(output[where(data[:,2] == 1)]) #black people Out [15]: -0.300591159584 In [16]: mean(output[where(data[:,2] == 0)]) #white people Out [15]: -0.0107252756984 So in this case, our model has a disparate impact because it accurately reflects the world. If we want to avoid a disparate impact, the only way we can do that is by adding +0.30 to the scores of black people, but then we'll be increasing the squared error significantly. We also have no bias. What if measurements are biased? It's been claimed in many places that the SAT, high school GPA, and similar measures are biased against some groups. What would be the effect of this? Lets suppose we have the following relationship. Each person has an intrinsic ability. SAT and high school exit exam are noisy measurements of ability. Also, lets assume that these measurements are biased - the measurements reduce the scores of black people, but they do not reduce our output variable (namely college performance). Our model looks like this: ability = norm(0,1).rvs(N) #The true driver data = norm(0,1).rvs((N, nvars)) data = zeros(shape=(N,nvars), dtype=float) data[:,2] = bernoulli(0.25).rvs(N) #Race, 1 if black data[:,0] = 0.5ability[:] + norm(0,1).rvs(N) data[:,0] -= 0.5data[:,2] #Biasing the SAT data[:,1] = 0.5ability[:] + norm(0,1).rvs(N) data[:,1] -= 0.5data[:,2] #Biasing exit exams output = ability + norm(0,1).rvs(N) The net result of linear regression here is alpha = [ 0.34523587, 0.33528078, 0.31779809]. Our process in generating the data was biased, but our learning algorithm discovered that and corrected for it! If we scrubbed the data this result would be impossible. Running least squares on scrubbed data yields alpha = [ 0.29878373, 0.30869833] - we can't correct for bias because we don't know the variable being biased on. As an intellectual exercise, lets consider as a hypothetical that our data was biased differently. Suppose instead of being biased against blacks, our measurements were biased in favor. The outcome would be more or less the same except that the coefficient on race would be negative: alpha = [ 0.32611793, 0.34397119, -0.30572819]. This is pretty cool. Our machine learning algorithm doesn't seem to be doing what the pundits and journalists predict at all. Rather than incorporating human bias, it seems to be detecting it and correcting for it! That's because least squares isn't human. It doesn't know what data[:,0] or data[:,2] mean - all it knows is that it wants to predict the outcomes as accurately as possible. So in this example, we have no disparate impact and no bias. We do, however, have direct discrimination - the algorithm is discriminating in favor of blacks in order to cancel out biases earlier in the process. Also note: Under other circumstances, it's totally uncontroversial to claim that a statistical algorithm can eliminate bias. For example, you probably find it completely unsurprising that I can use statistics to correct for bias in a mobile phone's compass. Real world interlude The analysis above yields some interesting testable predictions. Supposing bias exists, we should be able to detect it by directly conditioning on race and observing the coefficient. If the coefficient is positive, it means that the observables are biased against that race. If it's negative, it means they are biased in favor. And if it's zero, it means things are unbiased. This analysis has actually been done. For example, this paper discovers that SAT, high school exit exams and similar predictors are mildly biased against Asians and fairly strongly in favor of blacks. These predictors are also mildly biased against students from high-income families, against women, and in favor of people with unmet educational need. Similar results more or less agree with this. Here's a blog post that links to data, so the interested reader can run this analysis themself. An alternate formulation of bias There is a different (but mathematically equivalent) way to formulate bias. Rather than subtracting from the input scores, we could equivalently add to the output scores. I.e., we previously chose as our model: data[:,0] = 0.5ability[:] + norm(0,1).rvs(N) data[:,0] -= 0.5data[:,2] #Biasing the SAT data[:,1] = 0.5ability[:] + norm(0,1).rvs(N) data[:,1] -= 0.5data[:,2] #Biasing exit exams output = ability + norm(0,1).rvs(N) What if we instead chose: data[:,0] = 0.5ability[:] + norm(0,1).rvs(N) data[:,1] = 0.5ability[:] + norm(0,1).rvs(N) output = ability + norm(0,1).rvs(N) output += 0.33data[:,2] The net result is the same - alpha = [ 0.32258076 0.32353926 0.3253351 ]. This is a pretty straightforward mathematical equivalence - we are just moving a variable from the left to the right. This means that we cannot distinguish between the inputs being biased or the factor we are biased on actually being directly causal. I.e., as far as linear regression (and many similar algorithms) is concerned, the propositions "SAT/Exit exams are biased against blacks" is equivalent to the statement "Blacks are 'intrinsically' superior in a manner not reflected in exit exam/SAT". The word 'intrinsically' means that either blackness, or some hidden variable which is correlated with it (the more likely possibility), directly causes outcomes to change. What if we scrub race, but redundantly encode it? Lets now consider the situation where race doesn't matter, and we've scrubbed the data, but we redundantly encode it. Lets suppose we have 3 new binary variables, generated via the following process: data[:,2] = racebernoulli(0.4).rvs(N) + bernoulli(0.1).rvs(N) data[:,3] = racebernoulli(0.4).rvs(N) + bernoulli(0.1).rvs(N) data[:,4] = racebernoulli(0.4).rvs(N) + bernoulli(0.1).rvs(N) data[:,2:] = minimum(data[:,2:],1.0) So for each person, we generate 3 new variables, which are either true or false. If a person is black, these variables have a 40% chance of being equal to 1, otherwise they have a 10% chance. This means that the more of these variables are true, the more likely it is that a person is black. The result of regression is alpha = [ 0.3374577 , 0.32448367, 0.04370261, -0.01621927, -0.02446477]. Even though our algorithm could, if it wanted to, determine a person's race, it has no reason to. This is true even if we include lots of redundant encoding, say 28 of them. The result is simply: alpha = [ 0.33345215, 0.32298627, -0.07885754, 0.00441561, 0.04332198, 0.00825558, -0.06916433, 0.06032788, 0.02769571, -0.01998633, 0.06123838, 0.04794704, -0.01579531, -0.00326249, -0.03947687, 0.00117585, -0.00274476, -0.02228296, -0.02865488, -0.03107947, -0.05825314, -0.06108869, 0.03893044, -0.06881212, 0.04479646, 0.09647968, 0.02672891, -0.04827223, 0.01878823, 0.03254893] In this situation, it's pretty easy to determine if a person is black - compute sum(data[i,2:]) and check whether it's closer to 0.428 or 0.128. If it's the former they are black, if it's the latter they aren't. The algorithm doesn't care about this redundant encoding because even if it knew, that's not useful. However, if we bias the inputs, suddenly the algorithm does care. Biasing the inputs (as described above) yields alpha = [ 0.32504926 0.30582667 0.14417805 0.08187899 0.11585452]. Equivalently, as discussed above, if race is directly causal (which is mathematically equivalent to bias), then the algorithm will also care. In short, redundant encoding has the same effect (albeit weaker) as directly encoding race. It allows an algorithm to correct for biased inputs or (mathematically equivalently) to discover that one group is intrinsically better/worse performing than another. But that's all it does - discover these effects. It doesn't introduce these effects if they are not present in the data. Redundant encoding does not cause algorithms to vote for Donald Trump. It doesn't make otherwise friendly algorithms wear bedsheets and burn a cross. All it does is give them a piece of data and allow them to discover how well that data predicts outcomes. Furthermore, they will only discover the redundant encoding if the data actually matters (very different from what humans do)! What if you do make statistical errors? Over at Algorithmic Fairness, Sorelle points out that sometimes an algorithm doesn't have sufficient training data to actually detect and correct for bias in the manner I've described: If an all-white company attempts to use their current employees as training data, i.e., attempts to find future employees who are like their current employees, then they’re likely to continue being an all-white company. What Sorelle fails to account for is that bias has no consistent sign. Bias like what he describes may exist, but our alien intelligence has no particular reason to give this bias a negative sign. In terms of our analogy above, suppose Captain Kirk jumps to conclusions as to which kind of Cherosian is more dangerous to the Enterprise than the other. Is there any reason for Kirk's bias to be positive towards the Black-Left Cherosian rather than the Black-Right one? As noted above, in the academic example described, the bias in favor of blacks due to excluding racial data is actually positive! By using a white student body and then doing the linear regression described here would yield more black students, not less. Correcting the bias involves heavily penalizing black applicants; failing to detect the need for this penalty will result in more being admitted. Bias can have a positive sign! I've seen similar effects in credit decisions, though I haven't gone through the details. (I'm a big fan of the randomcriticalanalysis blog because he provides his data.) Furthermore, this kind of issue falls well within the category of statisticians not doing their job well. Algorithms and processes may prematurely converge, but better statistics can prevent this. Fixing the bias is just a matter of running an experiment; allow in enough black students to measure performance in order to get a sufficiently high sample size (due to the law, does not have to approach ). The key point to takeaway is that bias can have any sign, positive or negative. Alien intelligences might develop bias, but there is no reason whatsoever to expect that their bias will be positive or negative. Sorelle's assumption that alien bias will mimic human bias is nothing but anthropomorphic reasoning. Ethical questions Most of the folks discussing ethical issues surrounding algorithms are, unfortunately, being either innumerate or disingenuous. Machine learning algorithms are not humans in disguise - they are completely alien "intelligences" which think about things in a totally different manner than we do. An alien intelligence (human viewers or Captain Kirk) look at the Vulcan and the Romulan above and don't see a big difference. I doubt anyone reading who isn't a Star Trek fan does either. However, over time, Kirk and the viewers learned to tell the difference. Vulcans tend to be peaceful science types like Spock. Romulans tend to be hostile and destroy Federation outposts. The prospect of being shot with energy weapons is the only thing that leads an alien intelligence to work hard to distinguish the difference between them - if both were equally hostile or equally peaceful, the viewer would treat their differences like those of the Cheronians. Machine learning is an alien intelligence. When implemented correctly it will not reproduce human biases; when human biases lead to factually incorrect results the alien intelligence will correct them as best it can. Even when given information about factors which bias humans, the alien intelligence will not learn that they matter unless they do. Algorithms care about different categories of human as little as dogs, goats or Romulans do. This leads us to an uncomfortable conclusion. In everyday life we usually assume that racism and stereotypes are factually incorrect and driven by human biases; therefore eliminating them we will get better outcomes all around. When different flavors of intelligence all converge to the same belief, that's evidence that the belief might be true. Intuitively we know and accept this fact. If 10 scientists - each using a different statistical methodology and experiment design - all draw the same conclusion about Gallium Arsenide photonic crystals then we will likely believe them. When 10 data scientists running 20 algorithms draw the same conclusion about humans, we instead call the statistics racist. We need to start accepting the possibility that discriminatory algorithms might be factually correct and then figure out what to do about it. The real ethical issues being raised are a lot trickier than what Techcrunch and Mathbabe want to admit. If the issue was simply incorrect algorithms giving wrong conclusions that seem racist, then the solution is simply smarter statisticians with better algorithms. The real ethical issue that the algorithms might be right. Suppose we build a credit allocation algorithm that turns out to be "racist" - i.e., the algorithm accurately predicts that a black person will be more likely to default than a similarly situated white person. Should we ignore this effect, and scrub the model sufficiently in order to eliminate this prediction? That seems like burying our heads in the sand. Is it even beneficial for any individual? Giving a person a loan they are likely to default on seems harmful to both the lender and the borrower, as is admitting a person to a college with a high probability of dropping out. (I've seen an analysis on the topic of credit but I haven't fully gone through the details. It looks to be in the ballpark of correct, though of course statistics is hard.) Ultimately there are no easy choices here. It would be wonderful if we had an algorithm which was racially unbiased (neither via direct discrimination nor redundant encoding), accurately predicts college dropouts/delinquent loans/etc, and also serves the needs of "social justice" (a poorly defined term which I understand mainly as mood affiliation). Unfortunately the more we look, the more it seems that we can't have all of these things simultaneously. The ethical question which no one really wants to discuss is what tradeoffs we are willing to make. How many delinquent loans is more individual or group fairness worth? My priors My initial inclination, as of a few years back, was to support race-blind policies - policies which eliminate direct discrimination and possibly redundant encoding. Such policies seem intrinsically fair to me. At this point I'm not so sure - the analysis above in the section "What if measurements are biased" suggests this might not be optimal. If we directly include race in a statistical analysis we can accurately correct for existing biases in the input data. This kind of suggests support for traditional affirmative action except that the sign is wrong - the most accurate correction we could do (at least for college admissions) would heavily penalize blacks and benefit Asians (the exact opposite of current policies). On the other hand, using an algorithm which is directly discriminatory or uses redundant encoding is intrinsically unfair on the level of individuals. I don't like this very much either. I'm now really confused on the topic. Conclusions Recently, AlphaGo (an AI) played several go matches against Lee Sedol, the champion of the humans. AlphaGo won. Fan Hui, the commentator could only say of AlphaGo's strategy: "It's not a human move. I've never seen a human play this move". Earlier this year, an AI was used to design antennas. These antennas also don't look like anything a human would have designed. Neither do the laser pulses generated by machine intelligences when attempting to optimally control quantum state excitation - something I studied a little bit in a previous life. Machine intelligence simply doesn't think the way humans do. When you encounter someone in Techcrunch or NPR assuming machines will reproduce human biases and conclusions, the right question to ask whether those people are clueless or lying to you. Alien Intelligences and discriminatory algorithms - Chris Stucchio Label: grist Date: August 15, 2017 at 07:37PM Labeled: August 15, 2017 at 07:41PM via GitHub http://ift.tt/2vHmQSG August 15, 2017 at 07:41PM via GitHub http://ift.tt/2vHmQSG [100-days-of-writing] Chris Stucchio Chris Stucchio By janzeteachesit Assigned to http://ift.tt/2uNw3Hv GRIST4 Chris Stucchio Label: grist Date: August 15, 2017 at 07:39PM Labeled: August 15, 2017 at 07:41PM via GitHub http://ift.tt/2w0heoT August 15, 2017 at 07:41PM via GitHub http://ift.tt/2w0heoT [100-days-of-writing] site:http://ift.tt/2i3DOaB filetype:pdf g8 - Google Search site:http://ift.tt/2i3DOaB filetype:pdf g8 - Google Search By janzeteachesit Assigned to http://ift.tt/2fJpNxT GRIST4 CSP site:http://ift.tt/2i3DOaB filetype:pdf g8 - Google Search Label: grist Date: August 15, 2017 at 08:04PM Labeled: August 15, 2017 at 08:06PM via GitHub http://ift.tt/2x2ZINX August 15, 2017 at 08:06PM via GitHub http://ift.tt/2x2ZINX [100-days-of-writing] Fractions infinity in Grades 3-4 | Math Code 'Zine Fractions infinity in Grades 3-4 | Math Code 'Zine By janzeteachesit Assigned to Fractions + infinity in Grades 3-4 | Math + Code 'Zine http://ift.tt/2i3oTgx GRIST4 STEM Maths Fractions + infinity in Grades 3-4 Alycia Cazzola, Melanie Drummond, Katherine Kenney, Rebekah McElhone & Judy Mullen — Grade 3-4 teachers, Wellington Catholic DSB We walk in and out of our classroom door several times in a school day. Have you ever stopped to consider the fractions we encounter on the way? What if I continue traveling half of the remaining distance, on and on, forever? Will I ever get to the door? Most children say: “No. It’s not possible!” But how can that be? I travel to the door lots of times, and on my way I pass all of these fractions, and I do get there. Is it only when I think about the fractions that it makes a difference? Children shaded 8×8 grids to represent the first 6 fractions on the way to the door: 1/2, 1/4, 1/8, 1/16, 1/32 and 1/64. Then we asked: “If you cut out all of the shaded areas, for all the fractions to the door, and then put them together to form a new shape, how big would that shape be? Would it fit in our classroom? In Guelph? In your hand? In Canada?” Children guessed that it would grow forever and would not fit in our classroom. But when they started cutting out the shaded parts, they noticed that they all fit in one single 8×8 square, and that “I can hold infinity in my hand!” Now that’s something they looked forward to sharing at home. The we used the Repeating Patterns coding environment at http://ift.tt/2fJoY8v [There’s fractions tutorial at this link you can use. We adapted it for our lesson plan. And we printed it for children to take home to share with parents.] Children used code to create grids with colour and we discussed the fractions hiding inside. Interestingly, most children first saw 4/8 in the grid above. 4 of 8 columns are red. Then 32/64. 32 out of 64 small squares are red. Then, lastly,they saw that 1/2 of the grid (or the columns, or the small squares) is red. There was a lot of incidental learning of equivalent fractions, which we had not planned to teach. “One thing I noticed was the kids’ ability to reduce fractions to their smallest for, ie. 50/100 was 1/2. Equivalent fractions was definitely a big lesson for that day!” “Here is a video of a student giving the equivalent fraction and naming 50/100. This was a big moment for me to see! I was impressed. We hadn’t worked with fractions that ‘big’ or named equivalent fractions.” “Here is another student who began to give me lots of information about coding and the we switched to talking about fractions and he was able to pull out the equavalent fraction too.” Then children were challenged to create the patterns below, and identify the fractions hiding inside. And they created their own fraction patterns! It was lots of fun! Fractions + infinity in Grades 3-4 | Math + Code 'Zine Label: grist Date: August 15, 2017 at 08:06PM Labeled: August 15, 2017 at 08:11PM via GitHub http://ift.tt/2wOaDvn August 15, 2017 at 08:17PM via GitHub http://ift.tt/2wOaDvn [100-days-of-writing] Repeating Patterns Repeating Patterns By janzeteachesit Assigned to http://ift.tt/2i3Ysaq GRIST4 STEM Math Repeating Patterns Label: grist Date: August 15, 2017 at 08:08PM Labeled: August 15, 2017 at 08:11PM via GitHub http://ift.tt/2wOej0d August 15, 2017 at 08:17PM via GitHub http://ift.tt/2wOej0d [100-days-of-writing] MATH and CODE MATH and CODE By janzeteachesit Assigned to http://ift.tt/1XkXSh0 GRIST4 STEM Math MATH and CODE Label: grist Date: August 15, 2017 at 08:10PM Labeled: August 15, 2017 at 08:11PM via GitHub http://ift.tt/2vC2XOr August 15, 2017 at 08:17PM via GitHub http://ift.tt/2vC2XOr [100-days-of-writing] TIMESQUARE DIY Watch Kit - Red Display Matrix ID: 1106 - $29.95 : Adafruit Industries Unique & fun DIY electronics and kits TIMESQUARE DIY Watch Kit - Red Display Matrix ID: 1106 - $29.95 : Adafruit Industries Unique & fun DIY electronics and kits By janzeteachesit Assigned to TIMESQUARE DIY Watch Kit - Red Display Matrix ID: 1106 - $29.95 : Adafruit Industries, Unique & fun DIY electronics and kits http://ift.tt/IDKVch GRIST4 STEM TIMESQUARE DIY Watch Kit - Red Display Matrix ID: 1106 - $29.95 : Adafruit Industries, Unique & fun DIY electronics and kits Show up stylish AND on time to any event with this awesome looking DIY watch. We have a few watch kits here at Adafruit but we finally have one that looks good and fits well, even for ladies and kids and others with smaller wrists and hands. Its got a 8x8 bit matrix display and a repurposed silicone watch band for a professional look. 64 LEDs light up to tell you the time in a variety of ways. Built into the kit are 3 different watch 'faces' - a scrolling marquee with time and date, a binary watch display (for geeks, robots and binary fans), and a moon phase display (for beach-combers, werewolves). There's also a built in battery meter so you can check your battery life. Want to make your own watch? Easy! The microcontroller is an Arduino-compatible, all you need is an FTDI Friend and the Arduino IDE and you can design your own watch faces and upload them to the TIMESQUARE. This embedded content is from a site (www.youtube.com) that does not comply with the Do Not Track (DNT) setting now enabled on your browser. Clicking through to the embedded content will allow you to be tracked by www.youtube.com. Learn more about Adafruit's privacy policy here. Engineered for greatness by PaintYourDragon, this watch squeezes 500-1000 full time displays out of a coin battery, and a up to one year 'resting' lifetime, so you can use this as a day-to-day time keeper. This watch comes with a ultra bright red LED matrix and a black silicone watch band that fits all wrists from children to adult. The band is an "off-the-shelf" band that holds the watch in pretty well, we'll be creating other bands - the included band is to just get you started! This watch is meant to be hackable, from the software to the band! This is a DIY kit, and requires some basic soldering/assembly to put together. It is a beginner kit, so this is a fine project to use in learning how to solder. Tools are not included, you'll need a soldering iron, solder and diagonal cutters as a minimum. Check the tutorial page for details on what tools and steps are required to assemble. Take about 1-2 hours to put together. Build it in the afternoon and you'll be done in time to hit the clubs in the evening.For more information and downloads check out the page in the Adafruit Learning System. *To show the watch "in action" photos above have the LEDs on with the lights lowered and added the on-wrist photos with photo taken with flash & studio lighting. TIMESQUARE DIY Watch Kit - Red Display Matrix ID: 1106 - $29.95 : Adafruit Industries, Unique & fun DIY electronics and kits Label: grist Date: August 15, 2017 at 08:17PM Labeled: August 15, 2017 at 08:21PM via GitHub http://ift.tt/2vGQFT5 August 15, 2017 at 08:21PM via GitHub http://ift.tt/2vGQFT5 [100-days-of-writing] CodeSandbox: Online playground for React CodeSandbox: Online playground for React By janzeteachesit Assigned to https://codesandbox.io/ GRIST4 CSP CodeSandbox: Online playground for React Label: grist Date: August 16, 2017 at 10:07AM Labeled: August 16, 2017 at 10:16AM via GitHub http://ift.tt/2uJm766 August 16, 2017 at 10:21AM via GitHub http://ift.tt/2uJm766 [100-days-of-writing] 3 Ways to Design with Data room2learn Medium 3 Ways to Design with Data room2learn Medium By janzeteachesit Assigned to 3 Ways to Design with Data – room2learn – Medium http://ift.tt/2uJgx3t GRIST4 STEM 3 Ways to Design with Data – room2learn – Medium room2learnAug 16 3 Ways to Design with Data by room2learn Tick tock tick tock! We can all hear the time passing by as we inch closer to the start of the school year. Whether you’re an educator, teacher, or designer, a new school year gives you the opportunity to redesign your classroom — anything from changing the layout to adding new, smaller hacks to improve engagement. We’re big fans of trying out different layouts and seeing what happens, but there are ways to design in a more analytical, strategic way. In other words, we want to share three ways you could design with data in mind. Let’s take a closer look! The first method we’ll introduce is the Classroom Observation Protocol for Undergraduate STEM (COPUS). This process measures student-faculty interactions in the classroom setting based on the types of activities performed. Researchers observe each class with an Excel worksheet (included on the site) and a 30-second timer. During each 30-second interval, researchers check off activities performed by the instructor or the students on a list. All the information gathered could then be transformed into graphs that show the breakdown of class activities. The image below is a visual representation of two sample courses with different instructional approaches: the lecture-based course is primarily composed of the instructor lecturing and few interactions between students and the instructor (some question-answer). However, the active-learning model shows a diverse distribution of activities and a lot more interaction between the students and the instructor. Here at room2learn, we want to take this one step further. We know that space impacts learning, so after using this strategy, we invite you to think about how the layout of your room has impacted these activities and how a simple change in layout may shift your teaching practice. Let’s move on to the next two strategies! One of our favorite resources at room2learn is Edutopia. They have tons of great resources on tips and tricks to redesign your classroom space. We’ve taken two of their most effective “design with data” strategies and broken them down for you. The first is “classroom flow!” With “Classroom Flow,” the main concept is similar to COPUS as it involves observing the classroom in session. However, this exercise focuses more on having observers map out the way students and teachers move in the classroom. Here’s how to do it: Find an honest colleague or student who is free during a time that you teach! Ask them to come and observe how you and your students move in the classroom. Draw or design a diagram of your classroom, making sure to include any and all furniture and give it to your observer. Ask your colleague or student to observe you and your students and draw where everyone moves. Make sure to use one color for you and one color for your students! Meet with your colleague and discuss what they noticed! An example of a “classroom flow” observation sheet After outlining the movements in the classroom, you can easily see which parts of your classroom could use some redesign or extra attention, especially if you have one area of the map where movement is heavy. The map could also be used as a tool to identify underused spaces that could be transformed for new activities. For an example of how an architect observes a classroom, check out this blog post here. The next strategy uses our favorite brainstorming and designing tool — post-its! This is a great way to collectively brainstorm ways to improve a space or to solve an existing problem. Here’s one way to use sticky notes in tandem with the “classroom flow” strategy: After you’ve highlighted pain points in your classroom, post up sticky notes in that area. Then, ask students to brainstorm ways to solve that specific pain point. Having students generate ideas right in that area can help them come up with more viable ideas. If you read our post from two weeks ago, you know we are passionate about including students in your redesign process. Collecting real data from your classroom is an additional way to ensure that your classroom redesign is addressing the actual needs of your students. Happy designing! Have you collected data about your classroom space in an innovative way? Let us know at www.room2learn.org or Tweet us at @HackClassrooms! 3 Ways to Design with Data – room2learn – Medium Label: grist Date: August 16, 2017 at 10:40AM Labeled: August 16, 2017 at 10:41AM via GitHub http://ift.tt/2vJ3oop August 16, 2017 at 10:41AM via GitHub http://ift.tt/2vJ3oop [100-days-of-writing] How to live without sketch & rock with Photoshop (yeah for windows PC) How to live without sketch & rock with Photoshop (yeah for windows PC) By janzeteachesit Assigned to http://ift.tt/2x2Wjyj GRIST4 GR How to live without sketch & rock with Photoshop (yeah for windows PC) Label: grist Date: August 16, 2017 at 10:42AM Labeled: August 16, 2017 at 10:46AM via GitHub http://ift.tt/2uQ2UeP August 16, 2017 at 10:51AM via GitHub http://ift.tt/2uQ2UeP [100-days-of-writing] Going Material with Gravit Designer Gravit Designer Medium Going Material with Gravit Designer Gravit Designer Medium By janzeteachesit Assigned to http://ift.tt/2vJj2Aa GRIST4 GR Going Material with Gravit Designer – Gravit Designer – Medium Label: grist Date: August 16, 2017 at 10:45AM Labeled: August 16, 2017 at 10:46AM via GitHub http://ift.tt/2wfUjG3 August 16, 2017 at 10:51AM via GitHub http://ift.tt/2wfUjG3 [100-days-of-code] A Dozen Times Artificial Intelligence Startled The World A Dozen Times Artificial Intelligence Startled The World By janzeteachesit Assigned to http://ift.tt/2wfjo0l aimlnn A Dozen Times Artificial Intelligence Startled The World Label: AI-NN-ML Date: August 16, 2017 at 11:59AM Labeled: August 16, 2017 at 12:01PM via GitHub http://ift.tt/2wglZdE August 16, 2017 at 12:01PM via GitHub http://ift.tt/2wglZdE [100-days-of-code] Own Your Bot Archie.AI Medium Own Your Bot Archie.AI Medium By janzeteachesit Assigned to http://ift.tt/2pVZt7Q aimlnn Own Your Bot – Archie.AI – Medium Label: AI-NN-ML Date: August 16, 2017 at 12:01PM Labeled: August 16, 2017 at 12:06PM via GitHub http://ift.tt/2v2PUlp August 16, 2017 at 12:11PM via GitHub http://ift.tt/2v2PUlp [100-days-of-writing] (12) Stanford Webinar - Design Your Life: Part I: Reframe Your Passion - YouTube (12) Stanford Webinar - Design Your Life: Part I: Reframe Your Passion - YouTube By janzeteachesit Assigned to https://www.youtube.com/watch?v=8bYIQDlWj34+ GRIST4 Writing (12) Stanford Webinar - Design Your Life: Part I: Reframe Your Passion - YouTube Label: grist Date: August 16, 2017 at 03:59PM Labeled: August 16, 2017 at 04:01PM via GitHub http://ift.tt/2x5BwKM August 16, 2017 at 04:06PM via GitHub http://ift.tt/2x5BwKM [100-days-of-writing] (12) Stanford Webinar - Design Your Life: Part II: Prototypes for Personal Success - YouTube (12) Stanford Webinar - Design Your Life: Part II: Prototypes for Personal Success - YouTube By janzeteachesit Assigned to https://www.youtube.com/watch?v=qOwAkE0Sdbg GRIST4 Writing (12) Stanford Webinar - Design Your Life: Part II: Prototypes for Personal Success - YouTube Label: grist Date: August 16, 2017 at 04:00PM Labeled: August 16, 2017 at 04:01PM via GitHub http://ift.tt/2wbzvjH August 16, 2017 at 04:06PM via GitHub http://ift.tt/2wbzvjH [100-days-of-writing] Designing Your Life Stanford Life Design Lab Designing Your Life Stanford Life Design Lab By janzeteachesit Assigned to http://ift.tt/2fMJvZW GRIST4 Writing Designing Your Life — Stanford Life Design Lab Label: grist Date: August 16, 2017 at 04:01PM Labeled: August 16, 2017 at 04:06PM via GitHub http://ift.tt/2v2QXSt August 16, 2017 at 04:11PM via GitHub http://ift.tt/2v2QXSt [100-days-of-writing] Applied Design Skills and Technologies_Introduction | Building Student Success - BC's New Curriculum Applied Design Skills and Technologies_Introduction | Building Student Success - BC's New Curriculum By janzeteachesit Assigned to Applied Design, Skills and Technologies_Introduction | Building Student Success - BC's New Curriculum http://ift.tt/2uRbhXy GRIST4 DH DT ADST Applied Design, Skills and Technologies Introduction The ability to design and make, acquire skills as needed, and apply technologies is important in the world today and a key aspect of educating citizens for the future. The Applied Skills learning area has been re-envisioned as a K–12 program and renamed. The new Applied Design, Skills, and Technologies (ADST) curriculum is an experiential, hands-on program of learning through design and creation that includes skills and concepts from traditional and First Peoples practice; from the existing disciplines of Business Education, Home Economics, Information Technology, and Technology Education; and from new and emerging fields. It envisions a K–12 continuum fostering the development of the skills and knowledge that will allow students to create practical and innovative responses to everyday needs and problems. K–5 Foundations Students in Kindergarten to Grade 5 will have opportunities to develop foundations in Applied Design, Skills, and Technologies within the context of existing curricula. The curriculum provides Big Ideas and Curricular Competencies for Kindergarten but does not include any Content learning standards. The intent and requirement is that teachers use the learning standards for Curricular Competencies from Applied Design, Skills, and Technologies K–5 with grade-level content from other subject areas to provide students with cross-curricular opportunities to develop foundational mindsets and skills in design thinking and making. In the early years, students will be given opportunities to develop foundational skills in Applied Design, Skills, and Technologies through exploratory and purposeful play. As they get older and develop an interest in knowing how things work and making things that work, they will have opportunities to develop foundational skills in activities that have a practical and real-life focus. Students in Kindergarten to Grade 5 will develop the skills for design thinking and a maker mindset in cross-curricular contexts that they will bring to future explorations in Applied Design, Skills, and Technologies. Grades 6–9 Explorations Students in Grades 6 to 9 will have opportunities to explore specific areas of Applied Design, Skills, and Technologies while continuing to build their design thinking and foundational skills. The Applied Design, Skills, and Technologies 6–9 curriculum encompasses content from the four existing Applied Design, Skills, and Technologies disciplines (Business Education, Home Economics, Information and Communications Technology, and Technology Education) and new and emerging fields, and provide opportunities for choice, modularization, and a variety of delivery options. This approach provides provincial recognition of the variety and scope of existing locally developed middle years programs and a template for the development of additional local programs. As a result of their explorations in Grades 6 to 9, students may begin to show particular interest in and aptitude for specific Applied Design, Skills, and Technologies areas and set more specialized learning goals. Grades 10–12 Specializations Students in Grades 10 to 12 will have opportunities to specialize in a specific area or to continue to explore their interests in more than one area. The specialization might be within the disciplines Business Education, Culinary Arts, Home Economics, Information and Communications Technology, Media Arts, Technology Education, or Tourism, across these and other areas, or in emerging disciplines. The specialization might be driven by students’ desire for practical skills in a particular area, their interests and passions, or their plans for post-secondary education or careers. This will allow students in Grades 10 to 12, who are becoming increasingly independent, to personalize their learning by pursuing interests that are relevant to them. Features of the ADST curriculum There is a renewed focus on designing and making, the acquisition of skills, and the application of technologies The ADST curriculum is now a provincial curriculum for K–12 that can be delivered in different ways at different grade levels There is a common set of curricular competencies for all of the ADST (formerly Applied Skills) curricula that can also be used as a template for locally developed options now and in the future Design of the ADST curriculum Big Ideas The Big Ideas of the ADST curriculum are derived from the Curricular Competencies. The Big Ideas are intended to capture a progression of learning in applying design processes, skills, and technologies, as shown in the chart below. K–3 4–5 6–8 9–10 11–12 Applied Design Designs grow out of natural curiosity. Designs can be improved with prototyping and testing. Design can be responsive to identified needs. Social, ethical, and sustainability considerations impact design. Products can be designed for lifecycle. Applied Skills Skills can be developed through play. Skills are developed through practice, effort, and action. Complex tasks require the acquisition of additional skills. Complex tasks require the sequencing of skills. Personal design interests require the evaluation and refinement of skills. Applied Technologies Technologies are tools that extend human capabilities. The choice of technology and tools depends on the task. Complex tasks may require multiple tools and technologies. Complex tasks require different technologies and tools at different stages. Tools and technologies can be adapted for specific purposes. Curricular Competencies The Curricular Competencies are organized under three headings: Applied Design Applied Skills Applied Technologies The Curricular Competencies under Applied Design are further organized under subheadings that reflect general stages of designing and making. For Grades 4 to 12, these are: Understanding context Defining Ideating Prototyping Testing Making Sharing Elaborations for the Curricular Competencies provide definitions for clarity. The subheadings for Kindergarten to Grade 3 are simplified in order to be developmentally appropriate; for example, young children do not prototype, test, and make as discernibly separate stages when they are designing and making through exploratory and purposeful play. The three stages of Applied Design that are identified for Kindergarten to Grade 3 encompass all of the stages of designing and making that are identified at higher grade levels, but in a naturalistic and developmentally appropriate way. They are: Ideating Making Sharing An important feature of the ADST curriculum is that the Curricular Competencies do not change for every grade. They remain the same for Kindergarten to Grade 3, and then there are sets for Grades 4 to 5, 6 to 8, 9 to 10, and 11 to 12. Even then, the changes are quite incremental. This aspect of the curricular design is intended to provide a consistent focus for both students and teachers on the “doing” aspect of the curriculum and to encourage student metacognition. Students use and develop the core competencies of creative and critical thinking, communication, and the personal and social competencies through the Curricular Competencies of ADST. The chart below gives some examples (but not an exhaustive list). K–3 4–5 6–8 9–10 11–12 Thinking Generate ideas from their experiences and interests Add to others’ ideas Generate potential ideas and add to others’ ideas Screen ideas against the objective and constraints Generate potential ideas and add to others’ ideas Screen ideas against criteria and constraints Take creative risks in generating ideas and add to others’ ideas in ways that enhance them Critically analyze and prioritize competing factors, including social, ethical, and sustainability considerations, to meet community needs for preferred futures Take creative risks to identify gaps to explore as design space Critically analyze how competing social, ethical, and sustainability considerations impact designed solutions to meet global needs for preferred futures Communication Demonstrate their product, tell the story of designing and making their product Demonstrate their product and describe their process Demonstrate their product and describe their process, using appropriate terminology and providing reasons for their selected solution and modifications Demonstrate their product to potential users, providing a rationale for the selected solution, modifications, and procedures, using appropriate terminology Share their progress while making to increase feedback, collaboration, and, if applicable, marketing Personal and Social Explain how their product contributes to the individual, family, community, and/or environment Determine whether their product met the objective and contributes to the individual, family, community, and/or environment Identify the personal, social, and environmental impacts, including unintended negative consequences, of the choices they make about technology use Evaluate the personal, social, and environmental impacts, including unintended negative consequences, of the choices they make about technology use Analyze the role and impact of technologies in societal change, and the personal, social, and environmental impacts, including unintended negative consequences, of their choices of technology use Content The ADST curriculum does not specify any Content learning standards for Kindergarten through Grade 5. The intent is for teachers to use the Curricular Competencies from ADST K–5 with grade-level content from other areas of learning to provide students with cross-curricular opportunities to develop foundational mindsets and skills in design thinking and making. For example, students might design and build something based on the Content learning standards in the Science or Social Studies curriculum. For Grades 6 to 12, the Content is concept-based and includes learning standards for the four existing Applied Skills disciplines (Business Education, Home Economics, Information Technology, and Technology Education) and for new and emerging fields such as Media Arts. Content learning standards are stated as topics. This creates the space for students to personalize their learning by making choices about what they design and make and the depth and breadth of their learning on a particular topic based on their own interests and passions. The generality of the Content learning standards also facilitates inclusion by allowing the teacher or the student to adjust depth and breadth to match abilities. Grades 6 to 9 are intended as exploration years. For Grades 6 and 7, this is a new provincial curriculum; for Grades 8 and 9, it is a redesigned curriculum. The curriculum provides one set of Content options for Grades 6 and 7 that are intended to be short modules that may be offered in rotation. Over the two years, students may be exposed to several of these and perhaps other locally developed options that also use the Curricular Competencies of ADST with locally developed content. This approach provides provincial recognition of the variety and scope of existing locally developed middle years programs and a template for the development of additional local programs. There are separate sets of Content options for Grade 8 and Grade 9. These may be offered as modular rotations of varying length, as is common for Grade 8 now, or as full-year courses, as is often the case in Grade 9 now. The Content elaborations are non-mandatory curricular supports that suggest possible depth and breadth for teaching concepts. The Content options for Grade 10, 11, and 12 have been significantly redesigned and reorganized to build on the new program in Kindergarten to Grade 7 and the redesigned program in Grades 8 and 9, to maintain a focus on designing and making, and to reflect developments in the domain. Some courses have been combined, some have been eliminated, some have been renamed, and some have been moved to and from other learning areas. Economics 12 has been moved to the Social Studies learning area; new Computer Science 11 and 12 courses have been developed in the Mathematics learning area; and Media Arts 10–12, with a focus on the application of digital technologies, has been moved to the Applied Design, Skills, and Technologies learning area. These elective courses are intended to offer students opportunities to continue exploring their interests or to specialize in an area of interest. Considerations for delivering ADST At all grade levels The focus on hands-on designing and making, acquisition and honing of skills, and choosing and applying technologies requires a high degree of student choice, although there may still be a place for common activities for specific purposes — for example, to introduce new skills or equipment, to communicate safety procedures, or to explicitly focus on one aspect of the design process The curriculum is inclusive of modern and traditional First Peoples design, skills, and technologies. Students should have opportunities to learn from local First Peoples. This will require an understanding by both students and teachers of appropriation issues and that some knowledge is considered sacred Kindergarten to Grade 5 Students can be given opportunities to develop foundational skills in ADST through exploratory and purposeful play, and through designing and making activities related to the content in other areas of learning. This is already a normal practice in K–5 classrooms and will not require additional time or resources A single set of Curricular Competencies for Kindergarten to Grade 3 provides common language and continuity for the first four years Another set of Curricular Competencies for Grades 4 and 5, with more stages delineated for Applied Design, encourages students to take a more purposeful approach to designing and making Grades 6 and 7 The curriculum is designed to be modular to allow for choice and a variety of delivery models depending on school configuration and student interest The requirement will be that students experience a minimum of three modules of ADST in each of Grades 6 and 7. Schools may choose from among the modules provided in the provincial curriculum or develop new modules that use the Curricular Competencies of ADST 6–7 with locally developed content. Locally developed modules can be offered in addition to, or instead of, the modules in the provincial curriculum Schools that currently have an exploratory rotation may choose to continue with that delivery model for ADST. Schools that do not currently have an exploratory rotation may wish to develop one, or to teach ADST modules in an integrated cross-curricular way with other areas of learning Grades 8 and 9 Schools will be able to accommodate the redesigned ADST curriculum within their current delivery models The curriculum may be offered as modular rotations of varying length, as is common for Grade 8 now, or as full courses, as is often the case in Grade 9 now There are more Content learning standards for Grade 9, as schools often offer these as full courses Schools are expected to offer students the equivalent of a “full-year” program in ADST. This can be made up of one or more modules Schools may choose from among the modules provided in the provincial curriculum or develop new modules that use the Curricular Competencies of ADST 8 or 9 with locally developed content. Locally developed modules can be offered in addition to, or instead of, the modules in the provincial curriculum As the new ADST curriculum has explorations starting in Grade 6, schools may wish to offer students more choice in Grades 8 and 9 than was offered previously Grades 10 to 12 Schools will be able to provide a variety of elective courses in Applied Design, Skills, and Technologies to meet student interests Current Board/Authority Authorized (BAA) courses remain approved. School and districts interested in revising BAA courses or developing new ones are encouraged to use the Curricular Competencies that are common for all Applied Design, Skills, and Technologies courses. Last updated: June 27, 2016 Applied Design, Skills and Technologies_Introduction | Building Student Success - BC's New Curriculum Label: grist Date: August 16, 2017 at 05:53PM Labeled: August 16, 2017 at 05:56PM via GitHub http://ift.tt/2vKqDOM August 16, 2017 at 06:01PM via GitHub http://ift.tt/2vKqDOM [100-days-of-writing] Applied Design Skills and Technologies_Goals and Rationale | Building Student Success - BC's New Curriculum Applied Design Skills and Technologies_Goals and Rationale | Building Student Success - BC's New Curriculum By janzeteachesit Assigned to Applied Design, Skills and Technologies_Goals and Rationale | Building Student Success - BC's New Curriculum http://ift.tt/2fMG4lP GRIST4 ADST DH DT Applied Design, Skills and Technologies Goals and Rationale Rationale The Applied Design, Skills, and Technologies curriculum builds on students’ natural curiosity, inventiveness, and desire to create and work in practical ways. It harnesses the power of learning by doing, and provides the challenging fun that inspires students to dig deeper, work with big ideas, and adapt to a changing world. It provides learning opportunities through which students can discover their interests in practical and purposeful ways. Applied Design, Skills, and Technologies includes skills and concepts from the disciplines of Business Education, Home Economics, Information Technology, and Technology Education, as well as rich opportunities for cross-curricular work and space for new and emerging areas, such as Media Arts. Business Education builds an understanding of business skills and concepts in the context of current technology, ethical standards, and an increasingly global economy, empowering students with economic, financial, consumer, and communication skills for lifelong participation in local and global contexts. Home Economics focuses on fundamental needs and practical concerns of individuals and families in a changing and challenging world, It integrates knowledge, processes, and practical skills from multiple areas, including foods, textiles, and family studies, and provides opportunities for creative applications and critical examination from global citizenship perspectives. Information Technology encompasses evolving processes, systems, and tools for creating, storing, retrieving, and modifying information. As students design, share, and adapt knowledge in critical, ethical, purposeful, and innovative ways, they gain perspective on the long-term implications of life in a digital, connected world and develop literacies to responsibly take ownership of such technologies to augment learning and benefit society. Technology Education involves students in the design and fabrication of objects using a variety of materials, methods, technologies, and tools in order to develop their ability to shape and change the physical world to meet human needs. It may include woodwork, metalwork, electronics, drafting, automotive technology, power mechanics, and robotics. Using creative and critical thinking, students can work collaboratively to problem find and solve by exploring materials, using tools and equipment, designing and building, developing processes, and communicating the merits of their work. They can learn to critically evaluate the appropriateness of the products they develop and those developed by others. As they explore the role of culture, including local Aboriginal cultures, in the development of practical and innovative solutions to human needs, they can develop a sense of personal and social responsibility for the products they use and develop, and their effects on individuals, communities, and the environment, now and in the future. Learning in Applied Design, Skills, and Technologies provides firm foundations for lifelong learning and, for some, specialized study and a diverse range of careers. It develops well-rounded citizens who are informed creators and consumers. It fosters the development of future problem solvers, innovators, and skilled tradespeople who can contribute to solving problems not yet anticipated with processes and technologies not yet imagined in order to improve their lives, the lives of others, and the environment. Goals The BC Applied Design, Skills, and Technologies curriculum contributes to students’ development as educated citizens through the achievement of the following goals. Students are expected to acquire practical skills and knowledge that they can use to bring their ideas from conception to fruition develop a sense of efficacy and personal agency about their ability to participate as inventors, innovators, and agents of change to solve practical problems in a rapidly changing world explore how the values and beliefs of cultures, including local Aboriginal cultures, affect the development of products, services, and processes understand the environmental implications of the products they are designing and constructing investigate and actively explore a variety of areas, including aspects of Business Education, Home Economics, Information Technology, and Technology Education, and new and emerging fields, in order to develop practical hands-on skills and make informed decisions about pursuing specialized interests for personal enjoyment or careers develop a lifelong interest in designing, making, and evaluating products, services, and processes, and contributing through informed citizenship, volunteer work, or their careers, to finding and solving practical problems Last updated: June 29, 2016 Applied Design, Skills and Technologies_Goals and Rationale | Building Student Success - BC's New Curriculum Label: grist Date: August 16, 2017 at 05:58PM Labeled: August 16, 2017 at 06:01PM via GitHub http://ift.tt/2v3c1bG August 16, 2017 at 06:06PM via GitHub http://ift.tt/2v3c1bG [100-days-of-writing] Applied Design Skills and Technologies_What's New | Building Student Success - BC's New Curriculum Applied Design Skills and Technologies_What's New | Building Student Success - BC's New Curriculum By janzeteachesit Assigned to Applied Design, Skills, and Technologies_What's New | Building Student Success - BC's New Curriculum http://ift.tt/2w3uMQJ GRIST4 DT DH ADST Applied Design, Skills, and Technologies What's New? As part of the current work of transforming the BC provincial curriculum, the intention is to bring applied learning to all curricula. This is being done in two ways. Firstly, individual areas of learning are being revised to place greater emphasis on curricular competencies, the doing part of the curricula. Secondly, the Applied Skills curricula are being re-envisioned as a K–12 program. The name “Applied Design, Skills, and Technologies” replaces “Applied Skills.” The new name is intended to better capture the scope and nature of the domain. Design involves the ability to combine an empathetic understanding of the context of a problem, creativity in the generation of insights and solutions, and critical thinking to analyze and fit solutions to the context. To move from design to final product or service requires skills and technology. Skills are the abilities gained through competence to do something and to do it increasingly well. Technologies are tools that enable human capabilities, and range from blunt-nosed scissors, to tablets, to drill presses, depending on the grade level, available resources, and facilities. In Applied Design, Skills, and Technologies (ADST), students will grow in their ability to use design thinking to gain an understanding of how to apply their skills to problem finding and solving, using appropriate technologies. Kindergarten to Grade 5 What's the same? Teachers will continue to provide students with opportunities to design and make things in the context of exploratory and purposeful play and learning in various areas of learning. What's new? This is a new provincial curriculum for Kindergarten to Grade 5. The K–5 curriculum consists only of Curricular Competencies and Big Ideas. These will provide a common focus and a common language for the designing and making activities that are currently a normal part of students’ learning experiences in K–5 classrooms. There is one set of Curricular Competencies for Kindergarten to Grade 3, with simplified design stages that are naturalistic and developmentally appropriate. There is another set of Curricular Competencies for Grades 4 and 5 with more detailed design stages, to reflect a developmental progression and encourage more purposeful designing and making. This is a simplified curriculum that has no Content learning standards for Kindergarten to Grade 5. The intent and requirement is that teachers use the learning standards for Curricular Competencies from ADST K–5 with gradelevel content from other areas of learning to provide students with crosscurricular opportunities to develop foundational mindsets and skills in design thinking and making. Grades 6 and 7 What's the same? Middle schools or other schools that currently offer a rotation of modular explorations will be able to accommodate the redesigned ADST curriculum within their current delivery models. What's new? This is a new provincial curriculum for Grades 6 and 7. The curriculum is modular in design to allow for choice and a variety of delivery models, depending on the school configuration and student interest. The curriculum is identical for the two grades. The intent is that students will experience at least three Content modules in each grade. The Curricular Competencies and Big Ideas are identical for all Content modules. Schools may choose from among the modules provided in the provincial curriculum or develop new modules that use the Curricular Competencies of ADST 6–7 with locally developed content. Locally developed modules can be offered in addition to, or instead of, the modules in the provincial curriculum. The curriculum has been developed to accommodate delivery in a variety of settings. Schools that currently have an exploratory rotation may choose to continue with that delivery model for ADST. Schools that do not currently have an exploratory rotation may wish to develop one, or to teach ADST modules in an integrated cross-curricular way with other areas of learning. Grades 8 and 9 What's the same? There are provincial curricula in Business Education, Home Economics, Information Technology, and Technology Education. Schools will continue to encourage exploration, as well as offering students choices. Schools will be able to accommodate the redesigned ADST curriculum within their current delivery models. What's new? The Curricular Competencies and Big Ideas for Grade 8 are the same as for Grade 7. The Curricular Competencies and Big Ideas for Grade 9 are continued for Grade 10. There are separate sets of Content options for Grade 8 and Grade 9. These These may be offered as modular rotations of varying length, as is common for Grade 8 now, or as full-year courses, as is often the case in Grade 9 now. The Curricular Competencies and Big Ideas are the same for all of the Content modules in a grade. Schools are expected to offer students the equivalent of a “full-year” program in ADST. This can be made up of one or more modules. Schools may choose from among the modules provided in the provincial curriculum or develop new modules that use the Curricular Competencies of ADST 8 or 9 with locally developed content. Locally developed modules can be offered in addition to, or instead of, the modules in the provincial curriculum. As the new ADST curriculum has explorations starting in Grade 6, schools may wish to offer students more choice in Grades 8 and 9 than was offered previously. Grades 10 to 12 What’s the same? There is provincial curriculum in the areas of Business Education, Culinary Arts, Home Economics, Information Technology, Media Arts, and Technology Education and related disciplines. Students in Grades 10 to 12 have opportunities to specialize in a specific area or to continue to explore their interests in more than one area. The specialization might be driven by students’ desire for practical skills in a particular area, their interests and passions, or their plans for post-secondary education or careers. School districts are able to continue to offer and develop local courses to augment provincial curricular offerings. Board/Authority Authorized (BAA) courses remain in effect. Skills Exploration courses and Industry Training Authority (ITA) curricula have not been revised and remain in effect. What’s new? The provincial curricula for Grades 10 to 12 have been reconfigured to match the intent and directions of ADST and to build on the explorations in Grades 6 to 9, and redesigned to match the current curricular design. The Curricular Competencies and Big Ideas for Grade 9 have also been used for all Grade 10 ADST curricula, for consistency and continuity. One set of Curricular Competencies and Big Ideas has been developed for Grades 11 and 12 and used for all Grade 11 and 12 ADST curricula. In all ADST curricula there is greater emphasis on student choice about what products to design and make. Content learning standards identify concepts and topics. This creates the space for students to personalize their learning by making choices about what they design and make, and the depth and breadth of their learning on a particular concept, based on their own interests and passions. The generality of the Content learning standards also facilitates inclusion by allowing the teacher or the student to adjust depth and breadth to match abilities. The Content options for Grades 10, 11, and 12 have been significantly redesigned and reorganized to build on the new program in K-7 and the redesigned program in Grades 8 and 9, to maintain a focus on designing and making, and to reflect enrolment numbers, developments in the domain, and policy considerations. Some courses have been combined, some have been eliminated, some have been renamed, and some have been moved to and from other learning areas. In Business Education, courses have been combined and reorganized, Economics 12 has been moved to the Social Studies learning area, and a new E-Commerce 12 course has been developed. Cafeteria 11 and 12 have been renamed Culinary Arts 11 and 12, and a new Culinary Arts 10 course has been developed to allow earlier specialization. In Home Economics, curricular content from Human Services 11 and 12 has been combined with content from Family Studies 11 and 12 to create new courses called Child Development and Caregiving 12 and Housing and Living Environments 12. Information and Communication Technology courses have been significantly updated and two new courses, Computer Science 11 and 12, have been developed as Mathematics courses with input from post-secondary institutions. Media Arts 10-12, with a focus on the application of digital technologies, has been moved to the Applied Design, Skills and Technologies learning area. Technology Education courses have been significantly reorganized. Some courses have been combined, and some courses have been eliminated as a result of policy development considerations (e.g., Technology Education 11A, B, C, and D courses). New courses, such as Coding for Manufacturing 12, Mechatronics 12, and ROVs and Drones 12, have been added to reflect developments in the discipline. The chart below shows current provincial Applied Skills curricula and the proposed new ADST 10-12 curricula. Current Applied Skills 10-12 curricula Applied Design, Skills, and Technologies 10-12 curricula Business Education Business Education 10: General Business Education 10: Communication Business Education 10: Entrepreneurship Entrepreneurship and Marketing 10 Business Education 10: Marketing Business Education 10: Finance and Economics Accounting 11 Accounting 11 Basic Computer Applications 11 Entrepreneurship 11 Marketing 11 Marketing and Promotion 11 Accounting 12 Accounting 12 Business Information Management 12 Data Management 12 Economics 12 Has been moved to Social Studies Financial Accounting 12 Financial Accounting 12 Management Innovation 12 Marketing 12 E-Commerce 12 Culinary Arts Culinary Arts 10 Cafeteria 11 Culinary Arts 11 Cafeteria 12 Culinary Arts 12 Home Economics Home Economics 10: General Home Economics 10: Foods and Nutrition Food Studies 10 Home Economics 10: Textiles Textiles 10 Home Economics 10: Family Studies Families and Society 10 Food Studies 11 Foods Studies 11 Textile Studies 11 Textiles 11 Family Studies 11 Interpersonal and Family Relationships 11 Human Services 11 Food Studies 12 Food Studies 12 Textile Studies 12 Textiles 12 Family Studies 12 Child Development and Caregiving 12 Housing and Living Environments 12 Human Services 12 Information and Communications Technology Information Technology 10 Web Development 10 Computer Studies 10 Information and Communications Technology: Applied Digital Communications 11 Digital Communications 11 Information and Communications Technology: Computer Information Systems 11 Computer Information Systems 11 Information and Communications Technology: Computer Programming 11 Computer Programming 11 Information and Communications Technology: Digital Media Development 11 Digital Media Development 12 Information and Communications Technology: Applied Digital Communications 12 Information and Communications Technology: Computer Information Systems 12 Computer Information Systems 12 Information and Communications Technology: Computer Programming 12 Computer Programming 12 Information and Communications Technology: Digital Media Development 12 Media Arts Visual Arts: Media Arts 10 Media Arts 10 Visual Arts: Media Arts 11 Media Arts 11 Visual Arts: Media Arts 12 Media Arts 12 Technology Education Technology Education 10: General Technology Education 10: Drafting and Design Drafting 10 Technology Education 10: Electronics Electronics and Robotics 10 Technology Education 10: Mechanics Power Mechanics 10 Technology Education 10: Metalwork Metalwork 10 Technology Education 10: Woodwork Woodwork 10 Automotive Technology 11 Automotive Technology 11 Carpentry and Joinery 11 Woodwork 11 Drafting and Design 11 Drafting 11 Electronics 11 Electronics 11 Robotics 11 Metal Fabrication and Machining 11 Metalwork 11 Automotive Technology 12 Automotive Technology 12 Automotive Technology 12: Automotive Electricity and Electronics Automotive Technology 12: Body Repair and Finish Automotive Technology 12: Engine and Drive Train Automotive Engine and Drivetrain 12 Carpentry and Joinery 12 Woodwork 12 Carpentry and Joinery 12: Cabinet Construction Carpentry and Joinery 12: CNC Wood Processes Carpentry and Joinery 12: Residential Construction Carpentry and Joinery 12: Woodcraft Products Furniture and Cabinetry 12 Drafting and Design 12 Drafting 12 Coding for Manufacturing 12 Drafting and Design 12: Advanced Design Drafting and Design 12: Architecture and Habitat Design Drafting and Design 12: Engineering and Mechanical Drafting Drafting and Design 12: Technical Visualization Electronics 12 Electronics 12 Electronics 12: Analog Systems Electronics 12: Digital Systems Electronics 12: Robotics Robotics 12 Mechatronics 12 ROVs and Drones 12 Metalwork 12 Metal Fabrication and Machining 12: Advanced Fabrication Metal Fabrication and Machining 12: Advanced Machining Machining and Welding 12 Metal Fabrication and Machining 12: Advanced Welding Metal Fabrication and Machining 12: Art Metal and Jewellery Art Metal and Jewellery 12 Metal Fabrication and Machining 12: CNC Processes Metal Fabrication and Machining 12: Forging and Foundry Metal Fabrication and Machining 12: Sheet Metal Tourism Tourism 11 Tourism 11 Tourism 12 Tourism 12 Other Automotive Service Technician 1 These curricula have not been revised and are still in place. Carpentry Level 1 Professional Cook 1 Applied Skills 11 Skills Exploration 10 Skills Exploration 11 Skills Exploration 12 Last updated: August 12, 2016 Applied Design, Skills, and Technologies_What's New | Building Student Success - BC's New Curriculum Label: grist Date: August 16, 2017 at 06:07PM Labeled: August 16, 2017 at 06:11PM via GitHub http://ift.tt/2uKbWy5 August 16, 2017 at 06:16PM via GitHub http://ift.tt/2uKbWy5 [100-days-of-writing] Curriculum Overview | Building Student Success - BC's New Curriculum Curriculum Overview | Building Student Success - BC's New Curriculum By janzeteachesit Assigned to Curriculum Overview | Building Student Success - BC's New Curriculum http://ift.tt/2vKdrJR GRIST4 DT DH ADST Curriculum Overview Education for the 21st Century British Columbia has one of the best education systems in the world. Teachers are skilled, facilities are sound, and students are performing near the top of international assessments. Yet it is an education system modelled on the very different circumstances of an earlier century — when change was much more gradual than it is today. Conditions in the world are changing greatly and rapidly. Today’s students will grow into a world that is very different from and more connected than that of generations before. To maintain high achievement, British Columbia must transform its education system to one that better engages students in their own learning and fosters the skills and competencies students will need to succeed. One focus for this transformation is a curriculum that enables and supports increasingly personalized learning, through quality teaching and learning, flexibility and choice, and high standards. To guide the transformation, the province conducted reviews of trends in national and international jurisdictions and invited authorities on curriculum and assessment design to advise on proposed changes. In addition, as part of the work on core competencies, several commissioned researchers summarized the literature in critical thinking, creative thinking, and social and personal responsibility. Student Success Through Curriculum Transformation Today we live in a state of constant change. It is a technology-rich world, where communication is instant and information is immediately accessible. The way we interact with each other personally, socially, and at work has changed forever. Knowledge is growing at exponential rates in many domains, creating new information and possibilities. This is the world our students are entering. British Columbia’s curriculum is being redesigned to respond to this demanding world our students are entering, To develop new models, the Ministry consulted with experts in the field. They suggested that to prepare students for the future, the curriculum must be learner-centred and flexible and maintain a focus on literacy and numeracy, while supporting deeper learning through concept- based and competency-driven approaches. The redesign of curriculum maintains a focus on sound foundations of literacy and numeracy while supporting the development of citizens who are competent thinkers and communicators, and who are personally and socially competent in all areas of their lives. British Columbia’s redesigned curriculum honours the ways in which students think, learn, and grow, and prepares them for a successful lifetime of learning where ongoing change is constant. The Educated Citizen “A quality education system assists in the development of human potential and improves the well-being of each individual person in British Columbia society.” These words, along with the description of the educated citizen, became educational policy following the report of the Royal Commission on Education (known as the Sullivan Commission), in 1988. They continue to have meaning today. Achieving British Columbia’s social and economic goals requires well-educated citizens who are able to think critically and creatively and adapt to change. Progress toward the achievement of these goals also depends on the province having citizens who accept the tolerant and multifaceted nature of Canadian society and who are motivated to participate actively in our democratic institutions. To ensure the development of an educated society, government is responsible for providing all youth with the opportunity to obtain high-quality education. To that end, British Columbia’s schools assist in developing citizens who: Are thoughtful and able to learn and to think critically, and can communicate Information from a broad knowledge base Are creative, flexible, and self-motivated and have a positive self-image Are capable of making independent decisions Are skilled and able to contribute to society generally, including the world of work Are productive, gain satisfaction through achievement, and strive for physical well-being Are co-operative, principled, and respectful of others regardless of differences Are aware of the rights of the individual and are prepared to exercise the responsibilities of the individual within the family, the community, Canada, and the world The redesigned curriculum captures these qualities, both implicitly and explicitly, in the core and curricular competencies. The concept of the educated citizen will continue to guide educational decisions for years to come, ensuring that students across the province are supported and that future generations of British Columbians are empowered by their school experience. Personalized learning Personalized learning acknowledges that not all students learn successfully at the same rate, in the same learning environment, and in the same ways. It involves the provision of high-quality and engaging learning opportunities that meet the diverse needs of all students. Schools may provide flexible timing and pacing through a range of learning environments, with learning supports and services tailored to meet student needs. Personalized learning focuses on enhancing student engagement in learning and giving students choices — more of a say in what and how they learn — leading to lifelong, self-directed learning. Students and teachers develop learning plans to build on student’s interests, goals, and learning needs. Involving students in reflecting on their work and setting new goals based on their reflections allows them to take more control of their learning. Personalized learning also encompasses place-based learning, where learning experiences are adapted to the local environment or an individual context. Key features of redesigned curriculum At the heart of British Columbia’s redesigned curriculum are the Core Competencies, essential learning and literacy and numeracy foundations. All three features contribute to deeper learning. The Core Competencies Core Competencies underpin the curricular competencies in all areas of learning. They are directly related to the educated citizen and as such are what we value for all students in the system. Review the Core Competencies, including profiles and illustrations Essential learning The curriculum for each subject area includes the essential learning for students, which represent society’s aspirations for BC’s educated citizen. The redesigned curriculum develops around key content, concepts, skills and big ideas that foster the higher-order thinking demanded in today’s world. Literacy and numeracy foundations Literacy is the ability to understand, critically analyze, and create a variety of forms of communication, including oral, written, visual, digital, and multimedia, in order to accomplish one’s goals. Numeracy Is the ability to understand and apply mathematical concepts, processes, and skills to solve problems in a variety of contexts. Literacy and numeracy are fundamental to all learning. While they are commonly associated with language learning and mathematics, literacy and numeracy are applied in all areas of learning. Curriculum model All areas of learning are based on a “Know-Do-Understand” model to support a concept-based competency-driven approach to learning. Three elements, the Content (Know), Curricular Competencies (Do), and Big Ideas (Understand) all work together to support deeper learning. British Columbia’s curriculum design enables a personalized, flexible and innovative approach at all levels of the education system. All areas of learning have been redesigned using this model. Content (Know) The Content learning standards — the “Know” of the Know-Do-Understand model of learning — detail the essential topics and knowledge at each grade level. Curricular Competencies (Do) The Curricular Competencies are the skills, strategies, and processes that students develop over time. They reflect the “Do” in the Know-Do-Understand model of learning. While Curricular Competencies are more subject-specific, they are connected to the Core Competencies. Big Ideas (Understand) The Big Ideas consist of generalizations and principles and the key concepts important in an area of learning. They reflect the “Understand” component of the Know-Do-Understand model of learning. The big ideas represent what students will understand at the completion of the curriculum for their grade. They are intended to endure beyond a single grade and contribute to future understanding. Any of the elements may include elaborations. Elaborations are provided where necessary to clarify some words or statements and may include examples, key questions, definitions or be used to describe breadth and depth for content. Elaborations are presented as “mouse-over” links on the website. Concept-based, Competency-driven Curriculum British Columbia’s redesigned curriculum brings together two features that most educators agree are essential for 21st-century learning: a concept-based approach to learning and a focus on the development of competencies, to foster deeper, more transferable learning. These approaches complement each other because of their common focus on active engagement of students. Deeper learning is better achieved through “doing” than through passive listening or reading. Similarly, both concept-based learning and the development of competencies engage students in authentic tasks that connect learning to the real world. Concept-based learning A concept-based curriculum uses concepts to define standards of knowledge and skills associated with a given area of learning. It is focused on the key concepts, principles, and generalizations that are used to organize knowledge and solve problems within and across disciplines. A concept-based curriculum: Is built around higher-order standards and key ideas, allowing a more in-depth exploration of topics to gain deeper understanding Balances the study of factual information with the development of conceptual understanding and disciplinary skills Offers opportunities for the transfer of learning Is not a list of topics to cover in isolation from one another A concept-based curriculum allows for connections between big ideas — for example, through exploration of the concept of reoccurring patterns and comparison of how patterns appear in literature, geographical features, and the evolution of species. Competency-driven learning “Competency” and “competencies” are defined in different ways in different contexts. The terms have their own meanings when used by business and industry, where they generally refer to the skills needed to perform a given job. In the context of education, the terms refer to the ability of students to perform a task as expected within a specific discipline or area of learning. That ability represents a combination of skills, processes, behaviours, and habits of mind. Students are competent in an area of learning to the extent that they understand and can apply knowledge to new contexts. Competencies are often narrowly equated with skills, but in a 21st-century educational context, competencies represent a much broader and more adaptable achievement than a simple set of skills. The redesigned curriculum defines competencies at two levels: Core Competencies develop across the curriculum, and Curricular Competencies are explicit statements of what is expected at each grade level in each area of learning. Redesigned Curriculum In Action When planning, it is important to begin with a broad understanding of the curriculum being used. The rationale and goals provide the context for the area of learning and make clear its contribution to the development of educated citizens The rationale and goals provide a broad instructional and assessment context for the area of learning The introduction to each area of learning provides specifics about features, structure, and important considerations of the curriculum The curriculum for each area of learning is displayed in two ways—in HTML format on the website and in PDF or Word formats. The curriculum website will continue to evolve in ways that support planning for learning. At this point, several features are available such as: A search engine to allow teachers to search for key words or select key elements from specific grades or areas of learning The results of the search can be exported into a Word document for further manipulation PDF or Word versions of the curriculum can be printed Some resources for planning are included now and will be further expanded in the future This flexibility supports teachers to combine the learning standards in various ways. Teachers are encouraged to create courses, modules, thematic units or learning experiences that go beyond learning area borders to focus on students’ needs and interests or local contexts. The curriculum design and the website features provide the flexibility to serve the unique needs of classrooms, students, and teachers. Flexible learning environments Learning can take place anywhere, not just in classrooms. Many schools and teachers create learning environments that explore the use of time and space in creative ways. The integration of areas of learning and technology also have opened the door for teachers and schools to approach the use of time and space in creative ways — ways that adapt to the students’ needs and interests. Although the learning standards are described within areas of learning, there is no requirement for teachers to organize classrooms, schools or instruction in this manner. In effect, the Ministry of Education defines the “what” to teach but not the “how to organize the time, space or methods to teach it. The focus on personalization and the flexible structure of the curriculum support the configuration of combined grade classrooms. Classes of students of more than one grade provide opportunities for teachers to develop a mindset that sees all the students as a group of learners with a range of needs and interests. Multi-grade programs should find a comfortable fit with the curriculum. ICT-enabled learning environments Students need opportunities to develop the competencies required to use current and emerging technologies effectively in all aspects of their learning and life. Technology can facilitate collaboration between students, educators, parents, and classrooms while also providing schools with rich online resources. Today’s technology enables classrooms, communities, and experts around the world to share digitally in a learning experience, wherever they may be. Inquiry and question-based approaches Through demonstration of the core and curricular competencies, students are bound to form questions that provide teachers with insight into their thinking. Questions generated by both students and teachers are critical to encouraging a sense of wonder and curiosity among students. This dialogue can take place through many question-based approaches, including, but not limited to: Inquiry Project-based learning Problem-based learning Self-assessment Research skills Scientific methods Collaboration with community Learning can often be enriched through collaborations involving members of the community. Parents or guardians and others in the community may bring expertise and perspective from their own lives and experiences to enhance students’ learning. Teachers are encouraged to incorporate these experiences into their students’ learning when possible and appropriate. It is particularly helpful to co-operate and engage with experts from the community when learning about culture-specific contexts to avoid offence or misrepresentation or appropriation of culture. Cultural appropriation includes use of cultural motifs, themes, “voices,” images, knowledge, stories, songs, drama, and so on without permission or without appropriate context or in a way that may misrepresent the real experience of the people from whose culture they are drawn. Collaboration with community members exemplifies many of the First Peoples Principles of Learning and nurtures cross-generational and relational learning. When working with members of the community, teachers are encouraged to: Become familiar with school and board/authority policies for involving guest instructors in the classroom (e.g., reference checks) Arrange for a meeting to discuss appropriate learning expectations and to decide which areas of the curriculum are to be addressed Ensure that age-appropriate material is used Prepare students for the experience (e.g., discuss the expectations for process and etiquette, provide relevant background information) Determine the needs of the presenters (e.g., space, technology, materials) Debrief with students and guests Aboriginal Perspectives and Knowledge British Columbia has long had the goal of improving school success for all Aboriginal students. Achieving this goal will require that the voice of Aboriginal people be heard in all aspects of the education system; the presence of Aboriginal languages, cultures, and histories be increased in provincial curricula; and leadership and informed practice be provided. At the same time, Aboriginal perspectives and knowledge are a part of the historical and contemporary foundation of British Columbia and Canada. British Columbia’s education transformation therefore incorporates the Aboriginal voice and perspective by having Aboriginal expertise at all levels, ensuring that Aboriginal content is a part of the learning journey for all students, and ensuring that the best information guides the work. An important goal in integrating Aboriginal perspectives into curricula is to ensure that all learners have opportunities to understand and respect their own cultural heritage as well as that of others. Over the past decade, British Columbia’s curriculum has integrated Aboriginal content into specific courses. The redesigned curriculum builds on what has been learned and extends Aboriginal perspectives into the entire learning journey, rather than into specific courses or grade levels. This means that from Kindergarten to graduation, students will experience Aboriginal perspectives and knowledge as part of what they are learning. And because Aboriginal perspectives and knowledge are embedded in the curriculum, they will naturally influence the ways in which students will be assessed. The First Peoples Principles of Learning provided a crucial lens for teacher teams when drafting curricula, and all curriculum teams included Aboriginal representation. The teams put great effort into embedding Aboriginal knowledge and worldviews in curriculum in authentic and meaningful ways. Curriculum material was reviewed by Ministry staff as well as by Aboriginal teachers and other experts. References to Aboriginal perspectives and knowledge are both explicit and implicit in the redesigned curriculum and are evident in the rationale statements, goals, learning standards, and some of the elaborations. Rich instructional samples to inspire teaching and learning will be collected and shared online to provide examples of relevant teaching units and place-based learning. In all of the areas of learning, teachers are encouraged to teach in ways that respect the place in which the students are — to teach from within the school and its surrounding community. Program Considerations Valuing Diversity British Columbia’s schools include young people of varied backgrounds, interests, and abilities. The Kindergarten to grade 12 school system focuses on meeting the needs of all students. When selecting specific topics, activities, and resources to support the implementation of the curriculum, teachers are encouraged to ensure that these choices support inclusion, equity, and accessibility for all students. In particular, teachers should ensure that classroom instruction, assessment, and resources reflect sensitivity to diversity and incorporate positive role portrayals, relevant issues, and themes such as inclusion, respect, and acceptance. This includes diversity in family compositions and gender orientation. The school system strives to create and maintain conditions that foster success for all students. These conditions include: Equitable access to and equitable participation in quality education for all students School cultures that value diversity and respond to the diverse social and academic needs of individual students School cultures that promote understanding of others and respect for all School environments that are safe and welcoming Policies and practices that promote fair and equitable treatment Processes that give a voice to all members of the school community Honouring diversity within the school system is based on the principle that if our differences are acknowledged and utilized in a positive way, it is of benefit to the quality of our learning and working environments. More information is available at http://ift.tt/2w3eAPl. Supporting Diverse Learners BC educators strive to ensure that all learners are supported to participate in school, to develop their individual potential, and to acquire the knowledge, skills, and attitudes they need for a successful personal future and to contribute positively to society and to the economy. Curriculum used in British Columbia schools remains designed for the majority of students, with classroom teachers continually personalizing their instruction and assessment methods for students as appropriate. Government policy supports the principles of inclusion of all students. Students with special and/or ELL needs can achieve the prescribed learning standards through the strategic use of personalized instruction and assessment methods. Some students with special needs may require program adaptation or modification to facilitate their achievement of the learning standards in this curriculum. Adapted Programs An adapted program addresses the learning standards of the prescribed curriculum by providing accommodations to selected students. These accommodations may include alternative formats for resources, instructional strategies, and assessment procedures. Accommodations may also be made in areas such as skill sequence, pacing, methodology, materials, technology, equipment, services, and setting. Students on adapted programs are assessed using the learning standards and can receive full credit. Digital/audio texts or peer helper to assist with assigned readings Access to assistive tools/technology (e.g., word processor, calculator, text to speech/voice to text software, magnifier, FM system etc.) Alternative ways of demonstrating learning standards Graphic organizers/strategy lists to assist students Extended time to complete assignments or tests Support to develop and practice study skills; for example, in a learning assistance class Preteaching key vocabulary or concepts; multiple exposure to materials Working on select learning standards from different grade levels Modified programs A modified program has learning standards that are substantially different from the prescribed curriculum and specifically selected to meet the student’s special needs. A student on a modified program is assessed in relation to the goals and objectives established in the student’s IEP. The following are examples of strategies that may help students on modified programs: Specify personal support (by peers or educational assistants, for example) Set individualized goals that may consider learning standards but are developed to suit the student’s special needs Modify activities by providing parallel ones for students with special needs Inclusion British Columbia promotes an inclusive education system in which students with special needs are fully participating members of a community of learners. Inclusion describes the principle that all students are entitled to equitable access to learning, achievement, and the pursuit of excellence in all aspects of their educational programs. The practice of inclusion is not necessarily synonymous with full integration in regular classrooms, and goes beyond placement to include meaningful participation and the promotion of interaction with others. Placement A school board must ensure that a principal offers to consult with a parent or guardian of a child who has special needs regarding the student’s placement in an educational program. A school board must provide a student who has special needs with an educational program in a classroom where the student is integrated with other students who do not have special needs, unless the educational needs of the student with special needs or other students indicate that the educational program for the student with special needs should be provided otherwise. The emphasis on educating students with special needs in neighbourhood school classrooms with their age and grade peers, however, does not preclude the appropriate use of learning assistance rooms, self-contained classes, community-based programs, or specialized settings. Students with special needs may be placed in settings other than a neighbourhood school classroom with age and grade peers. This should only be done when the school board has made all reasonable efforts to integrate the student, and it is clear that a combination of education in such classes and supplementary support cannot meet the student’s educational or social needs, or when there is clear evidence that partial or full placement in another setting is the only option after considering the student’s educational needs or the educational needs of others. Integration Integration is one of the major strategies used to achieve inclusion, Students with special needs are included in educational settings with their peers who do not have special needs, and are provided with the necessary accommodations, determined on an individual basis, to enable them to be successful there. The principle of “placement in the most enabling learning environment” applies when decisions are made about the extent to which an individual student is placed in regular classrooms or is assigned to an alternate placement. English Language Learning (ELL)/Apprentissage de la langue anglaise (ALS) People from all parts of the globe contribute to the social, cultural, and linguistic fabric of British Columbia. This diversity is mirrored in our school populations, in both the contributions made and the unique needs that must be addressed. ELL/ALS students come from many linguistic and cultural backgrounds and have had a wide variety of life experiences — attributes that can significantly enrich the life of the school and help enhance learning for all students. English Language Learning (ELL)/Apprentissage de la langue anglaise (ALS) services enable students whose primary language or languages of the home is/are other than English to achieve the expected learning outcomes of the provincial curriculum and to develop their individual potential within British Columbia’s school system. Differentiated Instruction Differentiated Instruction (DI) is a flexible approach to teaching in which a teacher plans and carries out varied approaches to address content, learning processes, learning style, practical procedures, presentation strategies, and assessment tools. It results in a more personal, proactive learning environment, inclusive of a wide variety of learners. When teachers differentiate instruction, they provide students with the structures to maximize strengths, work around weaknesses, and experience timely remediation. This enables students to take advantage of effective learning strategies as they begin to understand their own personal learning styles, interests, and needs and engage with their learning. As a result, student motivation increases. Universal Design for Learning Universal Design for Learning (UDL) is a framework of instructional approaches that recognizes and accommodates varied learning styles. It provides learning activities that expand students’ opportunities for acquiring information and demonstrating learning, as well as for enhancing social participation and inclusion. The driver for universal design is the philosophy of proactively addressing needs. Universal Design for Learning is integrated into regular instructional planning as a mechanism to make diversity the norm. It provides support for all students and motivates through the element of choice. Response to Intervention Response to Intervention (RTI) is a framework for formative assessment that involves collecting data on a regular basis to make instructional decisions in a multi-tier model. RTI is based on the principle of prevention and early intervention. By using ongoing assessment to inform teaching practice and allocate instructional resources, teachers are able to provide appropriate, evidence-based interventions. Central elements of all RTI models include early screening of all students to identify those at risk for academic difficulties, implementing research-based interventions matched to student need and increasing intensity of intervention when needed. RTI also involves continuous monitoring and recording of student progress during interventions to guide decisions for both the student (e.g., further assessment, individualized planning) and the teacher (e.g., using small-group or one-to-one learning contexts, topics for professional development). Although RTI originates from special education, it is intended for use with all students in general education. Personal safety To ensure a safe learning environment, teachers may consider the following questions before, during, and after instruction: Are students aware of established rules and procedures for safety? Do students fully understand the instructions? Is the activity suitable to each student’s interest, confidence, and ability? Has the instruction been sequenced progressively to ensure safety? Are students being properly supervised? Are facilities, equipment, and technologies suitable and in good repair? Some areas of learning make use of specific safety guides and manuals. These should be employed to ensure that students and teachers can enjoy safe learning activities at all times. In addition to physical safety, teachers should consider the emotional safety of students when planning instruction. This includes, but is not limited to: Being sensitive to individual students Being prepared to respond to unique situations Employing creative strategies to deal with rivalry, stress, fear of failure, performance anxiety, and so on As well, teachers should be mindful of activities that may cause emotional or psychological stress for individual students (e.g., blindfolding, working in closed environments, solo performance, body contact, heterogeneous groupings), and be prepared to offer alternative strategies as needed. Alternative Delivery policy The Alternative Delivery policy outlines how students and their parents or guardians, in consultation with their local school authority, may choose means other than instruction by a teacher within the regular classroom setting for addressing the learning standards contained in the health component of the Physical and Health Education curriculum. The Alternative Delivery policy applies only to the health-related learning standards (Note: the policy will be revised in the 2015/16 school year). The policy recognizes the family as the primary educator in the development of children’s attitudes, standards, and values, but it still requires that all learning standards be addressed and assessed in the agreed-upon alternative manner of delivery. It is important to note the significance of the term “alternative delivery” as it relates to the Alternative Delivery policy. The policy does not permit schools to omit any of the learning standards within the Physical and Health Education curriculum. Neither does it allow students to be excused from meeting any learning standards related to health. it is expected that students who arrange for alternative delivery will address the health-related learning standards and will be able to demonstrate their understanding of these learning standards. Curriculum Overview | Building Student Success - BC's New Curriculum Label: grist Date: August 16, 2017 at 06:08PM Labeled: August 16, 2017 at 06:11PM via GitHub http://ift.tt/2v3y2qB August 16, 2017 at 06:16PM via GitHub http://ift.tt/2v3y2qB [100-days-of-writing] A New Kind of Classroom: No Grades No Failing No Hurry - The New York Times A New Kind of Classroom: No Grades No Failing No Hurry - The New York Times By janzeteachesit Assigned to http://ift.tt/2w3FM0n GRIST4 STEM A New Kind of Classroom: No Grades, No Failing, No Hurry - The New York Times Label: grist Date: August 16, 2017 at 09:21PM Labeled: August 16, 2017 at 09:26PM via GitHub http://ift.tt/2fM9UqG August 16, 2017 at 09:26PM via GitHub http://ift.tt/2fM9UqG [100-days-of-writing] Vim isnt that scary. Here are 5 free resources you can use to learn it. Vim isnt that scary. Here are 5 free resources you can use to learn it. By janzeteachesit Assigned to Vim isn’t that scary. Here are 5 free resources you can use to learn it. http://ift.tt/2uK5YNU GRIST4 CSP VIM Vim isn’t that scary. Here are 5 free resources you can use to learn it. Fatos MorinaAug 16 Passionate Team Lead, Computer Science Graduate, Open Source Enthusiast at http://ift.tt/2rJjttT, Blogger at http://ift.tt/2wjEM8d This is a view from this open source project that displays cryptocurrencies values like Bitcoin, Ethereum and Nasdaq There unknown can be frightening. The unknown is usually followed by a type of resistance. Vim is not an exception. Despite the fact that a StackOverflow question asking about ways of exiting from it has been seen more than one million times, Vim is still one of the most used editors by developers around the world. Many people who do not use Vim are accustomed to other editors and think that they do not need to switch to it. They do not want to leave their comfort zone. They think that Vim takes too much time and effort to learn and that it does not make that much of a difference after all. By taking the time to read this article, you have shown that you already have some type of interest about Vim. Before we see some resources that make it easier for you to learn Vim, let’s see the reasons why should we should even consider using this 1980s text editor. Why should you learn Vim in the first place? “To use Vim is one of the best choices I’ve made in my programming career.” — Lucas Oman It is reasonable that you may need some reasons to know why learning Vim is worth the effort. After all, it may affect your entire workflow. It may even seem unreasonable to start learning something that does not look suitable for you. Vim is used by almost everybody at thoughtbot which is one of the most recommended companies in Bay Area. Knowing this might make it compelling for you to start learning it. Aside from that, there are other reasons worth mentioning. Let’s begin. It is like playing a game When you want to start playing a game, you do not step back from playing it just because it is hard. You actually get motivated to play it because it gives you pleasure. Developing with Vim is similar. When you start to see that it is fast and intuitive, you may start to enjoy the experience. You can even get more hooked on it once you learn some of the more advanced commands that increase your productivity. No need for a mouse You have many shortcuts to navigate through the code and files, which can actually help you get rid of the need to use your mouse at all. As a result, you do not need to get your fingers off the keyboard, which speeds up your coding. In other words, you can code in Vim as fast you can type. It is fast. Even the word Vim means energy and enthusiasm. Many powerful commands The list of commands that you can use is pretty long. You do not have to learn each one, you simply need to learn a few in the beginning and then try to learn new ones as you go. You may learn something new and important that is in Vim even many years after your first lesson. Highly customizable There are configurations that you can use and change based on your own preference. There are hundreds of colors schemes that you can download. Moreover, you can use a large number of plugins that enhance your editor and make it as powerful as modern IDEs. It is text-centered Modern IDEs have a lot of built in features. They usually come with a lot of buttons and a rich user interface to make it easier for you to use all the functionalities that are in it. Vim on the other hand is generally text centered. This makes it easier for you to focus only on the code and get rid of other distractive icons and options that are not code related. It is present in every Linux machine The vast majority of servers use Linux as their operating system. When you are familiar with the basics of Vim, you may become comfortable with the deployments and server maintenance. These are not the only reasons why Vim needs your attention. But they represent some of the most important ones. If they resonate with you, then you may give learning Vim a chance. 5 free online resources to learn Vim Here are a few resources that you can use to help you in your learning journey. Do not pretend to learn everything related to Vim at once. There are people who have been using Vim for 20 years and they are still learning new things related to it. VimTutor If you are using a Unix-based machine, you can go to your shell and type vimtutor. If you are on Windows, you can see some of the answers to open it here. You will have an excellent tutorial that will help you learn the basics of Vim in a few minutes. When you are done, you will already see why Vim is amazing. OpenVim This is an interactive tutorial that you can use to get a solid understanding of the basics in Vim. You can also use it to test your existing Vim skills. Vim Adventures If you like learning while playing games, then this resource may be valuable for you. In this game, you can learn to use Vim commands for navigation, which are essential for you to navigate the maze. You can always type :help for any hint. The basics of Vim Derek Wyatt has prepared an album with 13 videos where he teaches Vim. These videos have been seen several thousand times and are very valuable resources for you to learn the basics of Vim. If you are still doubting whether you should learn Vim, then these videos can give you more reasons to learn. Vim Cheat Sheet Print this cheat sheet and leave it next to your desk. From time to time, take a few seconds to look through the list and try to use something from it. This way you can memorize new commands on the go and also reinforce the ones that you already one. Conclusion If you’re new to Vim, then it may be better to not start to use it immediately in your work projects, because you may get frustrated and never get back to it. You should initially use it in your side projects, and only start using it in your full time job once you are pretty comfortable. Try using Vim for a few days in a side project that you have and see how it goes. If you enjoy using it, then you can stick to it. I am a Passionate Software Engineer, currently serving as a Team Lead Developer for a group of enthusiastic developers that specialize in developing web and mobile applications, mostly using Ruby on Rails and React JS. I am currently looking for a remote job. Please contact me for new opportunities. Show your support Clapping shows how much you appreciated Fatos Morina’s story. freeCodeCamp Our community publishes stories worth reading on development, design, and data science. Vim isn’t that scary. Here are 5 free resources you can use to learn it. Label: grist Date: August 17, 2017 at 08:31AM Labeled: August 17, 2017 at 08:40AM via GitHub http://ift.tt/2wTccbv August 17, 2017 at 08:56AM via GitHub http://ift.tt/2wTccbv [100-days-of-writing] Interactive Vim tutorial Interactive Vim tutorial By janzeteachesit Assigned to http://ift.tt/nHAJaF GRIST4 CSP Interactive Vim tutorial Label: grist Date: August 17, 2017 at 08:36AM Labeled: August 17, 2017 at 08:40AM via GitHub http://ift.tt/2vGBxqH August 17, 2017 at 08:56AM via GitHub http://ift.tt/2vGBxqH [100-days-of-writing] Stop Forming Habits and Start Keeping Habits: the Shift in Mindset that Makes all the Difference Stop Forming Habits and Start Keeping Habits: the Shift in Mindset that Makes all the Difference By janzeteachesit Assigned to Stop Forming Habits and Start Keeping Habits: the Shift in Mindset that Makes all the Difference http://ift.tt/2fQSn0F GRIST4 Writing Stop Forming Habits and Start Keeping Habits: the Shift in Mindset that Makes all the Difference Michael J. MottaAug 16 Professor. Author of LONG TERM PERSON, SHORT TERM WORLD. Doesn’t believe in mailing lists. mjmottajr.com I put a checkmark next to all of my intentioned actions today. Hopefully I will do the same tomorrow, but I might not. And that’s OK. I’ll still keep my habits. Life’s a rollercoaster and I’m not focused on waiting in line and taking my seat. I’m focused on knowing that the ups will become downs and the downs will become ups. I have wined and dined with kings and queens, and I’ve slept in alleys and dined on pork and beans. — Dusty Rhodes Here’s an example. I’ve journaled for 5 years… except that I haven’t. Visit productivityjournals.com for context. Here’s what I mean. In 5 years, I’ve actually only journaled in: 35 of 60 months. That’s less than 60% of months. 91 of 240 weeks. That’s only 38% of weeks. 750 of 1,825 days. Only 41% of possible days. For a “daily” habit that I write a lot about, that’s hypocritical. My habit is demonstrably inconsistent. But I learned years ago that I’m not good at forming habits. For the first few days, sure, I’d do the thing. Then life came along and the habit withered, only to return a few months down the road. Only to meet the same fate again. This is why I don’t place my emphasis on forming habits. I don’t try to do something for 66 days in a row or whatever science says I should do. Instead, I focus on keeping habits. Consistency is Overrated When you miss doing Habit X for a day, week, month, or even a year, a voice in your head declares: “It’s all ruined now. Might as well accept defeat!” That’s why one missed day turns into two days, one week into three, one month into a year. It’s why so many habits are start-stop, start-stop for our entire lives. It’s why so many of my habits fell by the wayside only to be “reformed” later. Consistency is both necessary and sufficient for forming a habit; however, it is neither necessary nor sufficient for keeping a habit. In other words: Don’t let convince yourself that you’ve lost the war when you’ve lost one measly battle. Grit is Underrated More important than consistency is the willingness to return to a practice after an absence. Grit. How many have almost reached the goal of their ambition, but, losing faith in themselves, have relaxed their energies, and the golden prize has been lost forever. — P.T. Barnum If you accept that you’ll drop the ball and neglect habits, and if you expect that your inner self will seize the opportunity to deflate your ambitions, you’ll be prepared to soldier on. Slowly, over time, you’ll build confidence in your ability to pick the habit back up. You will no longer beat yourself up. You will no longer have to worry about reforming the habit because you’ll have the habit. Strategy To keep the habit, you must anticipate threats. While threats are unpredictable, they are predictably unpredictable. We don’t know when these threats will come but we know that they will come. Here are some threats I’ve encountered over the years and how I’ve dealt with them (or how I wish I dealt with them.) TRAGEDY STRIKES It’s hard to focus on keeping a habit when you aren’t sure if you can make it through the day. Eventually, we’ll want a distraction from our emotions. We can choose whether the distraction is Netflix or our journal, or a run, or a book, or anything else related to our goals and habits. DEATH BY A MILLION PAPER CUTS The most existential threat to habit-keeping isn’t the worst the world throws at us — it’s the small, barely perceptible wounds we give ourselves everyday. Every time we make a short term decision (such as getting lost in a Facebook rabbit hole), we give ourselves a little cut. We justify the decision and promise never to do it again. But each time we make such a decision, we increase the chances that we’ll make the same decision again. And again. And again. The only strategy for preventing death by a million paper cuts is to prevent the cut if we can, and if we can’t, to make the cuts small and shallow. Lower your expectations in order to fulfill your intentions. Give yourself permission to compromise with yourself. Do the thing but change up the routine. Try a different workflow. Do something else first then come back to it. Or, if you must, go into “Survival Mode” where you write one line of code, do one push-up, write one line in the journal, or watch a leaf fall slowly from a tree instead of meditating. Seemingly “small” actions, if they keep a habit, are worth their weight in gold. There are two mistakes one can make along the road to truth — not going all the way, and not starting. — Gautama Buddha HYPER-FOCUS Sometimes we face the opposite problem: We become obsessed with one goal and hyper-focus upon it, ultimately to the detriment of other goals. We feel like we’re being productive, and technically we are, but we’re leaving a path of destruction behind us. After you finish this important project or accomplish this critical goal, you will live to fight another day for another cause — hopefully many days and many causes. You will be in this same situation again and again, finding yourself hyper-focusing on one thing while neglecting others. How you perform now is probably how you will perform then. When I feel myself becoming hyper-focused, I make myself work five or ten minutes on one of my neglected projects. This has several benefits. I make progress, and I keep the habit. This also provides insight into why I’m hyper-focusing. Is it because I’m procrastinating in some other area of my life? Or am I genuinely passionate? Once I know this, I can make an informed decision regarding how to proceed. You can also use this extra motivation for accomplishing Goal A to help you accomplish goals B and C. Force yourself to complete other tasks before allowing yourself to work on the preferred task. By rewarding yourself, you’re in effect taking the excess motivation and distributing it elsewhere. ACCEPT, AND EXPLICITLY DEFINE, LIMITATIONS It is suboptimal to do all things optimally. When all the elements of a system are at capacity, the system itself is over capacity. You must find elements of your system where you are willing to accept limitations. Example: I have zero ambition of running a marathon or being in anything close to “elite” shape. I will probably never try to extend my meditation sessions beyond 20 or 30 minutes. I cannot commit to writing several pages in my journal with much regularity. Such “limitations” in one place also make it possible to have “unlimitations” elsewhere. VACATION Personally, if I take a week off from all of my habits, I have a very hard time getting back into the swing of things. Maybe you are more disciplined and can do that. If you cannot, my recommendation is this: At a bare minimum, keep performing at least one action related to your long term goals. This need not take much time at all and will make it infinitely easier to get the system back up-and-running when you return. Take a vacation, but not from everything. Go for a run, or just do a push-up. Write in your journal, even if it’s only one line. Keeping something going is almost as good as keeping everything going. RE-ENTRY PLANS Vacations will not be the only time your habits will come to a halt. Inevitably, you will neglect them. A day here or there, a week, maybe a month or more. You can, of course, summon enough grit to pick the entire habit back up. But there’s a way to make it easier: re-entry plans. Re-entry plans are a failsafe. They prevent neglect from becoming abandonment. You can make plans for specific actions (e.g., “What To Do If I Stop Working Out”) or you can have a plan that applies to all actions. It doesn’t matter. The important thing is to have a plan that requires nominal grit. If you lose your exercise habit, the plan might be to go for a walk. If you stop writing 1,000 pages a day, the plan might be for 50 words. I use one action: I write a single line in my journal. I do this when I drop the ball on journaling or any other habit — or all of them. Each time, I’ve kept writing, wanting to tell the story of why I’d been away from the particular habit(s). Like catching up with an old friend, doing sogives me enough of a spark to do something else, then something else. And, soon enough, I’m back on track. WRONG HABIT Maybe you’ve dropped the habit because something more fundamental is amiss. Have a series of questions ready to ask yourself. Maybe your goals have changed or maybe there’s a better way to go about achieving them. Maybe your sleeping habits have changed, affecting when you feel at your peak. Maybe the winter makes running difficult. Maybe your shin splints suggest you should run less and practice yoga more. Whatever the reason, find it, then adjust as necessary. (I believe journaling makes such shifts perceptible earlier than they otherwise would be.) A Final Quote and a Final Note I love this quote: How we spend our days is how we spend our lives. — Annie Hillard But I ultimately disagree with it. How we spend most of our days is how we spend our lives. You can learn more about keeping habits in my book, on my blog, and by following me here on Medium. If you enjoyed this story, please recommend and share to help others find it! Feel free to leave a comment below. The Mission publishes stories, videos, and podcasts that make smart people smarter. You can subscribe to get them here. Show your support Clapping shows how much you appreciated Michael J. Motta’s story. Michael J. Motta Medium member since Apr 2017 Professor. Author of LONG TERM PERSON, SHORT TERM WORLD. Doesn’t believe in mailing lists. mjmottajr.com Stop Forming Habits and Start Keeping Habits: the Shift in Mindset that Makes all the Difference Label: grist Date: August 17, 2017 at 04:05PM Labeled: August 17, 2017 at 04:10PM via GitHub http://ift.tt/2fP9sYD August 17, 2017 at 04:11PM via GitHub http://ift.tt/2fP9sYD [100-days-of-writing] A Primer to Colors in Digital Design uxdesign.cc A Primer to Colors in Digital Design uxdesign.cc By janzeteachesit Assigned to A Primer to Colors in Digital Design – uxdesign.cc http://ift.tt/2wogWIw GRIST4 GR A Primer to Colors in Digital Design Archit JhaJul 16 Digital Designer | Front-end Enthusiast | UI/UX Aficionado | HCI Lover Source: As a beginner in the world of design, I often struggled with picking the right colors to provide visual depth to my artworks. Consequently, my initial works seemed out of balance as the colors lacked contrast and harmony, robbing my illustrations of the much needed visual acuity. Since painting wasn’t my forte, I hadn’t experimented enough with mixing physical colors using brushes in the past and felt overwhelmed just by looking at the color picker in tools such as Illustrator and Photoshop. Although it took time to educate myself on color theory and principles of harmony in design, the lessons I imbibed along the way certainly helped boost my confidence in picking colors. COLOR THEORY Our brain helps us perceive colors when light reflected off an object is received by the eyes. Objects do not inherently bear color, albeit it is the interplay of absorption and reflection of a choice of continually distributed wavelengths from the visible spectrum by the object that determines its appearance. Therefore, two of the most basic colors, ‘Black’ and ‘White’ respectively denote absence and presence of light and aren’t actually colors. Sunlight, considered as the natural source of light is characteristically ‘White’ but with a pinch of salt. Each white light source has a degree of ‘warmth’ attached to it which is determined by a property called ‘Color Temperature’. This property varies for different light sources as we find the warmth of a halogen bulb, an artificial source of light, inclining towards the yellow side of the spectrum, making the spectral distribution different than daylight. In simple words, appearance of an object depends on the properties of incident light(s) and is never really a single color. COLOR MODELS AND SYSTEMS Color Models are a popular way to represent a range of colors. The underlying principle for almost all color models is the concept of primary colors. Primary colors represent a small set of colors that can be combined to generate all possible colors in the range. These colors maintain an individual identity of their own and cannot be used to generate each other. Colors on Screen Colors on screens and displays are intangible and are generated artificially by combining lights of different colors. They are therefore represented by what is known as ‘Additive Color Models’. RGB RGB is an additive color model used to represent colors on scanners and displays. With ‘Red’, ‘Green’ and ‘Blue’ as the primary colors, RGB color model can be used to produce 16 million (16777216 to be precise) colors as each of R,G and B use 8 bits to take a value between 0 to 255 to construct colors in the range. Red, Green and Blue combine to form ‘White’ [R:255, G:255, B:255], while the absence of all of them produces Black [R:0, G:0, B:0]. On LED screens, each pixel fundamentally comprises a subpixel grid of Red, Green and Blue LEDs which light up at a given intensity to produce the required color in that space on the screen. Additive models are device dependent as the rendering of color varies for monitors. Therefore, a color in RGB space, say [R:32, G:64, B:128], may appear different on different screens. RGB spaces can be customized by using new primaries for Red, Green and Blue and selecting a gamma value. Therefore, other open-ended RGB spaces exist such as the Photo RGB, DCI-P3Pro, Rec 209. Rec 2020, scRGB and ACES(Academy Color Encoding System) some of which are used and were developed primarily for motion pictures by film academies. sRGB(developed by HP and Microsoft together) and Adobe RGB are the two defaults on computers and the internet. 2. HSV and HSL RGB, although very helpful in making computers understand color doesn’t agree much with human perception of colors. It makes more sense to think in terms of ‘lightness’, ‘darkness’ and ‘intensity’ of the color rather than contemplating numeric values of R,G and B to get to the right color. Therefore, HSL (Hue, Saturation, Lightness) and HSV(Hue, Saturation, Value) exist as transformations of RGB model to make a designer’s life easier. 3. Indexed ColorThis system, simply put, assigns a number or ‘index’ to each color in the palette. Images with limited colors in the range save memory and can be refreshed quickly on displays. thereby consuming less power. An index system helps the cause by only requiring the computer to store the indexed number instead of the entire color table. 4. BitmapAnother memory friendly image representation system that uses 1 bit per pixel. Images are stored as a 2-dimensional grid (map) of pixels. 5. GrayscaleCommonly referred to as ‘Black and White’, this image system has no color and just stores the value of intensity of light (White: High Intensity, Black: Low Intensity) 6. YUV Bandwidth comes at a premium and back in the days of Black and White televisions, the analog age, signal transmission capabilities were limited and the system required a way to compress data to be transmitted. Human visual system(HVS) is more sensitive to intensity of light than colors and it receives low frequencies(in Visible EM spectrum) better over the high frequencies. Tapping into workings of human visual system allowed the engineers to create the YUV color space that worked as a color encoding system for broadcasting purposes. While Y captured luma (or luminance i.e perceptive brightness), U and V are chromacities that captured color as factor of difference from Y component. Unlike RGB, where all three values use 8 bits, YUV space allots more space to Y, which stores intensity information, than U and V as HVS is more sensitive to intensity over color, thereby compressing the overall data stream. Among analog television systems PAL(Europe except France and Southeast Asia) used YUV, NTSC(Americas, Japan, South Korea and Suriname) adopted YIQ, a variation of YUV and SECAM utilized YDbDr. In the YUV family of spaces, YCbCr is another variation popular for digital image compression and forms the basis of the JPEG and MPEG algorithms. All three color spaces are fundamentally similar and work as storage and transmission channel intermediates that cannot be rendered directly on screen. Colors in Print Colors you can touch are ‘tangible’ and exist due to natural(or natural + artificial) lighting in the environment. Since these are a result of light reflected off of an object, they are represented by what are called ‘Subtractive Color Models’. A plain paper is perceived as ‘white’ as it reflects all the cored wavelengths of light that fall on it. With the help of ink ,the white paper can be made to absorb some of the colored wavelengths such that a color appears on paper. This is how inks fundamentally operate, however there are two mechanisms to achieve this: I Spot Colors based PrintWhen each color in the print job is achieved with a separate ink, the print is Spot colored based since spots from individual colored inks or pigments are used to obtain the final print. Spot colored prints produce the best output as the colors are exact but prove expensive with increasing number of colors in the final job. Some standard proprietary spot color systems are ANPA, Colour Index International, DIC, FOCOLTONE, HKS, Munsell, NCS, Pantone, RAL, TOYO and Truematch. Pantone Matching System(PMS) PMS is a proprietary color space owned by Pantone Inc.(now under X-Rite) and is the leading standard for spot colors in the printing industry. Each of the 1,114 spot colors in the PMS system could be identified by it’s unique PMS number. PMS is preferred across the industry to maintain consistent branding across the globe. Only a small subset PMS colors can be reproduced using the CMYK model which is used for process printing. II Process Colors based PrintProcess printing works on the concept of primary colors where a handful of spot colors are used to create new colors. Reprographic techniques such as ‘Halftone’ in process color printing create an optical illusion of a new color by strategically spacing differently sized dots of spot colors in a way that they appear as a new color or a smooth transition between colors. Although, not as vivid as spot color print, process printing saves costs. CMYK (C)Cyan, (M)Magenta, (Y)Yellow and (K)Key-Black is a subtractive color model that can be used to achieve a range of colors. Combining C,M,Y and K at 100% each produces pure black while absence of all is white which is opposite to the RGB model as CMYK is implemented using inks and pigments rather than light. When inks combine in full concentration they absorb all the light, producing black. Reproduction of image using CMYK bases process printing produces different results as this model is also device dependent. Optical Illusion when using Process Colors Device Independent Color Device dependent color management system often have suppressed gamuts(range of colors). Age, make, subpixel arrangement, display panel type (OLED, LCD, Plasma) affect the rendering of color in monitors. Similarly among printers, paper type, nozzle make and dye account for variations in color reproduction. International Consortium on Illumination (CIE) began work on color spaces that would provide a nexus between physical wavelengths in visible spectrum and human perception of colors as early as 1931. This was before the age of transistors and the system developed was device independent. It started with CIE XYZ and subsequently CIE LUV and CIE LAB were derived. LAB Derived from the CIE XYZ color space, CIE LAB is the mathematical representation of all perceivable colors in a 3-dimensional space. While ‘L’ defines lightness on one axis, ‘A’ and ‘B’ are color channels. The LAB space creates a much wider gamut than RGB and encompasses 50% more colors. In fact, a lot of values on LAB space are not even colors since they fall outside the spectrum of perceivable colors by the human visual system. The displays aren’t capable of rendering all the values in LAB either and therefore it finds it’s rare but very important use in medical imaging and computer vision applications where pushing RGB spaces just produces white instead of a possible color value. You can’t depend on your eyes when your imagination is out of focus. -Mark Twain COLOR WHEEL The quote from Twain provides us a segue into the artistic(and more designer friendly) phase of this article after the overdose of color lingo from the vocabulary of computer graphics. A color wheel is a concept in art(not technology) that arranges colors in a circular fashion in order to establish relations between the primary secondary and tertiary colors. In practice(painting), primary colors can be used to produce other colors mixing them: Primary [ Red, Blue, Yellow ] Primary + Primary = Secondary [ Violet(Red+Blue), Green(Blue+Yellow), Orange(Yellow+Red)] Primary + Secondary = Tertiary [ Green-Yellow, Yellow–Orange, Orange-Red, Red–Violet, Violet-Blue and Blue–Green ] Visual Parameters of Color Hue: The property to significantly distinguishes a breed of colors from other in the spectrum Value: The lightness or darkness of a color. The term value is often used interchangeably with ‘Brightness’, ‘Lightness’ and ‘Luminosity’. However, in physics, the terms bear a subtly different meaning. Saturation: The intensity of a color. It determines the purity of a color and is often denoted by terms ‘colorfulness’ or ‘chroma’. Shade: A darker variant of a color obtained by adding black. Tint: A lighter variant of a color obtained by adding white. Tone: Both tinting or toning a color or adding grays produces tones of a color SIDE NOTE: ‘Pastel’ is a special family of hues that have relatively low saturation but high values. These ‘muted’ colors appear soft and evoke soothing, calming sensations. Harmonies in Color Colors create both a visceral and a visual sensation and a portion of both helps us establish relations between them. On the color wheel, primaries Red, Blue and Yellow are equidistant are located at 120 degrees from each other. Going clockwise on the color wheel from Red-Violet to Yellow, gives a sensation of warmth and these 6 adjacent colors are referred to as ‘Warm Hues’. On the other half, the remaining colors from Violet to Yellow-Green are referred to as ‘Cool Hues’. Colors add depth to design and generate emotions. It is important to balance them in a way that they produce sufficient contrast to draw the viewer in and add a pep to the creativity that lies underneath. Although sky is the limit to creativity, some basic rules govern the laws of harmony. The rules aren’t perfect and art lies in bending them the right way. Color schemes(read ‘Palettes’) that inform the design could be developed based on the foundation of these classical rules: Analogous: Colors contiguous colors on the wheel are analogous to each other. Complementary: Colors at a radial separation of 180 degrees are complementary to each other. Monochromatic: A single hue on the color wheel with varying levels of saturation forms a monochromatic relationship with it’s variants. Split-Complimentary: A base color with colors on either side its complement are said to be in a split-complimentary relationship. Triadic: Colors at a redial separation of 120 degrees from each other form a triad. Choosing Colors Color palette for an artwork is developed by starting with a base color and gradually picking other colors that form a visual harmony with the base color. Playing around with value(Lightness/Darkness) of a color helps fine tune the contrast and creates a sense of balance. Classical rules are good start but one should never be afraid to bend the rules. At times, a color choice out of nowhere could generate a better emotion over the classic alternative. Color Picker Navigation It is important to note that colors around a color will impact how it feels to the user. Some values may make your base color feel too dark or too light while some hues may make it look to warm or cold (observe the text labels on axis in the picture above closely). Robert Plutchik’s Wheel of Emotion Colors elicit emotions and bear a meaning which varies with cultures, beliefs, geographies and other demographics. For example, RED in China indicates luck while in South Africa it is the color of mourning. Russia associates Red with communism while the countries in the west attribute it to fervor and intensity. It is fascinating how colors can be used to create moods. Forming relations is a very human way of processing things and colors are just the right tool build them. Good Practices in Design The world of digital design, especially branding is a challenging space for designers as the scale of your artwork’s reproduction is sometimes unfathomable. A company’s logo, for example, dwells on a breath of materials in both physical and virtual forms. To get an an idea, consider these: Displays(LCD, Plasma, CRT, LED, OLED) Papers(Coated, Uncoated, Cardstock) Clothing(Flags, T-shirts, Caps) Equipment/Devices(Metals, Ceramics, Glass) Merchandise(Leather, Wood, Plastic, Cardboard) As a designer, you job is to create a uniform experience across all of the above such that the aesthetics of the company is diffused into the environment wherever there is a possible interaction. It is a complex job, but some good practices make the ride smoother. Even if your artwork isn’t a logo, following these rules would help you in the longer run. Always work in CMYK space — The conversion from CMYK to RGB produces better results then the other way round. The Adobe suite of applications use the Adobe RGB color space which is a compressed gamut. Blacks tend to lose their intensity when transformed from RGB to CMYK and miss that pop when you observe them closely. Start with Grayscales — Play around with just the value in the beginning without introducing colors. If your grayscale variant has enough contrast to make a visual appeal, adding hues to the values will usually form a good harmony. Pick Pantones for Branding Projects —The advantage of spot colors is they appear identical regardless of where they are printed in the world. Having standard spot colors, Pantones especially, would make sure the visual identity of your branding artwork is retained. Know the Mood and the Purpose — Ask yourself what is the purpose of your illustration? What do you want your users to feel when they see your work? What do you want to convey with your artwork? Answering these questions will help you make a decision in picking a base color and balancing the warm and cool hues in your artwork. Remember that colors carry meaning and have the power to evoke emotions. Choose wisely. Target good contrast — Experiment with hues to create contrast of hue, saturation and value. Highly intense colors stab the eye instead of pleasing it. If there’s text on your illustration, make it readable by using high contrast colors (Black text on White is the best contrast). Follow WCAG guidelines if you will. Warm and Cool hues on each other aren’t good for type and some colors are just intrinsically difficult for humans to differentiate (Green on Red or vice versa, blue on green). Work with a Palette — Adding shadows and highlights to your work adds visual detail and makes it look both professional and creative. Work with ‘Tonal Families’ which is your color palette replete with shades and tints of your choice of colors. There are some great online tools out there to help you create and maintain your color palette — Adobe Color, CheckMyColors, Colrd, ColorExplorer, ColorHunter, ColourLovers, ColorMatters, ColourMod, Coolers, Designspiration, Paletton, Pitaculous. Seek Inspiration — A nice trick to create good color palettes is to pick(read ‘borrow’)colors from an artwork you really like. Both digital graphics and paintings by masters from the renaissance can turn out to be great sources of colors that work well together. Respect the environment — If you have an image that goes with your design, try to pick colors from that to create a sense of balance across the space. Magazines are some really good examples. Notice how the text and other visual artefacts of design that reside nearby blends with each other creating a harmony that leads you into it. Bend the rules — This point cannot be stressed enough. Don’t be shy to experiment. Practice! Practice! Practice! —The more you do, the more you learn. Follow popular artistes on dribbble and behance. Try to deconstruct their style and implement it and one day you’ll have one of your own Show your support Clapping shows how much you appreciated Archit Jha’s story. Archit Jha Digital Designer | Front-end Enthusiast | UI/UX Aficionado | HCI Lover A Primer to Colors in Digital Design – uxdesign.cc Label: grist Date: August 18, 2017 at 08:28AM Labeled: August 18, 2017 at 08:40AM via GitHub http://ift.tt/2vPHPCG August 18, 2017 at 08:45AM via GitHub http://ift.tt/2vPHPCG [100-days-of-writing] 12 extensions that will make any UX Designer 12 extensions that will make any UX Designer By janzeteachesit Assigned to 12 extensions that will make any UX Designer’s life easier http://ift.tt/2wcbusK GRIST4 GR 12 extensions that will make any UX Designer’s life easier KaylaMatthewsAug 16 If a person has only 15 minutes to spend on content, around 75% prefer to read a page with good design over reading something without much pizzazz. Designers seem to intrinsically understand this fact and will spend hours getting coloring and spacing just right. Fortunately, there are a number of tools that will make any UX designer’s life easier and speed up the process a bit. Here’s an even dozen for you to check out. 1. Window Resizer Today’s UX designers understand that different people access the internet on different screen sizes, including smaller devices like smartphones. The Window Resizer Chrome browser extension allows you to quickly adjust your screen size to see how a screen will look on different devices. This is vital for developing the best user experience possible. 2. MultiClipboard Designing means doing a lot of coding work. When coding, designers tend to copy and paste from one place to the next. You might grab some code from a design you completed last year with a specific element or you might look up code and grab it. You might also be in the process of debugging and need to get some feedback on some copied-and-pasted code. The MultiClipboard plugin makes it easy to have several clipboards going at one time so you can easily grab a bit of code from here and paste it into a different notepad file. 3. AutoSave You’ve just spent an hour coding a particularly challenging piece of PHP when your laptop battery runs down and your computer shuts off. And you thought you had it plugged in! If you’ve remembered to hit Ctrl/S over and over again, you’ll be fine. However, if you forgot, you will have to start over. Unless, that is, you’ve already downloaded the Notepad plugin called AutoSave. AutoSave automatically saves your work every so many seconds so you don’t have to worry about losing vital coding and having to start over from scratch. In a pinch, this plugin can really save you both frustration and time. 4. HTML2WordPress Do you have a static HTML website that you’d like to convert to WordPress? In the past, this has been a real headache. tags and other issues crop up with conversion and can take hours upon hours to debug. On top of that, HTML coding doesn’t always translate well into PHP and you’re left with strange-looking conversions that might not be very user-friendly. That’s where the HTML2WordPress plugin comes into play. HTML2WordPress takes your static coding and converts it into WordPress language, making the process of converting your website much easier. 5. Brackets Extensions You may already be using Brackets software to more easily code, but did you know there are numerous extensions for Brackets that can save you even more time on coding tasks? For example, you can use the Autoprefixer, which will add vendor prefixes via support data from your browser and help you figure out on-the-fly if a specific prefix is needed and can be used. In addition, the extension will take out any vendor prefixes that aren’t needed and clean up your code. 6. Monster Widget When you’re in the middle of designing a new WordPress site, you may want to test out a number of different plugins to see what gives you the look and function you need. However, this can be extremely time-consuming, as you will have to add and remove widgets over and over. With Monster Widget, you can see at-a-glance the impact different widgets will have on a theme’s look. 7. What Font Did you see a font on another website that you loved and really want to replicate in one of your designs? There are so many fonts these days that it can be difficult to know 100% which font another site is using. However, if you download the What Font Chrome extension, you can simply click on the text on the page and find out what font is being used. This allows you to incorporate the look of text you really love into a fresh, new design all your own. 8. PSD to WordPress Do you have a design you created in Photoshop that you want to easily move over to WordPress? Fortunately, Photoshop has an extension that allows you to easily convert so that everything is coded perfectly for WP. PSD to WordPress speeds up the process and allows you to design once and then convert easily without additional hours spent coding and recoding files. 9. Spectrum When designing a website, you want the colors to look just so. However, one thing that’s easy to forget is that there are people out there with visual challenges who might not be able to see your site the way you think they will. This can include visual impairment or color blindness. Spectrum allows you to see the website you’re creating through their eyes. You simply use the extension and you can see how different colors look and whether or not there’s enough contrast for someone who has a color vision deficiency. 10. CSS3 Generator Some coding tasks are straightforward and easy, but some are more complex. Finding shortcuts can save you a ton of time. The CSS3 Generator is a Chrome app that allows you to create different snippets of CSS code, such as grabbing Hex/RGBA coding or creating CSS columns. 11. Check My Links Checking links within your design might sound simplistic, but it can greatly impact user experience if links are broken. It’s time-consuming to click on each link, make sure the page loaded, etc. Check My Links works with Chrome. You simply start Check My Links and the plugin will crawl through the links on your website and report any broken links. This is also a smart thing to utilize from time to time as you update your site or a bit of time passes to make sure everything is still functional for the user. 12. Eye Dropper Sometimes you see a color on another website that you fall in love with. While you don’t want to copy another design, inspiration from a particular color is common. You could screen-capture the page, plug the screenshot into a photo editor and use the eye dropper tool to try to figure out what the exact formulation of the color is, but that’s time-consuming and not always accurate. Another option is to download the Eye Dropper Chrome extension. With this extension, you just click on the color on the actual site and you will find out the exact color. You can then use it in your design or avoid it like the plague if you hate it. These extensions will make your life as a designer a bit easier and speed up the time it takes you to code. There are many other extensions out there, but these 12 will give you a good start. 12 extensions that will make any UX Designer Label: grist Date: August 18, 2017 at 08:29AM Labeled: August 18, 2017 at 08:40AM via GitHub http://ift.tt/2w9835L August 18, 2017 at 08:45AM via GitHub http://ift.tt/2w9835L [100-days-of-writing] Thoughts on Skeuomorphic Menu Systems Charlie Deets Medium Thoughts on Skeuomorphic Menu Systems Charlie Deets Medium By janzeteachesit Assigned to Thoughts on Skeuomorphic Menu Systems – Charlie Deets – Medium http://ift.tt/2uVlYrq GRIST4 GR Thoughts on Skeuomorphic Menu Systems The tradeoffs and benefits of pseudo-realistic menu design Charlie DeetsAug 13 Product Designer at WhatsApp / charliedeets.com Recently I’ve been playing Splatoon 2, which is a team-based third-person shooter available on the Nintendo Switch. To move between different styles of gameplay, the player must physically move their character in 3D space around a place called Inkopolis Square. This isn’t necessarily a new mechanic in games, but Splatoon’s implementation of it is particularly bold. Moving through 3D space to make selections The square acts as the main menu to the game, giving players the ability to start solo play, online play, local play, purchase items from vendors, and more. Most of the areas have non-obvious names like Octo Canyon, The Shoal, Grizzco, and Galleria. The game encourages players to move around the square and figure out what these various places do. My Squid Kid in the middle of Inkopolis Square, the main menu of Splatoon 2 At the same time, there is a persistent overlay in the bottom right corner which lets the player know they can access a menu with the X button. When the player taps the menu button they get a more traditional menu system which allows them to quick travel to any of the available locations. It also shows them where these locations exist on a map and if they are currently available. Splatoon 2’s traditional menu system One of the benefits of moving around the 3D space of Inkopolis Square is that you run into other players. Walking by certain players will reveal drawings they made which give you a sense of what people are thinking about or inside community jokes. Players can also check out each others gear and order the items other players are wearing. All this creates a sense of culture and community in Splatoon 2. Viewing another player’s drawing The main disadvantage to this system is speed. It takes a lot longer to move around this space than it does to make a selection from a list menu. A player can become distracted from their objective moving around the square. They can get lost trying to find the place they are going. This is why Nintendo included the X button menu. When I first discovered the menu, I was relieved that there was an faster way to start games. After thinking about it, I found myself disappointed because it undermines the core value proposition of the skeuomorphic menu by giving players a way to avoid it. Destiny, an online-multiplayer first-person shooter by Bungie, uses ‘social spaces’ in a similar way to Splatoon. Players must physically walk to vendors, mission guides and postmasters. They must board their spaceship before they can fly to a mission. Unlike Splatoon, Destiny does not offer an alternative 2D menu for these actions. Physical motion of your character in 3D space is required to engage with play modes and vendors. The Tower, a social space in Destiny, featuring vendors such as a postmaster, cryptarch, vaults, and more. One of the reasons this paradigm might be so impactful, even if it is inefficient, is that it supports a game world’s sense of immersion and helps suspend disbelief. In a traditional UI this is rarely important, but in a game UI it is advantageous to keep players immersed in the game world. Inventory management paradigms In Destiny, players must be in physical proximity to a vendor in order to purchase gear. When acquiring loot during gameplay, players physically pick up gear from dropped engrams. The reliance on physical space for these transactions adds a realism to the idea that the player acquired something. When the player manages their inventory, they must move their character to the ‘vault’, which allows them to store their weapons. Approaching this ATM-like console ends up giving the player the feeling their weapons are physically stored somewhere when they are not using them. The action helps keep the player immersed in the experience much better than moving items from one menu to another less prominent menu. A player using a vault in Destiny PlayerUnknown’s Battlegrounds also uses physicality in an interesting way with their inventory menu. When the player encounters loot in the game, they can pick it up one of two ways. In the 3D world they can tap the F key, their avatar will bend over and pick up the item. The player can also press the tab key to open a menu that allows them to see what loot is physically near them presented in a list view. PlayerUnknown’s Battlegrounds inventory menu, the list on the left are items in your reachable vicinity When the player is in that menu, they must drag-and-drop the items from the left side of the screen to their avatar on the right side of the screen. The developers could have solved this by allowing players to click on the items they want, but the physicality of dragging the loot to the character gives the player a sense of ‘acquiring’ in a more realistic way. When a player drops loot for their teammates, they drag the loot to the left side of the screen and let it go, ‘dropping’ it on the ground for them. Historical references The Splatoon 2 menu system reminds me of some old school 90s UI design paradigms. Between 1994 and 1996, Apple had an online service called eWorld. It catered to those who were coming online for the first time. Apple decided to describe features such as email and bulletin board systems as physical locations that mirrored their real life equivalents. Apple’s eWorld menu http://ift.tt/1F7fI16 There was an Arts & Leisure Pavilion, Marketplace, Newsstand, Community Center and more. For those who didn’t understand BBSes, email, and content browsers this design offered assistance in the helping the user understand their choices. The user had to ‘travel’ to each feature, which helped educate the user that in order to use other features they would have to ‘return’ to the main menu. AOL, another online service provider used a less skeuomorphic UI during this time for its main navigation. My guess is people found navigation and repetitive actions easier with a UI that valued visual clarity of choices over education. AOL main menu in 2003 via http://ift.tt/2vEQGXN Super Mario Bros. 3 was an early example where physical space and menu systems converged. The game navigation in SMB3 looks like a physical map the player moves their character over. It also acts as a non-linear menu system because the player can select anything that has been unlocked by moving their character to the option. World 2 map in Super Mario Bros. 3 featuring card games, levels, mushroom houses, castles and warp zones If you take this same paradigm and move it to a contemporary game like Breath of the Wild you can see how this interaction still applies to the game modes. With contemporary games, the behavior tends to feel more fluid and less obvious because of how avatars flow between various states. Not all contemporary games employ this technique, for example Ultra Street Fighter II: The Final Challengers is a great example of a list based menu system. No frills, just options presented as text. Ultra Street Fighter II: The Final Challengers is a contemporary game that features a list based menu system Wrap-up Most user interfaces generally need to be fast and obvious because people perform repeated navigation actions in them. Experiencing the Splatoon 2 menu system was shocking to me at first because it felt so inefficient, but there are real advantages to increasing friction by using skeuomorphic design patterns in three-dimensional space. These menus can help create a sense of immersion, develop social interactions, explain complex concepts quickly by referencing real-life counterparts, and even create a sense of mystery and intrigue by obscuring how simple the system might actually be. Come hang out and play some Splatoon, my friend code is SW-5160–0900–5248 I’d love to know your thoughts on menu systems, games that use skeuomorphic design to enhance the experience and games that work great with a traditional UI. You can find me on Twitter @charliedeets. I also have a podcast called Games UX. You can listen to episodes on the website or follow along on Twitter @games_ux. My Switch friend code is: SW-5160–0900–5248. Show your support Clapping shows how much you appreciated Charlie Deets’s story. Charlie Deets Medium member since Apr 2017 Product Designer at WhatsApp / charliedeets.com Thoughts on Skeuomorphic Menu Systems – Charlie Deets – Medium Label: grist Date: August 18, 2017 at 08:58AM Labeled: August 18, 2017 at 09:00AM via GitHub http://ift.tt/2v84l7Y August 18, 2017 at 09:08AM via GitHub http://ift.tt/2v84l7Y [100-days-of-code] Speech API - Speech Recognition | Google Cloud Platform Speech API - Speech Recognition | Google Cloud Platform By janzeteachesit Assigned to http://ift.tt/2fRuo14 aimlnn Speech API - Speech Recognition | Google Cloud Platform Label: AI-NN-ML Date: August 18, 2017 at 09:39AM Labeled: August 18, 2017 at 09:40AM via GitHub http://ift.tt/2wodQEm August 18, 2017 at 09:40AM via GitHub http://ift.tt/2wodQEm [100-days-of-writing] Make: - YouTube Make: - YouTube By janzeteachesit Assigned to https://www.youtube.com/channel/UChtY6O8Ahw2cz05PS2GhUbg GRIST4 STEM Make: - YouTube Label: grist Date: August 19, 2017 at 02:34PM Labeled: August 19, 2017 at 02:40PM via GitHub http://ift.tt/2wbXNKc August 19, 2017 at 02:45PM via GitHub http://ift.tt/2wbXNKc [100-days-of-writing] (13) Kids Make: - YouTube (13) Kids Make: - YouTube By janzeteachesit Assigned to https://www.youtube.com/channel/UCDdMryhO2umklbFW8GZA3-w GRIST4 STEM (13) Kids Make: - YouTube Label: grist Date: August 19, 2017 at 02:35PM Labeled: August 19, 2017 at 02:40PM via GitHub http://ift.tt/2vSOEmR August 19, 2017 at 02:45PM via GitHub http://ift.tt/2vSOEmR Github Weekly Summary
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[100-days-of-writing] Think Watch Do: 3 Simple But Powerful Self-Awareness Exercises Think Watch Do: 3 Simple But Powerful Self-Awareness Exercises By janzeteachesit Assigned to Think, Watch, Do: 3 Simple, But Powerful Self-Awareness Exercises http://ift.tt/2tm98T5 GRIST4 Writing Think, Watch, Do: 3 Simple, But Powerful Self-Awareness Exercises Niklas GoekeJul 21 Writer, book summarizer & habit coach on coach.me. | Made http://time2read.co | Blog: http://niklasgoeke.com | 365+ book summaries on http://ift.tt/1kMo1so It never ceases to amaze me how much you can learn from movies, books and music, even if it’s completely fictional. Take Harry Potter, for example. No matter how many times I watch it, read it, or think about it, I always find something new that’s interesting. Here’s what I learned from it this week: In every trio there is a thinker, a watcher and a doer. Take our three aspiring magicians, for example. Source Who’s who is obvious: Ron’s the doer. He charges right ahead and he doesn’t know what he’s doing most of the time. Harry’s the watcher. He observes everything and tries to process it. If you’ve ever wondered why he spends so much time of the saga on the sidelines, either incapable of acting or reluctant in deciding, that’s why. Hermione’s the thinker. She doesn’t just observe things, but deliberately takes time to think about them before she gets more information. That’s what makes her so brilliant. When you try to identify these types for the people in your life, you’ll see the thinkers are the ones who seem to have it the easiest while the doers are frustrated a lot. That’s because this categorization corresponds to different levels of self-awareness: the thinkers know themselves best. This is not to say one is better than the other. In fact, we have to carry all of these types within us. It’s just that the thinkers tend to know best when to take on which role. At the same time, it’s the capacity most of us have developed the least. Whatever mode you spend the majority if your time in, there are certain things you can practice to get to the next level. Today, I’d like to show you three self-awareness exercises to achieve just that. Self-Awareness Exercise #1 — For Doers: Apologize Since he does first and thinks later, Ron is often wrong. That’s why he’s making a fair share of apologies. Apologies to Harry, apologies to Hermione, apologies to his family. Source As a doer, that’s one of the best things he can do. You can’t apologize without acknowledging you’ve made a mistake. This acknowledgement is where self-awareness comes from. Exercise: The next time you feel embarrassed because you know you just made a mistake, don’t brush off that feeling. Take it as a chance to quickly turn this obstacle around by apologizing. I used to hate apologies. Especially as a teenager. Over the years I’ve come to see that not only is the transparency and vulnerability of it liberating, but it actually helps you see the kinks in your armor — and how could you iron out what you can’t see? Apologize fast, apologize often. We hate admitting mistakes more than making them, but when you do, you won’t turn into a hypocrite and can reflect on how you can do better next time. Self-Awareness Exercise #2 — For Watchers: Journal When you observe so much, it’s hard to keep track of everything without writing it down. And write a lot Harry does. He writes letters to everyone, he writes in detention and he even had a diary that one time… Source This is a good idea for watchers in general. There’s a saying by Confucius: “You cannot open a book without learning something.” — Confucius Well, you also can’t write a sentence without learning something. The simplest form of journaling I know is the 1-sentence journal. Exercise: Take a thought-provoking question and answer it in one sentence, but answer differently each day. There are endless possibilities to design this exercise and you can change the question from each week or month to the next. Why did you get up this morning? What made you go “huh?” yesterday? Were you content before you fell asleep? You can also gear your questions towards when in the day you’re answering them. For example, here are some ideas for good questions to ask yourself in the morning: Do you feel ready to tackle the day? Why? Why not? What was the first thing you thought of after waking up? What’s one thing you’re grateful for? What’s the most important thing you want to achieve today? Did you sleep enough? What are you most excited about today? Then again, you might want to journal before bed. In that case, you could answer an evening question. Here are some examples: Why did you get out of bed this morning? What’s the best thing that happened today? When did you feel happy or content today? Which hour of the day was your favorite? What did you learn today? Did you do your best today? How could you make tomorrow an even better day than today? What thing are you most excited about for tomorrow? Even in this tiny format, journaling helps your brain structure the things you observe and get better at filtering what matters. That way you can take action in a more targeted way and have to apologize less. If you want to grow this habit over time and slowly spend some more time each day, there are a lot of pre-structured journals out there too. Here are a few some of my coaching clients and I have used: The 5 Minute Journal The SELF Journal The Productivity Planner The Freedom Journal The Bullet Journal You could also journal online, using an app like Day One or Penzu, but there’s something visceral to writing by hand, which I prefer. If you’re a watcher, you’re great at watching life. Might as well remember what’s important. Journaling helps you do just that. Self-Awareness Exercise #3 — For Thinkers: Read When you generally have a good sense of what’s going on, which events are most important and where action’s required, it’s up to you to now extend this knowledge at the right ends. That’s why Hermione’s favorite place is the library. Source Thinkers transform their good contributions to great contributions through selective and well-timed reading. Reading the right thing at the right time allows your neurons to find the best connections between the pictures in your mind. Exercise: Read at least one page a day. Wittgenstein prompted us to read many books to expand our language. You can only know if you’re an ambivalent person when you know what that means. But you don’t have to overdose either. Thinkers usually have a fairly ingrained reading habit as is, but here are some resources that have helped make mine better: Time 2 Read. A free, 14-day email course I made to get your reading habit off the ground when you’ve fallen off the wagon. The Complete Guide To Remembering What You Read. A post I wrote to help you retain more. A Kindle. Easy access to books on the go. It removes the friction of having to carry books around. Books first, rent second. Ryan Holiday never worries about money spent on books. I try to do the same. Four Minute Books. A stash of 400+ short non-fiction book summaries with three lessons each. The Daily Stoic. A great philosophy book by Ryan Holiday, which is literally set up to read one page day. Blinkist. An app that provides you with 15-minute summaries of non-fiction books. The extension of knowledge we get from reading always comes with a side of self-awareness: are you the kind of person who can put it to good use? A page a day goes a long way. Being able to tell what you need to learn next and where you can find it is one of the highest forms of self-awareness. Think, Watch, Do — The Path To Knowing Oneself Only the best of us carry multiple characters around in our chest that we can draw on at will. We all begin one way or another. Start looking around. You’ll find this 3-type pattern in all famous trios. Them… Source …them… Source …even those guys: Source Doers must learn to watch. Watchers must learn to think. Thinkers must learn to think better. The way you do that is by practicing. 1. If you’re a doer, apologize when you screw up. 2. If you’re a watcher, journal about the things you notice. 3. If you’re a thinker, master your reading habit. The question is: Which one are you and what do you need to find out about yourself to get to the next level? If you enjoyed this… …you’ll love Nik’s Newsletter, with the best of my weekly writings, ideas, and book summaries. I’ll even give you my top 3 out of 400+ so far. Get it here. Worth reading? Then it might be worth recommending. Hit the heart so someone else on Medium will do, watch or think. 💚 This was first published at niklasgoeke.com. Better Humans Real stories of success in productivity, health and leadership. Think, Watch, Do: 3 Simple, But Powerful Self-Awareness Exercises Label: grist Date: August 13, 2017 at 04:40PM Labeled: August 13, 2017 at 04:48PM via GitHub http://ift.tt/2vvSmo3 August 13, 2017 at 04:52PM via GitHub http://ift.tt/2vvSmo3 [100-days-of-writing] Run or Walk (Part 2): Collecting Device Motion Data the Right Way Run or Walk (Part 2): Collecting Device Motion Data the Right Way By janzeteachesit Assigned to Run or Walk (Part 2): Collecting Device Motion Data the Right Way http://ift.tt/2wHF7iE GRIST4 STEM Fitness Data Run or Walk (Part 2): Collecting Device Motion Data the Right Way Viktor MalyiAug 13 Read previous part: “Run or Walk (Part 1): Detecting Motion Data Activity with Machine Learning and Core ML” Being motivated to develop a machine learning model that accurately predicts whether the user walks or runs, I needed data. A quick search for the publicly available datasets which contain such activities gave no results. And the only option left was to collect data on my own. Everyone who took part in any data science competitions knows that dataset always needs to be processed to some extent before it can be fed into machine learning model. You can’t pass by this phase, otherwise, your model will suffer from missing, skewed data, outliers and a several other issues. Sometimes after finishing a competition and looking back to the time invested in it, you realize that nearly a half amount of your efforts were spent on processing a dataset! The reason? Datasets are based on the real-life data which is not ideal in a sense of continuity, homogeneity or statistical distribution. DIY data Things are better when you are solely responsible for collecting the data. It’s the most expensive way of getting data from the one side, but from the other side, you have a good chance to save yourself future efforts by collecting data in the way you need. Thinking carefully about the basics of the problem you’re trying to solve helps to find a proper approach to collecting data. I started from the essentials. If I wanted to know whether the person runs or walks I first needed to find a place on human’s body where each of these activities could be clearly distinguished in terms of sensor data. Simply put the iPhone in the pocket and collecting the data from there is not a good solution because each time the device can be differently positioned there. This could result in too variable results from the sensors even for the same activity. Given a limited amount of time I had to collect data, I preferred to sacrifice data variability for the simplicity. A perfect candidate for collecting people activity data is a hand wrist. And here’s why: Walking: hand wrist directed to the ground, moves with low to medium velocity Running: hand wrist directed mostly perpendicular to the ground, moves with medium to high velocity Considering most people have two hand wrists, the data for my 2-class classification model should be collected in following variations: Walking, right wrist; Walking, left wrist; Running, right wrist Running, left wrist; A valid question here would be “Wait, why mounting an iPhone on your wrist when Apple Watch is a more appropriate choice?!” Totally agree, but by that time I didn’t own one and assumed iPhone with its accelerometer and gyroscope will deliver equivalent sensor data. iPhone was always positioned with Home button pointing to the fingers What to collect? What first seems an easy to answer question, can lead you in the wrong direction. Having accelerometer, gyroscope, magnetometer, pedometer and even barometer in your iPhone doesn’t mean that collecting sensor data from all of them makes sense. The good starting point here is an official documentation which reveals the capabilities and limitations of each sensor. After carefully reading it I realized that the most valuable data comes from 2 sensors: accelerometer and gyroscope. Remember, I wanted to use as fewer data as possible? Limiting the number of sensors is the first step in this direction. Why those two? The accelerometer provides changes in device’s velocity along 3 axes which is a crucial piece of information about how one moves his hand. And a gyroscope delivers the rate at which a device rotates around a spatial axis which carries probably fewer insights for distinguishing running and walking activities, but, might still be helpful. Sensor axes for accelerometer (left) and gyroscope (right) Raw or processed data? Apple made a very good job providing different formats of motion data for different occasions. If one needs the accelerometer data limited to acceleration which was applied to the device only by the user, processed data is a valid option in this case. It doesn’t include different forms of bias like the acceleration caused by the gravity. From the other side, raw accelerometer data leaves it up to you how you process it, if at all. This kind of data is the perfect candidate to be used in my future machine learning model. Being unprocessed means that the data is free from any form of bias caused by implementation details of processing algorithms in iOS. This makes the data potentially reusable on other platforms and makes the risk getting hardly identifiable issues when training the model lower. Sensor update frequency Depending on hardware, Apple states impressive “at least 100 Hz” of a maximum sensor update frequency for accelerometer and gyroscope. It’s obvious: the more detailed information about device movement you need, the higher should be this value. But there is always some threshold when you get detailed enough data and getting even more detailed measurements don’t make sense. How to find an optimal sensor update frequency? Collect equivalent activity data at a maximum possible frequency, then at 70% of this value, and then 40%, and, finally, 10%. Plot the signal you received from each of those values and find a plot which keeps the important details of a signal and has the lowest sensor update frequency at the same time. Data collected at 50Hz The same data downsampled to 30Hz. Important signal details are lost. After experimenting with several values I identified 50Hz as an optimal sensor update frequency for the type of activities I was going to record. Collection interval Initially, I tried to collect data in an “uncontrolled” environment. I thought I will just stroll through the city on foot and endlessly record data for a walking activity. The same with running — I would just use my regular jogging sessions for data recording. Reality showed, however, that continuous recording of activities in the real environment like cities, where your movement is constantly interrupted by intersections, traffic lights, and other people, is a very bad idea. Data obtained during 30-minutes long walking session is full of noise from interruptions. I made an attempt to apply a few technics for removing outlying data samples, but none of them gave me a confidence that I preserve original data characteristics. The solution was to drastically shorten data collection intervals. When I evaluated recorded sessions which lasted only 10 seconds, I found out that only 3–4% of them contained outliers. Compared to 45% of data samples contained noise after continuous recording sessions, this is a clear improvement and a way to go. An app for a data collection I needed an app to collect data and temporarily store it before it’ll be uploaded to the environment where the samples will be processed. Staying pragmatic about the possible app features I refrained from developing fancy things and focused on the single goal — reliably collect data with fixed intervals and store it inside the app. The main questions regarding how often I want to collect data samples (50Hz) and for how long (10-second intervals) were answered. I had to implement an app which collects data samples and supplies them with meta information like date- and timestamp, username and a hand wrist on which a recording took place. Recorded sessions were stored in data recording app’s container in .csv format and then extracted and copied to my computer from it. Additionally, I implemented a haptic feedback within a regular time intervals in order to inform myself that recording still takes place and I don’t waste my time running somewhere without actually collecting a data. There were 2 recording modes: manual and continuous. I used the second one 95% of the time and it didn’t require me to start new recording session after every 10 seconds but was doing this automatically for me. Simplest possible UI Depending on whether “Walking” or “Running” was tapped, collected data has been accordingly labeled in the resulting .csv files. The final dataset After collecting walking and running data for about 5 hours in total, I could get an almost equal amount of data for each class including left/right wrist variations. This resulted in 88588 data samples with following structure: To prove that dataset I collected is robust and doesn’t suffer from typical dataset problems, I uploaded it to Kaggle and let others review and analyze it. I made my own analysis as well to make sure I will not face hard-to-analyze issues when training machine learning model on this dataset. The fact the dataset was featured by Kaggle team gave me confidence that the time spent recording this data worth it. And the biggest outcome, of course, is the fact that I could lose some weight during a couple of weeks when I was collecting the data. Follow me and stay tuned to know what machine learning techniques I applied to this dataset to predict user activity with >99% accuracy. Image/Video credits: http://ift.tt/2vvWDrB http://ift.tt/2wHktzf Videezy.com Run or Walk (Part 2): Collecting Device Motion Data the Right Way Label: grist Date: August 13, 2017 at 09:03PM Labeled: August 13, 2017 at 09:08PM via GitHub http://ift.tt/2hWMqQd August 13, 2017 at 09:12PM via GitHub http://ift.tt/2hWMqQd [100-days-of-writing] Conventional wisdom (course content) dawn pankonien Medium Conventional wisdom (course content) dawn pankonien Medium By janzeteachesit Assigned to Conventional wisdom (course content) – dawn pankonien – Medium http://ift.tt/2vTS1wB GRIST4 Writing Conventional wisdom (course content) dawn pankonienAug 11 Conventional wisdom, here, means knowledge that is popular (familiar or, even, taken for granted) but incorrect. Funny and harmless: If you swallow your gum, it stays in your stomach for seven years. More insidiously: Poor people are lazy, and that’s why they’re poor; most welfare recipients are black women with many children who can afford Cadillacs with their welfare funds. What at first appears positive but turns out to be socially detrimental (exclusionary and more) and its own form of racism: Asians are smart (this is called a model minority construct; also: the model minority myth). Previously: If women bathe while menstruating, they risk bleeding to death; everybody needs a tonsillectomy; different racial groups have different IQs… Here’s how economist John Kenneth Galbraith explained conventional wisdom: “As just noted, economic and social behaviour are complex and mentally tiring. Therefore we adhere, as though to a raft, to those ideas which represent our understanding. This is a prime manifestation of vested interest. For a vested interest in understanding is more preciously guarded than any other treasure. It is why men react, not infrequently with something akin to religious passion, to the defence of what they have so laboriously learned. Familiarity may breed contempt in some areas of human behaviour, but in the field of social ideas it is the touchstone of acceptability. Because familiarity is such an important test of acceptability, the acceptable ideas have great stability. They are highly predictable. It will be convenient to have a name for the ideas which are esteemed at any time for their acceptability, and it should be a term that emphasized this predictability. I shall refer to those ideas henceforth as the conventional wisdom” (from The Affluent Society 1958). Conventional wisdom (course content) – dawn pankonien – Medium Label: grist Date: August 13, 2017 at 09:22PM Labeled: August 13, 2017 at 09:23PM via GitHub http://ift.tt/2uByoJE August 13, 2017 at 09:27PM via GitHub http://ift.tt/2uByoJE [100-days-of-writing] The History of Programming Technicat on Software Medium The History of Programming Technicat on Software Medium By janzeteachesit Assigned to The History of Programming – Technicat on Software – Medium http://ift.tt/2vAvFxB GRIST4 CSP Women The History of Programming Philip ChuAug 12 On my list of things-I-want-to-do-but-I’m-not-serious-just-talking is a history of computers, or at least a history of computer programming, something like Bertrand Russell’s History of Western Philosophy or Will and Ariel Durant’s Story of Civilization. I got this interest during my one and only stint in academic teaching as an assistant to Computer Literacy 101 at Johns Hopkins University. The textbook included a decent history of computers, which was wasted on all the psych majors who only took the course because it was a requirement and raised their hands just to ask “Is this going to be on the test?” But I felt a really comprehensive history of computers would be fascinating and something both CS and non-CS majors should learn. Because it’s history, and it’s an interesting history that’s intertwined with everything from WWII codebreaking to the space race to just about everything you’re doing right now. And also it does help you learn how computers and computer programs actually work. I still haven’t seen any book or set of books like I’m envisioning, but I have been to a couple of computer history museums, most recently the one in Mountain View next to Google (there were some rather obvious Googlers sporting Google Glasses walking around), and I’ve read some biographies that collectively give you a sampling of computer history, like those of Countess Ada Lovelace, John Atanasoff, Alan Turing, John von Neumann… Wait a minute: Countess Ada Lovelace? Sounds like the heroine in a romance novel or a Lifetime movie. But real life is even better. She was the daughter of a rapscallion Lord Byron who left the family after she was born. Ada grew up a whiz at math and unfortunately was sick most of her life and died young, but in the meantime figured out how to program Charles Babbage’s (never-finished) Analytical Engine. She would have been a shoo-in for a 3o-under-30 list back then, or more like a 1-under-30 list if you narrowed the list to tech. In other words, Ada Lovelace was the first programmer, even without a functioning computer, and in general, hold on to your Google Glasses, women were the first programmers on real computers. I realized that after reading the Alan Turing biography and learning about the women at Bletchley Park who operated the machines he designed and decrypted German codes during World War II. They were even called “computers”. So, women representation in software development hasn’t just been dropping since the 1980's, it’s been dropping since the 1800's, where it started at 100%. After WWII, men started crowding into the field and getting those plum jobs at IBM, but there were still influential women like the colorful and later Admiral Grace Hopper, who developed the earliest compiled languages like COBOL and popularized bugs (just she and Countess Ada are enough for a new Bill and Ted movie where they go back in time and collect famous computing women to present at a Google diversity seminar). But even if you turn up your nose at COBOL (although that was a nice skill to have during the Y2K scare), every modern programming language, and concepts like GUIs, and design patterns like MVC, can be traced back to Adele Golderberg’s Smalltalk (if you’ve ever wondered why Objective-C is the way it is, look no further…). Less popularly known, one of my MIT profressors, Barbara Liskov, won the Turing Award and developed influential languages like CLU and Argus (CLU was used in the software engineering course she taught where I learned about data abstraction, commenting code, and not working with partners on your final project if you can possibly help it). In the meantime, Ada did get her own computer language. And she’s shown up here and there in pop culture among those in the know, for example in, appropriately, the William Gibson/Bruce Sterling steampunk novel The Difference Engine. So maybe a history of computing is too ambitious, but there’s still plenty of material for a History of Women in Computing. Someone, get on that! The History of Programming – Technicat on Software – Medium Label: grist Date: August 13, 2017 at 09:27PM Labeled: August 13, 2017 at 09:28PM via GitHub http://ift.tt/2w4LNcS August 13, 2017 at 09:32PM via GitHub http://ift.tt/2w4LNcS [100-days-of-writing] Claude Shannons Creative Thinking Speech: A Genius Reveals How To Be Creative Claude Shannons Creative Thinking Speech: A Genius Reveals How To Be Creative By janzeteachesit Assigned to Claude Shannon’s “Creative Thinking” Speech: A Genius Reveals How To Be Creative http://ift.tt/2feUtHb GRIST4 Writing Claude Shannon’s “Creative Thinking” Speech: A Genius Reveals How To Be Creative A speech from one of the 20th century’s most brilliant minds about how to be creative. Henry KimAug 3 As a part of writing the biography of Claude Shannon, we waded through papers — tons of them. At the Library of Congress alone, there were 21 boxes worth of Claude Shannon papers. We went through each carton, page by page. And that was just the beginning. Outside of what was in that collection, there were other published and unpublished volumes of Shannon’s work, totaling in the thousands of pages; never-before-seen interviews given to us by his family and others; letters and memos from countless collaborators and friends. We pored over several decades’ worth of the Otsego County Times, Shannon’s hometown paper, and a similar set of records produced by the Bell Laboratories. In our hunting, we found some gems. There was this 1953 letter from Alan Turing to Claude Shannon: (Courtesy of the Library of Congress, LC-MSS84831) Almost one year later to the day, Alan Turing would be dead. His death was ruled a suicide, though its circumstances remain in dispute to this day. Other letters were more light-hearted. We chuckled at the correspondence Shannon had with Dr. Carl Sagan (about, of all things, a poem about Rubik’s cubes that Shannon had written): (Courtesy of the Library of Congress, LC-MSS84831) Dr. Sagan’s response: (Courtesy of the Library of Congress, LC-MSS84831) There were items that didn’t necessarily speak to Shannon’s scientific collaborations but gave us a window into his personality. We found, for example, a purchase order Shannon made while at Bell Labs. It wasn’t the most consequential historical artifact, but after reading so many of Shannon’s serious academic papers, the detailed account of these purchases brought the tinkering Shannon to life: (Courtesy of the Library of Congress, LC-MSS84831) And so on. All of this wading through paper sounds like a lot of work, and it was — but it is also a thrill, the absolute best part of biographical research. Yes, you have to sift through a lot of historical hay, but every now and again, you find a needle in the palm of your hand. One example: the day we found the wedding announcement for Claude Shannon’s parents. It was front page news in 1909 Gaylord, MI (Shannon’s hometown), and the details — how Claude’s father caught a train in the middle of the night to the home of his future in-laws; what Claude’s mother’s wedding dress looked like the day of — added texture to our narrative. (Credit: Otsega County Library Newspaper Archive) Finding that nugget of news felt like hitting a game-winning shot. And there were enough moments like that to help us power through the five years it took to finish the book. But no day, no moment, was quite like the one when we found a 1952 Claude Shannon speech that had been all but forgotten. Claude Shannon thought about and wrote about many things — but he didn’t pontificate about creativity, or thinking, or genius. Better, he thought, to do those things than to talk about them. There was one exception, though, and it was a speech he gave in 1952 to his fellow Bell Labs engineers. The speech was in a volume of unpublished papers, buried toward the end. We’ve written about it elsewhere, adding our own interpretation to a genius’s musings on genius. But for the sake of giving Shannon fans — both old and new — the same thrill we had when we stumbled on this speech, we decided to put the full text of it here. “Creative Thinking” Claude Shannon March 20, 1952 Up to 100% of the amount of ideas produced, useful good ideas produced by these signals, these are supposed to be arranged in order of increasing ability. At producing ideas, we find a curve something like this. Consider the number of curves produced here — going up to enormous height here. A very small percentage of the population produces the greatest proportion of the important ideas. This is akin to an idea presented by an English mathematician, Turing, that the human brain is something like a piece of uranium. The human brain, if it is below the critical lap and you shoot one neutron into it, additional more would be produced by impact. It leads to an extremely explosive of the issue, increase the size of the uranium. Turing says this is something like ideas in the human brain. There are some people if you shoot one idea into the brain, you will get a half an idea out. There are other people who are beyond this point at which they produce two ideas for each idea sent in. Those are the people beyond the knee of the curve. I don’t want to sound egotistical here, I don’t think that I am beyond the knee of this curve and I don’t know anyone who is. I do know some people that were. I think, for example, that anyone will agree that Isaac Newton would be well on the top of this curve. When you think that at the age of 25 he had produced enough science, physics and mathematics to make 10 or 20 men famous — he produced binomial theorem, differential and integral calculus, laws of gravitation, laws of motion, decomposition of white light, and so on. Now what is it that shoots one up to this part of the curve? What are the basic requirements? I think we could set down three things that are fairly necessary for scientific research or for any sort of inventing or mathematics or physics or anything along that line. I don’t think a person can get along without any one of these three. The first one is obvious — training and experience. You don’t expect a lawyer, however bright he may be, to give you a new theory of physics these days or mathematics or engineering. The second thing is a certain amount of intelligence or talent. In other words, you have to have an IQ that is fairly high to do good research work. I don’t think that there is any good engineer or scientist that can get along on an IQ of 100, which is the average for human beings. In other words, he has to have an IQ higher than that. Everyone in this room is considerably above that. This, we might say, is a matter of environment; intelligence is a matter of heredity. Those two I don’t think are sufficient. I think there is a third constituent here, a third component which is the one that makes an Einstein or an Isaac Newton. For want of a better word, we will call it motivation. In other words, you have to have some kind of a drive, some kind of a desire to find out the answer, a desire to find out what makes things tick. If you don’t have that, you may have all the training and intelligence in the world, you don’t have questions and you won’t just find answers. This is a hard thing to put your finger on. It is a matter of temperament probably; that is, a matter of probably early training, early childhood experiences, whether you will motivate in the direction of scientific research. I think that at a superficial level, it is blended use of several things. This is not any attempt at a deep analysis at all, but my feeling is that a good scientist has a great deal of what we can call curiosity. I won’t go any deeper into it than that. He wants to know the answers. He’s just curious how things tick and he wants to know the answers to questions; and if he sees thinks, he wants to raise questions and he wants to know the answers to those. Then there’s the idea of dissatisfaction. By this I don’t mean a pessimistic dissatisfaction of the world — we don’t like the way things are — I mean a constructive dissatisfaction. The idea could be expressed in the words, This is OK, but I think things could be done better. I think there is a neater way to do this. I think things could be improved a little. In other words, there is continually a slight irritation when things don’t look quite right; and I think that dissatisfaction in present days is a key driving force in good scientists. And another thing I’d put down here is the pleasure in seeing net results or methods of arriving at results needed, designs of engineers, equipment, and so on. I get a big bang myself out of providing a theorem. If I’ve been trying to prove a mathematical theorem for a week or so and I finally find the solution, I get a big bang out of it. And I get a big kick out of seeing a clever way of doing some engineering problem, a clever design for a circuit which uses a very small amount of equipment and gets apparently a great deal of result out of it. I think so far as motivation is concerned, it is maybe a little like Fats Waller said about swing music — “either you got it or you ain’t.’’ if you ain’t got it, you probably shouldn’t be doing research work if you don’t want to know that kind of answer. Although people without this kind of motivation might be very successful in other fields, the research man should probably have an extremely strong drive to want to find out the answers, so strong a drive that he doesn’t care whether it is 5 o’clock — he is willing to work all night to find out the answers and al weekend if necessary. Well now, this is all well and good, but supposing a person has these three properties to a sufficient extent to be useful, are there any tricks, any gimmicks that he can apply to thinking that will actually aid in creative work, in getting the answers in research work, in general, in finding answers to problems? I think there are, and I think they can be catalogued to an certain extent. You can make quite a list of them and I think they would be very useful if one did that, so I am going to give a few of them which I have thought up or which people have suggested to me. And I think if one consciously applied these to various problems you had to solve, in many cases you’d find solutions quicker than you would normally or in cases where you might not find it at all. I thing that good research workers apply these things unconsciously; that is, they do these things automatically and if they were brought forth into the conscious thinking that here’s a situation where I would try this method of approach that would probably get there faster, although I can’t document this statement. The first one that I might speak of is the idea of simplification. Suppose that you are given a problem to solve, I don’t care what kind of a problem — a machine to design, or a physical theory to develop, or a mathematical theorem to prove, or something of that kind — probably a very powerful approach to this is to attempt to eliminate everything from the problem except the essentials; that is, cut it down to size. Almost every problem that you come across is befuddled with all kinds of extraneous data of one sort or another; and if you can bring this problem down into the main issues, you can see more clearly what you’re trying to do and perhaps find a solution. Now, in so doing, you may have stripped away the problem that you’re after. You may have simplified it to a point that it doesn’t even resemble the problem that you started with; but very often if you can solve this simple problem, you can add refinements to the solution of this until you get back to the solution of the one you started with. A very similar device is seeking similar known problems. I think I could illustrate this schematically in this way. You have a problem P here and there is a solution S which you do not know yet perhaps over here. If you have experience in the field represented, that you are working in, you may perhaps know of a somewhat similar problem, call it P’, which has already been solved and which has a solution, S’, all you need to do — all you may have to do is find the analogy from P’ here to P and the same analogy from S’ to S in order to get back to the solution of the given problem. This is the reason why experience in a field is so important that if you are experienced in a field, you will know thousands of problems that have been solved. Your mental matrix will be filled with P’s and S’s unconnected here and you can find one which is tolerably close to the P that you are trying to solve and go over to the corresponding S’ in order to go back to the S you’re after. It seems to be much easier to make two small jumps than the one big jump in any kind of mental thinking. Another approach for a given problem is to try to restate it in just as many different forms as you can. Change the words. Change the viewpoint. Look at it from every possible angle. After you’ve done that, you can try to look at it from several angles at the same time and perhaps you can get an insight into the real basic issues of the problem, so that you can correlate the important factors and come out with the solution. It’s difficult really to do this, but it is important that you do. If you don’t, it is very easy to get into ruts of mental thinking. You start with a problem here and you go around a circle here and if you could only get over to this point, perhaps you would see your way clear; but you can’t break loose from certain mental blocks which are holding you in certain ways of looking at a problem. That is the reason why very frequently someone who is quite green to a problem will sometimes come in and look at it and find the solution like that, while you have been laboring for months over it. You’ve got set into some ruts here of mental thinking and someone else comes in and sees it from a fresh viewpoint. Another mental gimmick for aid in research work, I think, is the idea of generalization. This is very powerful in mathematical research. The typical mathematical theory developed in the following way to prove a very isolated, special result, particular theorem — someone always will come along and start generalization it. He will leave it where it was in two dimensions before he will do it in N dimensions; or if it was in some kind of algebra, he will work in a general algebraic field; if it was in the field of real numbers, he will change it to a general algebraic field or something of that sort. This is actually quite easy to do if you only remember to do it. If the minute you’ve found an answer to something, the next thing to do is to ask yourself if you can generalize this anymore — can I make the same, make a broader statement which includes more — there, I think, in terms of engineering, the same thing should be kept in mind. As you see, if somebody comes along with a clever way of doing something, one should ask oneself “Can I apply the same principle in more general ways? Can I use this same clever idea represented here to solve a larger class of problems? Is there any place else that I can use this particular thing?” Next one I might mention is the idea of structural analysis of a problem. Suppose you have your problem here and a solution here. You may have two big a jump to take. What you can try to do is to break down that jump into a large number of small jumps. If this were a set of mathematical axioms and this were a theorem or conclusion that you were trying to prove, it might be too much for me try to prove this thing in one fell swoop. But perhaps I can visualize a number of subsidiary theorems or propositions such that if I could prove those, in turn I would eventually arrive at this solution. In other words, I set up some path through this domain with a set of subsidiary solutions, 1, 2, 3, 4, and so on, and attempt to prove this on the basis of that and then this one the basis of these which I have proved until eventually I arrive at the path S. Many proofs in mathematics have been actually found by extremely roundabout processes. A man starts to prove this theorem and he finds that he wanders all over the map. He starts off and prove a good many results which don’t seem to be leading anywhere and then eventually ends up by the back door on the solution of the given problem; and very often when that’s done, when you’ve found your solution, it may be very easy to simplify; that is, to see at one stage that you may have short-cutted across here and you could see that you might have short-cutted across there. The same thing is true in design work. If you can design a way of doing something which is obviously clumsy and cumbersome, uses too much equipment; but after you’ve really got something you can get a grip on, something you can hang on to, you can start cutting out components and seeing some parts were really superfluous. You really didn’t need them in the first place. Now one other thing I would like to bring out which I run across quite frequently in mathematical work is the idea of inversion of the problem. You are trying to obtain the solution S on the basis of the premises P and then you can’t do it. Well, turn the problem over supposing that S were the given proposition, the given axioms, or the given numbers in the problem and what you are trying to obtain is P. Just imagine that that were the case. Then you will find that it is relatively easy to solve the problem in that direction. You find a fairly direct route. If so, it’s often possible to invent it in small batches. In other words, you’ve got a path marked out here — there you got relays you sent this way. You can see how to invert these things in small stages and perhaps three or four only difficult steps in the proof. Now I think the same thing can happen in design work. Sometimes I have had the experience of designing computing machines of various sorts in which I wanted to compute certain numbers out of certain given quantities. This happened to be a machine that played the game of nim and it turned out that it seemed to be quite difficult. If took quite a number of relays to do this particular calculation although it could be done. But then I got the idea that if I inverted the problem, it would have been very easy to do — if the given and required results had been interchanged; and that idea led to a way of doing it which was far simpler than the first design. The way of doing it was doing it by feedback; that is, you start with the required result and run it back until — run it through its value until it matches the given input. So the machine itself was worked backward putting range S over the numbers until it had the number that you actually had and, at that point, until it reached the number such that P shows you the correct way. Well, now the solution for this philosophy which is probably very boring to most of you. I’d like now to show you this machine which I brought along and go into one or two of the problems which were connected with the design of that because I think they illustrate some of these things I’ve been talking about. In order to see this, you’ll have to come up around it; so, I wonder whether you will all come up around the table now. This piece was the by-product of work on this book: Yes, it’s out. And of course, we’d love for you to read it. Conveniently and fittingly, It’s available in both analog and digital formats: paperback, audiobook, Kindle. We figured the book needed to have one foot in the world Claude lived in and one in the world he helped create. (Plus, that’s how the publisher was planning to do it anyway, though it’s nice to pretend that we did it on purpose as some grand metaphor about our subject’s life.) If you enjoyed this story, please recommend and share to help others find it! Feel free to leave a comment below. The Mission publishes stories, videos, and podcasts that make smart people smarter. You can subscribe to get them here. Claude Shannon’s “Creative Thinking” Speech: A Genius Reveals How To Be Creative Label: grist Date: August 15, 2017 at 07:33PM Labeled: August 15, 2017 at 07:36PM via GitHub http://ift.tt/2v00edT August 15, 2017 at 07:41PM via GitHub http://ift.tt/2v00edT [100-days-of-writing] Alien Intelligences and discriminatory algorithms - Chris Stucchio Alien Intelligences and discriminatory algorithms - Chris Stucchio By janzeteachesit Assigned to Alien Intelligences and discriminatory algorithms - Chris Stucchio http://ift.tt/1LBf9D7 GRIST4 Writing Alien Intelligences and discriminatory algorithms Mon 21 March 2016 bias detection / frequentist statistics / statistics In the Star Trek episode Let That Be Your Last Battlefield the Enterprise encounters two human-looking aliens (as is the Star Trek custom) from the planet Cheron. These aliens are full of intense ethnic hatred towards each other based on historical issues on their planet. This episode was broadcast in 1969; to a 2016 TV watcher like myself it comes off as a ham-handed criticism of American racial attitudes at the time. We, the human viewers, are of course oblivious to whatever happened on Cheron prior to this episode - most likely the human readers of my blog didn't notice that the Cheronese are mirror images of each other. As a result we find the hatred and conflict between the two Cheronese completely nonsensical. As aliens to the Cheronese, we (either the viewer or Captain Kirk) just don't care. Insofar as we might favor one Cheronese over the other, that would only be due to the danger or reward to the Enterprise. Captain Kirk cares about protecting the ship and discovering new life and new civilizations - minor aesthetic differences between two people from the same civilization are irrelevant to him. On Star Trek the majority of the aliens are just humans with colored makeup. In real life aliens will be truly different. One very important category of "alien" is machine learning - machine learning algorithms are completely alien to us and this fact is unfortunately lost on a lot of innumerate journalists. As AI-driven decisions are becoming more commonplace (e.g. in predicting crime, creditworthiness, advertisement delivery), pundits and journalists have become increasingly concerned that such algorithms might be "discriminatory" against various special classes of humans. Typically these pundits attribute to algorithms various human qualities; the mere ability to discriminate by race is treated as an assumption that the algorithm is doing so and in the same way that humans would. Cathy O'Neil - aka mathbabe - is one of the foremost writers in this field. In spite of her blog's title, she uses negligible amounts of math but lots of emotional rhetoric to groundlessly criticize statistics in order to sell books. Unfortunately this is all a load of anthropomorphic nonsense. Algorithms aren't people. While humans are known to be easily biased on physical traits of other humans, algorithms aren't. To a human, "race" or "sex" is a fundamental trait of another person. An algorithm cares about the 26'th element of a 100 element array as much as Kirk cares about who is black on the left - if it's predictive of something he cares about he'll pay attention, otherwise he doesn't care. It's a fair criticism that algorithms can reproduce biases in their inputs. But the assumption that they will do this - just like humans do - is fundamentally flawed. In reality, if the inputs to an algorithm are sufficiently informative, the algorithm will correct the bias in the inputs! This post is going to be somewhat mathematical. Unfortunately, while it's easy to criticize algorithms on emotional and anthropomorphic terms, it's very hard to defend them on that basis. So I'm going to introduce and explain linear regression - the simplest machine learning algorithm that I can think of - and show what conditions lead to algorithmic discrimination. What this article is about This article is about when and why an algorithm would discriminate, and more importantly when it won't. To illustrate this I'm going to construct a few hypothetical worlds, run an algorithm on that hypothetical world, and illustrate the output. By inverting this process, we can conclude that if an algorithm behaves a certain way, that is evidence that the world behaves in a corresponding manner (this is the uncomfortable part). At the end I also discuss some ethical issues, but I take no particular position. My main goal here is to push discussion of this issue in a less innumerate direction. What this article is NOT about This article is strictly NOT about badly implemented algorithms. Most of the people commenting on algorithmic discrimination are not arguing that a specific algorithm has an off-by-one error or proposing that we switch from a random forest to a deep neural network. I've never seen any LaTeX on mathbabe.org. In the event that an algorithm is incorrectly predicting outcomes, we can all agree that statisticians should do their jobs better. All the simulation experiments in this article will be carefully tuned to avoid this situation. I'll be generating gaussian data and fitting a linear model to it via least squares. The key point here is to avoid methodological errors - because I'm setting up the problem to be simple and easily solvable, you can't get a significantly better result via better algorithm choices. Instead, we'll need to actually recognize and confront the reality that good algorithms might yield correct results we don't like. I'm very strictly NOT claiming that all real world models are perfect. I'm just assuming that bad models are a math problem with a math solution and therefore beyond the reach of Techcrunch and Mathbabe. Different kinds of discrimination To begin with, we need to define what we mean by discrimination, and unfortunately there are several definitions floating around. Direct Discrimination: This form of discrimination is basically traditional racism - you encode your preferences into a model. However, this is pretty uncommon in more formal predictive models. When writing code, very few data scientists will write this: if applicant.race == 'black': fico -= 100 That's certainly something that will be spotted in code review, and it's also pretty easy to prevent with automated tools, e.g.: for a in applicants: a.race = None predictive_algorithm(applicants) I'm going to call a data set without direct information on protected classes scrubbed. Disparate Impact: This is when you have an unbiased algorithm, but the outcome of that algorithm is affects different protected classes differently. Direct discrimination can certainly cause a disparate impact, but there are lots of other possible causes. For example, if black people are taller than white people, a basketball competition will have a disparate inpact in their favor. Redundant encoding: This is what happens when you give an algorithm lots of data, and ask it to learn hidden features of the underlying probability distribution. The redundant encoding may then rediscover (at least probabilistically) some data which has been scrubbed. An example of this, consider the following example from Delip Rao. A data set has race scrubbed from it. However, it includes location and income. A second order kernel might then discover Feature6578 = Loc=EastOakland && Income<10k. This feature is strongly correlated with race. So although race was scrubbed from the algorithm, this data was redundantly encoded in the data. One really important thing to recognize is that none of these forms of discrimination necessarily yield incorrect results. This means that if gambler A has a gambling strategy based on some sort of discriminatory algorithm, and gambler B has a non-discriminatory one, gambler A might be systematically taking money from gambler B. Bias: This is a statistical property of an algorithm, and there are a variety of fairly technical definitions in different contexts. The most useful one here is that bias is the difference between an estimator's expected value and the true value of a parameter. Linear regression For most of this discussion, I'm going to take linear regression as a toy model. Linear regression is one of the simplest algorithms for building a predictor. The basic idea is the following. Consider an output variable - a quantity I wish to predict. I'm given a set of points: The value is a d-dimensional vector representing the my input variables. In python terms, it's an array of floats of length d. The value is a real number which represents my output. In python terms, it's a single float. Linear regression is the process of coming up with a function of the following form which predicts given : The vector is another (fixed) d-dimensional vector, and is a scalar. In python terms, we want a predictor of the form: def y_predict(x): assert(len(x) == d) result = beta for i in range(d): result += alpha[i]x[i] return result Using the numpy library for python, one can also simplify this to return dot(alpha, x) + beta, but I wrote out the for-loop once for pedagogical purposes. The goal of linear regression is to find the values of alpha (an array of floats) and beta (a float) which fit the data as closely as possible, perhaps subject to specific constraints (e.g. sparsity, matching a prior). In this post I'll always be doing least squares fits - choosing to minimize Pythonic example Our first example is very simple. We have 3 variables and a true model alpha_true = [1,2,3]. We have a data set of 1000 3-dimensional vectors, together with outputs. The outputs are generated by simply taking the true model and adding random noise to it. In python code: from numpy import from numpy.linalg import lstsq from scipy.stats import norm nvars = 3 alpha_true = [1,2,3] N = 1000 data = norm(0,1).rvs((N, nvars)) output = dot(data, alpha_true) + norm(0,1).rvs(N) print lstsq(data, output) The output array is: array([ 0.98027674, 2.0033624 , 3.00109578]) This is pretty close to the true value used to generate the input, as it should be. Real world example Suppose we wish to predict first year GPA in college. The variable x[0] might represent an SAT Z-score and the variable x[1] might represent a high school exit exam Z-score. The variable y could represent first year GPA. Then linear regression might yield x[0] = 0.368 and x[1] = 0.287 (example is truncated from here). So the prediction would be: (Here is not directly listed in the paper, but it is a concrete and known value.) What if race/other protected class doesn't matter? Lets consider the following situation. Suppose we want to predict an output variable - say college GPA, following along the example above. Suppose we have two predictive variables - SAT z-score and exit exam Z-score. We also have race as a third variable. Lets assume that for each person, race has no causal relationship with GPA. Suppose we run a linear regression. What will we get? In python terms we've generated the data as follows: alpha_true = [0.368, 0.287, 0] N = 1000 data = norm(0,1).rvs((N, nvars)) data = zeros(shape=(N,nvars), dtype=float) data[:,0:2] = norm(0,1).rvs((N,2)) #Z-score variables data[:,2] = bernoulli(0.25).rvs(N) #Race, 1 if black output = dot(data, alpha_true) + norm(0,1).rvs(N) The output is something along the lines of alpha=[ 0.36679413, 0.32865146, 0.0110941 ] - we rediscover that SAT and exit exam matter, and race doesn't. Due to statistical noise, the coefficient on race (the third variable) isn't zero, but it's very close. Additionally, there is no particular sign on it - depending on how the noise looks, our predictor might slightly overpredict or underpredict black GPA. In this case, we have no significant discrimination, no disparate impact, and no redundant coding. We also have no bias. Most importantly, the algorithm had the opportunity to introduce bias but chose not to. That's hardly surprising; the algorithm's only desire in life is minimizing squared error - being unkind to black people a silly thing that humans seem to enjoy for no apparent reason. If race (or x[2] to the algorithm) is not useful in minimizing squared error then the square error minimizer will ignore it, just as Captain Kirk barely noticed the mirror image of the aliens. Another great essay on distinguishing algorithmic desires from human desires is Bostrom's parable of the paperclip maximizer (see also lesswrong). What if black people don't perform as well? Now lets consider the following situation. Due to various historical factors, black people perform worse at the pre-college level. At the college level, lets suppose they perform exactly as well as their pre-college scores predict. I.e., our causal model changes as follows: data = norm(0,1).rvs((N, nvars)) data = zeros(shape=(N,nvars), dtype=float) data[:,0:2] = norm(0,1).rvs((N,2)) #Z-score variables data[:,2] = bernoulli(0.25).rvs(N) #Race, 1 if black data[where(data[:,2] == 1),0:2] -= 0.5 # Black people have lower SAT/GPA alpha_true = [0.368, 0.287, 0] #But holding SAT/GPA fixed, race doesn't matter. output = dot(data, alpha_true) + norm(0,1).rvs(N) What we are assuming in this case is that race still doesn't matter holding academics constant. I.e., a black person with a 1300 SAT is likely to have the same GPA as a white person with a 1300 SAT. The output? alpha = [ 0.36904923, 0.29184296, 0.02953688]. Just like before, we've faithfully reproduced our input model. However, we've now found a model with a disparate impact. The model we have predicts that blacks will score, on average, 0.3278 points lower. The reason the model predicts this is because it's true: In [15]: mean(output[where(data[:,2] == 1)]) #black people Out [15]: -0.300591159584 In [16]: mean(output[where(data[:,2] == 0)]) #white people Out [15]: -0.0107252756984 So in this case, our model has a disparate impact because it accurately reflects the world. If we want to avoid a disparate impact, the only way we can do that is by adding +0.30 to the scores of black people, but then we'll be increasing the squared error significantly. We also have no bias. What if measurements are biased? It's been claimed in many places that the SAT, high school GPA, and similar measures are biased against some groups. What would be the effect of this? Lets suppose we have the following relationship. Each person has an intrinsic ability. SAT and high school exit exam are noisy measurements of ability. Also, lets assume that these measurements are biased - the measurements reduce the scores of black people, but they do not reduce our output variable (namely college performance). Our model looks like this: ability = norm(0,1).rvs(N) #The true driver data = norm(0,1).rvs((N, nvars)) data = zeros(shape=(N,nvars), dtype=float) data[:,2] = bernoulli(0.25).rvs(N) #Race, 1 if black data[:,0] = 0.5ability[:] + norm(0,1).rvs(N) data[:,0] -= 0.5data[:,2] #Biasing the SAT data[:,1] = 0.5ability[:] + norm(0,1).rvs(N) data[:,1] -= 0.5data[:,2] #Biasing exit exams output = ability + norm(0,1).rvs(N) The net result of linear regression here is alpha = [ 0.34523587, 0.33528078, 0.31779809]. Our process in generating the data was biased, but our learning algorithm discovered that and corrected for it! If we scrubbed the data this result would be impossible. Running least squares on scrubbed data yields alpha = [ 0.29878373, 0.30869833] - we can't correct for bias because we don't know the variable being biased on. As an intellectual exercise, lets consider as a hypothetical that our data was biased differently. Suppose instead of being biased against blacks, our measurements were biased in favor. The outcome would be more or less the same except that the coefficient on race would be negative: alpha = [ 0.32611793, 0.34397119, -0.30572819]. This is pretty cool. Our machine learning algorithm doesn't seem to be doing what the pundits and journalists predict at all. Rather than incorporating human bias, it seems to be detecting it and correcting for it! That's because least squares isn't human. It doesn't know what data[:,0] or data[:,2] mean - all it knows is that it wants to predict the outcomes as accurately as possible. So in this example, we have no disparate impact and no bias. We do, however, have direct discrimination - the algorithm is discriminating in favor of blacks in order to cancel out biases earlier in the process. Also note: Under other circumstances, it's totally uncontroversial to claim that a statistical algorithm can eliminate bias. For example, you probably find it completely unsurprising that I can use statistics to correct for bias in a mobile phone's compass. Real world interlude The analysis above yields some interesting testable predictions. Supposing bias exists, we should be able to detect it by directly conditioning on race and observing the coefficient. If the coefficient is positive, it means that the observables are biased against that race. If it's negative, it means they are biased in favor. And if it's zero, it means things are unbiased. This analysis has actually been done. For example, this paper discovers that SAT, high school exit exams and similar predictors are mildly biased against Asians and fairly strongly in favor of blacks. These predictors are also mildly biased against students from high-income families, against women, and in favor of people with unmet educational need. Similar results more or less agree with this. Here's a blog post that links to data, so the interested reader can run this analysis themself. An alternate formulation of bias There is a different (but mathematically equivalent) way to formulate bias. Rather than subtracting from the input scores, we could equivalently add to the output scores. I.e., we previously chose as our model: data[:,0] = 0.5ability[:] + norm(0,1).rvs(N) data[:,0] -= 0.5data[:,2] #Biasing the SAT data[:,1] = 0.5ability[:] + norm(0,1).rvs(N) data[:,1] -= 0.5data[:,2] #Biasing exit exams output = ability + norm(0,1).rvs(N) What if we instead chose: data[:,0] = 0.5ability[:] + norm(0,1).rvs(N) data[:,1] = 0.5ability[:] + norm(0,1).rvs(N) output = ability + norm(0,1).rvs(N) output += 0.33data[:,2] The net result is the same - alpha = [ 0.32258076 0.32353926 0.3253351 ]. This is a pretty straightforward mathematical equivalence - we are just moving a variable from the left to the right. This means that we cannot distinguish between the inputs being biased or the factor we are biased on actually being directly causal. I.e., as far as linear regression (and many similar algorithms) is concerned, the propositions "SAT/Exit exams are biased against blacks" is equivalent to the statement "Blacks are 'intrinsically' superior in a manner not reflected in exit exam/SAT". The word 'intrinsically' means that either blackness, or some hidden variable which is correlated with it (the more likely possibility), directly causes outcomes to change. What if we scrub race, but redundantly encode it? Lets now consider the situation where race doesn't matter, and we've scrubbed the data, but we redundantly encode it. Lets suppose we have 3 new binary variables, generated via the following process: data[:,2] = racebernoulli(0.4).rvs(N) + bernoulli(0.1).rvs(N) data[:,3] = racebernoulli(0.4).rvs(N) + bernoulli(0.1).rvs(N) data[:,4] = racebernoulli(0.4).rvs(N) + bernoulli(0.1).rvs(N) data[:,2:] = minimum(data[:,2:],1.0) So for each person, we generate 3 new variables, which are either true or false. If a person is black, these variables have a 40% chance of being equal to 1, otherwise they have a 10% chance. This means that the more of these variables are true, the more likely it is that a person is black. The result of regression is alpha = [ 0.3374577 , 0.32448367, 0.04370261, -0.01621927, -0.02446477]. Even though our algorithm could, if it wanted to, determine a person's race, it has no reason to. This is true even if we include lots of redundant encoding, say 28 of them. The result is simply: alpha = [ 0.33345215, 0.32298627, -0.07885754, 0.00441561, 0.04332198, 0.00825558, -0.06916433, 0.06032788, 0.02769571, -0.01998633, 0.06123838, 0.04794704, -0.01579531, -0.00326249, -0.03947687, 0.00117585, -0.00274476, -0.02228296, -0.02865488, -0.03107947, -0.05825314, -0.06108869, 0.03893044, -0.06881212, 0.04479646, 0.09647968, 0.02672891, -0.04827223, 0.01878823, 0.03254893] In this situation, it's pretty easy to determine if a person is black - compute sum(data[i,2:]) and check whether it's closer to 0.428 or 0.128. If it's the former they are black, if it's the latter they aren't. The algorithm doesn't care about this redundant encoding because even if it knew, that's not useful. However, if we bias the inputs, suddenly the algorithm does care. Biasing the inputs (as described above) yields alpha = [ 0.32504926 0.30582667 0.14417805 0.08187899 0.11585452]. Equivalently, as discussed above, if race is directly causal (which is mathematically equivalent to bias), then the algorithm will also care. In short, redundant encoding has the same effect (albeit weaker) as directly encoding race. It allows an algorithm to correct for biased inputs or (mathematically equivalently) to discover that one group is intrinsically better/worse performing than another. But that's all it does - discover these effects. It doesn't introduce these effects if they are not present in the data. Redundant encoding does not cause algorithms to vote for Donald Trump. It doesn't make otherwise friendly algorithms wear bedsheets and burn a cross. All it does is give them a piece of data and allow them to discover how well that data predicts outcomes. Furthermore, they will only discover the redundant encoding if the data actually matters (very different from what humans do)! What if you do make statistical errors? Over at Algorithmic Fairness, Sorelle points out that sometimes an algorithm doesn't have sufficient training data to actually detect and correct for bias in the manner I've described: If an all-white company attempts to use their current employees as training data, i.e., attempts to find future employees who are like their current employees, then they’re likely to continue being an all-white company. What Sorelle fails to account for is that bias has no consistent sign. Bias like what he describes may exist, but our alien intelligence has no particular reason to give this bias a negative sign. In terms of our analogy above, suppose Captain Kirk jumps to conclusions as to which kind of Cherosian is more dangerous to the Enterprise than the other. Is there any reason for Kirk's bias to be positive towards the Black-Left Cherosian rather than the Black-Right one? As noted above, in the academic example described, the bias in favor of blacks due to excluding racial data is actually positive! By using a white student body and then doing the linear regression described here would yield more black students, not less. Correcting the bias involves heavily penalizing black applicants; failing to detect the need for this penalty will result in more being admitted. Bias can have a positive sign! I've seen similar effects in credit decisions, though I haven't gone through the details. (I'm a big fan of the randomcriticalanalysis blog because he provides his data.) Furthermore, this kind of issue falls well within the category of statisticians not doing their job well. Algorithms and processes may prematurely converge, but better statistics can prevent this. Fixing the bias is just a matter of running an experiment; allow in enough black students to measure performance in order to get a sufficiently high sample size (due to the law, does not have to approach ). The key point to takeaway is that bias can have any sign, positive or negative. Alien intelligences might develop bias, but there is no reason whatsoever to expect that their bias will be positive or negative. Sorelle's assumption that alien bias will mimic human bias is nothing but anthropomorphic reasoning. Ethical questions Most of the folks discussing ethical issues surrounding algorithms are, unfortunately, being either innumerate or disingenuous. Machine learning algorithms are not humans in disguise - they are completely alien "intelligences" which think about things in a totally different manner than we do. An alien intelligence (human viewers or Captain Kirk) look at the Vulcan and the Romulan above and don't see a big difference. I doubt anyone reading who isn't a Star Trek fan does either. However, over time, Kirk and the viewers learned to tell the difference. Vulcans tend to be peaceful science types like Spock. Romulans tend to be hostile and destroy Federation outposts. The prospect of being shot with energy weapons is the only thing that leads an alien intelligence to work hard to distinguish the difference between them - if both were equally hostile or equally peaceful, the viewer would treat their differences like those of the Cheronians. Machine learning is an alien intelligence. When implemented correctly it will not reproduce human biases; when human biases lead to factually incorrect results the alien intelligence will correct them as best it can. Even when given information about factors which bias humans, the alien intelligence will not learn that they matter unless they do. Algorithms care about different categories of human as little as dogs, goats or Romulans do. This leads us to an uncomfortable conclusion. In everyday life we usually assume that racism and stereotypes are factually incorrect and driven by human biases; therefore eliminating them we will get better outcomes all around. When different flavors of intelligence all converge to the same belief, that's evidence that the belief might be true. Intuitively we know and accept this fact. If 10 scientists - each using a different statistical methodology and experiment design - all draw the same conclusion about Gallium Arsenide photonic crystals then we will likely believe them. When 10 data scientists running 20 algorithms draw the same conclusion about humans, we instead call the statistics racist. We need to start accepting the possibility that discriminatory algorithms might be factually correct and then figure out what to do about it. The real ethical issues being raised are a lot trickier than what Techcrunch and Mathbabe want to admit. If the issue was simply incorrect algorithms giving wrong conclusions that seem racist, then the solution is simply smarter statisticians with better algorithms. The real ethical issue that the algorithms might be right. Suppose we build a credit allocation algorithm that turns out to be "racist" - i.e., the algorithm accurately predicts that a black person will be more likely to default than a similarly situated white person. Should we ignore this effect, and scrub the model sufficiently in order to eliminate this prediction? That seems like burying our heads in the sand. Is it even beneficial for any individual? Giving a person a loan they are likely to default on seems harmful to both the lender and the borrower, as is admitting a person to a college with a high probability of dropping out. (I've seen an analysis on the topic of credit but I haven't fully gone through the details. It looks to be in the ballpark of correct, though of course statistics is hard.) Ultimately there are no easy choices here. It would be wonderful if we had an algorithm which was racially unbiased (neither via direct discrimination nor redundant encoding), accurately predicts college dropouts/delinquent loans/etc, and also serves the needs of "social justice" (a poorly defined term which I understand mainly as mood affiliation). Unfortunately the more we look, the more it seems that we can't have all of these things simultaneously. The ethical question which no one really wants to discuss is what tradeoffs we are willing to make. How many delinquent loans is more individual or group fairness worth? My priors My initial inclination, as of a few years back, was to support race-blind policies - policies which eliminate direct discrimination and possibly redundant encoding. Such policies seem intrinsically fair to me. At this point I'm not so sure - the analysis above in the section "What if measurements are biased" suggests this might not be optimal. If we directly include race in a statistical analysis we can accurately correct for existing biases in the input data. This kind of suggests support for traditional affirmative action except that the sign is wrong - the most accurate correction we could do (at least for college admissions) would heavily penalize blacks and benefit Asians (the exact opposite of current policies). On the other hand, using an algorithm which is directly discriminatory or uses redundant encoding is intrinsically unfair on the level of individuals. I don't like this very much either. I'm now really confused on the topic. Conclusions Recently, AlphaGo (an AI) played several go matches against Lee Sedol, the champion of the humans. AlphaGo won. Fan Hui, the commentator could only say of AlphaGo's strategy: "It's not a human move. I've never seen a human play this move". Earlier this year, an AI was used to design antennas. These antennas also don't look like anything a human would have designed. Neither do the laser pulses generated by machine intelligences when attempting to optimally control quantum state excitation - something I studied a little bit in a previous life. Machine intelligence simply doesn't think the way humans do. When you encounter someone in Techcrunch or NPR assuming machines will reproduce human biases and conclusions, the right question to ask whether those people are clueless or lying to you. Alien Intelligences and discriminatory algorithms - Chris Stucchio Label: grist Date: August 15, 2017 at 07:37PM Labeled: August 15, 2017 at 07:41PM via GitHub http://ift.tt/2vHmQSG August 15, 2017 at 07:41PM via GitHub http://ift.tt/2vHmQSG [100-days-of-writing] Chris Stucchio Chris Stucchio By janzeteachesit Assigned to http://ift.tt/2uNw3Hv GRIST4 Chris Stucchio Label: grist Date: August 15, 2017 at 07:39PM Labeled: August 15, 2017 at 07:41PM via GitHub http://ift.tt/2w0heoT August 15, 2017 at 07:41PM via GitHub http://ift.tt/2w0heoT [100-days-of-writing] site:http://ift.tt/2i3DOaB filetype:pdf g8 - Google Search site:http://ift.tt/2i3DOaB filetype:pdf g8 - Google Search By janzeteachesit Assigned to http://ift.tt/2fJpNxT GRIST4 CSP site:http://ift.tt/2i3DOaB filetype:pdf g8 - Google Search Label: grist Date: August 15, 2017 at 08:04PM Labeled: August 15, 2017 at 08:06PM via GitHub http://ift.tt/2x2ZINX August 15, 2017 at 08:06PM via GitHub http://ift.tt/2x2ZINX [100-days-of-writing] Fractions infinity in Grades 3-4 | Math Code 'Zine Fractions infinity in Grades 3-4 | Math Code 'Zine By janzeteachesit Assigned to Fractions + infinity in Grades 3-4 | Math + Code 'Zine http://ift.tt/2i3oTgx GRIST4 STEM Maths Fractions + infinity in Grades 3-4 Alycia Cazzola, Melanie Drummond, Katherine Kenney, Rebekah McElhone & Judy Mullen — Grade 3-4 teachers, Wellington Catholic DSB We walk in and out of our classroom door several times in a school day. Have you ever stopped to consider the fractions we encounter on the way? What if I continue traveling half of the remaining distance, on and on, forever? Will I ever get to the door? Most children say: “No. It’s not possible!” But how can that be? I travel to the door lots of times, and on my way I pass all of these fractions, and I do get there. Is it only when I think about the fractions that it makes a difference? Children shaded 8×8 grids to represent the first 6 fractions on the way to the door: 1/2, 1/4, 1/8, 1/16, 1/32 and 1/64. Then we asked: “If you cut out all of the shaded areas, for all the fractions to the door, and then put them together to form a new shape, how big would that shape be? Would it fit in our classroom? In Guelph? In your hand? In Canada?” Children guessed that it would grow forever and would not fit in our classroom. But when they started cutting out the shaded parts, they noticed that they all fit in one single 8×8 square, and that “I can hold infinity in my hand!” Now that’s something they looked forward to sharing at home. The we used the Repeating Patterns coding environment at http://ift.tt/2fJoY8v [There’s fractions tutorial at this link you can use. We adapted it for our lesson plan. And we printed it for children to take home to share with parents.] Children used code to create grids with colour and we discussed the fractions hiding inside. Interestingly, most children first saw 4/8 in the grid above. 4 of 8 columns are red. Then 32/64. 32 out of 64 small squares are red. Then, lastly,they saw that 1/2 of the grid (or the columns, or the small squares) is red. There was a lot of incidental learning of equivalent fractions, which we had not planned to teach. “One thing I noticed was the kids’ ability to reduce fractions to their smallest for, ie. 50/100 was 1/2. Equivalent fractions was definitely a big lesson for that day!” “Here is a video of a student giving the equivalent fraction and naming 50/100. This was a big moment for me to see! I was impressed. We hadn’t worked with fractions that ‘big’ or named equivalent fractions.” “Here is another student who began to give me lots of information about coding and the we switched to talking about fractions and he was able to pull out the equavalent fraction too.” Then children were challenged to create the patterns below, and identify the fractions hiding inside. And they created their own fraction patterns! It was lots of fun! Fractions + infinity in Grades 3-4 | Math + Code 'Zine Label: grist Date: August 15, 2017 at 08:06PM Labeled: August 15, 2017 at 08:11PM via GitHub http://ift.tt/2wOaDvn August 15, 2017 at 08:17PM via GitHub http://ift.tt/2wOaDvn [100-days-of-writing] Repeating Patterns Repeating Patterns By janzeteachesit Assigned to http://ift.tt/2i3Ysaq GRIST4 STEM Math Repeating Patterns Label: grist Date: August 15, 2017 at 08:08PM Labeled: August 15, 2017 at 08:11PM via GitHub http://ift.tt/2wOej0d August 15, 2017 at 08:17PM via GitHub http://ift.tt/2wOej0d [100-days-of-writing] MATH and CODE MATH and CODE By janzeteachesit Assigned to http://ift.tt/1XkXSh0 GRIST4 STEM Math MATH and CODE Label: grist Date: August 15, 2017 at 08:10PM Labeled: August 15, 2017 at 08:11PM via GitHub http://ift.tt/2vC2XOr August 15, 2017 at 08:17PM via GitHub http://ift.tt/2vC2XOr [100-days-of-writing] TIMESQUARE DIY Watch Kit - Red Display Matrix ID: 1106 - $29.95 : Adafruit Industries Unique & fun DIY electronics and kits TIMESQUARE DIY Watch Kit - Red Display Matrix ID: 1106 - $29.95 : Adafruit Industries Unique & fun DIY electronics and kits By janzeteachesit Assigned to TIMESQUARE DIY Watch Kit - Red Display Matrix ID: 1106 - $29.95 : Adafruit Industries, Unique & fun DIY electronics and kits http://ift.tt/IDKVch GRIST4 STEM TIMESQUARE DIY Watch Kit - Red Display Matrix ID: 1106 - $29.95 : Adafruit Industries, Unique & fun DIY electronics and kits Show up stylish AND on time to any event with this awesome looking DIY watch. We have a few watch kits here at Adafruit but we finally have one that looks good and fits well, even for ladies and kids and others with smaller wrists and hands. Its got a 8x8 bit matrix display and a repurposed silicone watch band for a professional look. 64 LEDs light up to tell you the time in a variety of ways. Built into the kit are 3 different watch 'faces' - a scrolling marquee with time and date, a binary watch display (for geeks, robots and binary fans), and a moon phase display (for beach-combers, werewolves). There's also a built in battery meter so you can check your battery life. Want to make your own watch? Easy! The microcontroller is an Arduino-compatible, all you need is an FTDI Friend and the Arduino IDE and you can design your own watch faces and upload them to the TIMESQUARE. This embedded content is from a site (www.youtube.com) that does not comply with the Do Not Track (DNT) setting now enabled on your browser. Clicking through to the embedded content will allow you to be tracked by www.youtube.com. Learn more about Adafruit's privacy policy here. Engineered for greatness by PaintYourDragon, this watch squeezes 500-1000 full time displays out of a coin battery, and a up to one year 'resting' lifetime, so you can use this as a day-to-day time keeper. This watch comes with a ultra bright red LED matrix and a black silicone watch band that fits all wrists from children to adult. The band is an "off-the-shelf" band that holds the watch in pretty well, we'll be creating other bands - the included band is to just get you started! This watch is meant to be hackable, from the software to the band! This is a DIY kit, and requires some basic soldering/assembly to put together. It is a beginner kit, so this is a fine project to use in learning how to solder. Tools are not included, you'll need a soldering iron, solder and diagonal cutters as a minimum. Check the tutorial page for details on what tools and steps are required to assemble. Take about 1-2 hours to put together. Build it in the afternoon and you'll be done in time to hit the clubs in the evening.For more information and downloads check out the page in the Adafruit Learning System. *To show the watch "in action" photos above have the LEDs on with the lights lowered and added the on-wrist photos with photo taken with flash & studio lighting. TIMESQUARE DIY Watch Kit - Red Display Matrix ID: 1106 - $29.95 : Adafruit Industries, Unique & fun DIY electronics and kits Label: grist Date: August 15, 2017 at 08:17PM Labeled: August 15, 2017 at 08:21PM via GitHub http://ift.tt/2vGQFT5 August 15, 2017 at 08:21PM via GitHub http://ift.tt/2vGQFT5 [100-days-of-writing] CodeSandbox: Online playground for React CodeSandbox: Online playground for React By janzeteachesit Assigned to https://codesandbox.io/ GRIST4 CSP CodeSandbox: Online playground for React Label: grist Date: August 16, 2017 at 10:07AM Labeled: August 16, 2017 at 10:16AM via GitHub http://ift.tt/2uJm766 August 16, 2017 at 10:21AM via GitHub http://ift.tt/2uJm766 [100-days-of-writing] 3 Ways to Design with Data room2learn Medium 3 Ways to Design with Data room2learn Medium By janzeteachesit Assigned to 3 Ways to Design with Data – room2learn – Medium http://ift.tt/2uJgx3t GRIST4 STEM 3 Ways to Design with Data – room2learn – Medium room2learnAug 16 3 Ways to Design with Data by room2learn Tick tock tick tock! We can all hear the time passing by as we inch closer to the start of the school year. Whether you’re an educator, teacher, or designer, a new school year gives you the opportunity to redesign your classroom — anything from changing the layout to adding new, smaller hacks to improve engagement. We’re big fans of trying out different layouts and seeing what happens, but there are ways to design in a more analytical, strategic way. In other words, we want to share three ways you could design with data in mind. Let’s take a closer look! The first method we’ll introduce is the Classroom Observation Protocol for Undergraduate STEM (COPUS). This process measures student-faculty interactions in the classroom setting based on the types of activities performed. Researchers observe each class with an Excel worksheet (included on the site) and a 30-second timer. During each 30-second interval, researchers check off activities performed by the instructor or the students on a list. All the information gathered could then be transformed into graphs that show the breakdown of class activities. The image below is a visual representation of two sample courses with different instructional approaches: the lecture-based course is primarily composed of the instructor lecturing and few interactions between students and the instructor (some question-answer). However, the active-learning model shows a diverse distribution of activities and a lot more interaction between the students and the instructor. Here at room2learn, we want to take this one step further. We know that space impacts learning, so after using this strategy, we invite you to think about how the layout of your room has impacted these activities and how a simple change in layout may shift your teaching practice. Let’s move on to the next two strategies! One of our favorite resources at room2learn is Edutopia. They have tons of great resources on tips and tricks to redesign your classroom space. We’ve taken two of their most effective “design with data” strategies and broken them down for you. The first is “classroom flow!” With “Classroom Flow,” the main concept is similar to COPUS as it involves observing the classroom in session. However, this exercise focuses more on having observers map out the way students and teachers move in the classroom. Here’s how to do it: Find an honest colleague or student who is free during a time that you teach! Ask them to come and observe how you and your students move in the classroom. Draw or design a diagram of your classroom, making sure to include any and all furniture and give it to your observer. Ask your colleague or student to observe you and your students and draw where everyone moves. Make sure to use one color for you and one color for your students! Meet with your colleague and discuss what they noticed! An example of a “classroom flow” observation sheet After outlining the movements in the classroom, you can easily see which parts of your classroom could use some redesign or extra attention, especially if you have one area of the map where movement is heavy. The map could also be used as a tool to identify underused spaces that could be transformed for new activities. For an example of how an architect observes a classroom, check out this blog post here. The next strategy uses our favorite brainstorming and designing tool — post-its! This is a great way to collectively brainstorm ways to improve a space or to solve an existing problem. Here’s one way to use sticky notes in tandem with the “classroom flow” strategy: After you’ve highlighted pain points in your classroom, post up sticky notes in that area. Then, ask students to brainstorm ways to solve that specific pain point. Having students generate ideas right in that area can help them come up with more viable ideas. If you read our post from two weeks ago, you know we are passionate about including students in your redesign process. Collecting real data from your classroom is an additional way to ensure that your classroom redesign is addressing the actual needs of your students. Happy designing! Have you collected data about your classroom space in an innovative way? Let us know at www.room2learn.org or Tweet us at @HackClassrooms! 3 Ways to Design with Data – room2learn – Medium Label: grist Date: August 16, 2017 at 10:40AM Labeled: August 16, 2017 at 10:41AM via GitHub http://ift.tt/2vJ3oop August 16, 2017 at 10:41AM via GitHub http://ift.tt/2vJ3oop [100-days-of-writing] How to live without sketch & rock with Photoshop (yeah for windows PC) How to live without sketch & rock with Photoshop (yeah for windows PC) By janzeteachesit Assigned to http://ift.tt/2x2Wjyj GRIST4 GR How to live without sketch & rock with Photoshop (yeah for windows PC) Label: grist Date: August 16, 2017 at 10:42AM Labeled: August 16, 2017 at 10:46AM via GitHub http://ift.tt/2uQ2UeP August 16, 2017 at 10:51AM via GitHub http://ift.tt/2uQ2UeP [100-days-of-writing] Going Material with Gravit Designer Gravit Designer Medium Going Material with Gravit Designer Gravit Designer Medium By janzeteachesit Assigned to http://ift.tt/2vJj2Aa GRIST4 GR Going Material with Gravit Designer – Gravit Designer – Medium Label: grist Date: August 16, 2017 at 10:45AM Labeled: August 16, 2017 at 10:46AM via GitHub http://ift.tt/2wfUjG3 August 16, 2017 at 10:51AM via GitHub http://ift.tt/2wfUjG3 [100-days-of-code] A Dozen Times Artificial Intelligence Startled The World A Dozen Times Artificial Intelligence Startled The World By janzeteachesit Assigned to http://ift.tt/2wfjo0l aimlnn A Dozen Times Artificial Intelligence Startled The World Label: AI-NN-ML Date: August 16, 2017 at 11:59AM Labeled: August 16, 2017 at 12:01PM via GitHub http://ift.tt/2wglZdE August 16, 2017 at 12:01PM via GitHub http://ift.tt/2wglZdE [100-days-of-code] Own Your Bot Archie.AI Medium Own Your Bot Archie.AI Medium By janzeteachesit Assigned to http://ift.tt/2pVZt7Q aimlnn Own Your Bot – Archie.AI – Medium Label: AI-NN-ML Date: August 16, 2017 at 12:01PM Labeled: August 16, 2017 at 12:06PM via GitHub http://ift.tt/2v2PUlp August 16, 2017 at 12:11PM via GitHub http://ift.tt/2v2PUlp [100-days-of-writing] (12) Stanford Webinar - Design Your Life: Part I: Reframe Your Passion - YouTube (12) Stanford Webinar - Design Your Life: Part I: Reframe Your Passion - YouTube By janzeteachesit Assigned to https://www.youtube.com/watch?v=8bYIQDlWj34+ GRIST4 Writing (12) Stanford Webinar - Design Your Life: Part I: Reframe Your Passion - YouTube Label: grist Date: August 16, 2017 at 03:59PM Labeled: August 16, 2017 at 04:01PM via GitHub http://ift.tt/2x5BwKM August 16, 2017 at 04:06PM via GitHub http://ift.tt/2x5BwKM [100-days-of-writing] (12) Stanford Webinar - Design Your Life: Part II: Prototypes for Personal Success - YouTube (12) Stanford Webinar - Design Your Life: Part II: Prototypes for Personal Success - YouTube By janzeteachesit Assigned to https://www.youtube.com/watch?v=qOwAkE0Sdbg GRIST4 Writing (12) Stanford Webinar - Design Your Life: Part II: Prototypes for Personal Success - YouTube Label: grist Date: August 16, 2017 at 04:00PM Labeled: August 16, 2017 at 04:01PM via GitHub http://ift.tt/2wbzvjH August 16, 2017 at 04:06PM via GitHub http://ift.tt/2wbzvjH [100-days-of-writing] Designing Your Life Stanford Life Design Lab Designing Your Life Stanford Life Design Lab By janzeteachesit Assigned to http://ift.tt/2fMJvZW GRIST4 Writing Designing Your Life — Stanford Life Design Lab Label: grist Date: August 16, 2017 at 04:01PM Labeled: August 16, 2017 at 04:06PM via GitHub http://ift.tt/2v2QXSt August 16, 2017 at 04:11PM via GitHub http://ift.tt/2v2QXSt [100-days-of-writing] Applied Design Skills and Technologies_Introduction | Building Student Success - BC's New Curriculum Applied Design Skills and Technologies_Introduction | Building Student Success - BC's New Curriculum By janzeteachesit Assigned to Applied Design, Skills and Technologies_Introduction | Building Student Success - BC's New Curriculum http://ift.tt/2uRbhXy GRIST4 DH DT ADST Applied Design, Skills and Technologies Introduction The ability to design and make, acquire skills as needed, and apply technologies is important in the world today and a key aspect of educating citizens for the future. The Applied Skills learning area has been re-envisioned as a K–12 program and renamed. The new Applied Design, Skills, and Technologies (ADST) curriculum is an experiential, hands-on program of learning through design and creation that includes skills and concepts from traditional and First Peoples practice; from the existing disciplines of Business Education, Home Economics, Information Technology, and Technology Education; and from new and emerging fields. It envisions a K–12 continuum fostering the development of the skills and knowledge that will allow students to create practical and innovative responses to everyday needs and problems. K–5 Foundations Students in Kindergarten to Grade 5 will have opportunities to develop foundations in Applied Design, Skills, and Technologies within the context of existing curricula. The curriculum provides Big Ideas and Curricular Competencies for Kindergarten but does not include any Content learning standards. The intent and requirement is that teachers use the learning standards for Curricular Competencies from Applied Design, Skills, and Technologies K–5 with grade-level content from other subject areas to provide students with cross-curricular opportunities to develop foundational mindsets and skills in design thinking and making. In the early years, students will be given opportunities to develop foundational skills in Applied Design, Skills, and Technologies through exploratory and purposeful play. As they get older and develop an interest in knowing how things work and making things that work, they will have opportunities to develop foundational skills in activities that have a practical and real-life focus. Students in Kindergarten to Grade 5 will develop the skills for design thinking and a maker mindset in cross-curricular contexts that they will bring to future explorations in Applied Design, Skills, and Technologies. Grades 6–9 Explorations Students in Grades 6 to 9 will have opportunities to explore specific areas of Applied Design, Skills, and Technologies while continuing to build their design thinking and foundational skills. The Applied Design, Skills, and Technologies 6–9 curriculum encompasses content from the four existing Applied Design, Skills, and Technologies disciplines (Business Education, Home Economics, Information and Communications Technology, and Technology Education) and new and emerging fields, and provide opportunities for choice, modularization, and a variety of delivery options. This approach provides provincial recognition of the variety and scope of existing locally developed middle years programs and a template for the development of additional local programs. As a result of their explorations in Grades 6 to 9, students may begin to show particular interest in and aptitude for specific Applied Design, Skills, and Technologies areas and set more specialized learning goals. Grades 10–12 Specializations Students in Grades 10 to 12 will have opportunities to specialize in a specific area or to continue to explore their interests in more than one area. The specialization might be within the disciplines Business Education, Culinary Arts, Home Economics, Information and Communications Technology, Media Arts, Technology Education, or Tourism, across these and other areas, or in emerging disciplines. The specialization might be driven by students’ desire for practical skills in a particular area, their interests and passions, or their plans for post-secondary education or careers. This will allow students in Grades 10 to 12, who are becoming increasingly independent, to personalize their learning by pursuing interests that are relevant to them. Features of the ADST curriculum There is a renewed focus on designing and making, the acquisition of skills, and the application of technologies The ADST curriculum is now a provincial curriculum for K–12 that can be delivered in different ways at different grade levels There is a common set of curricular competencies for all of the ADST (formerly Applied Skills) curricula that can also be used as a template for locally developed options now and in the future Design of the ADST curriculum Big Ideas The Big Ideas of the ADST curriculum are derived from the Curricular Competencies. The Big Ideas are intended to capture a progression of learning in applying design processes, skills, and technologies, as shown in the chart below. K–3 4–5 6–8 9–10 11–12 Applied Design Designs grow out of natural curiosity. Designs can be improved with prototyping and testing. Design can be responsive to identified needs. Social, ethical, and sustainability considerations impact design. Products can be designed for lifecycle. Applied Skills Skills can be developed through play. Skills are developed through practice, effort, and action. Complex tasks require the acquisition of additional skills. Complex tasks require the sequencing of skills. Personal design interests require the evaluation and refinement of skills. Applied Technologies Technologies are tools that extend human capabilities. The choice of technology and tools depends on the task. Complex tasks may require multiple tools and technologies. Complex tasks require different technologies and tools at different stages. Tools and technologies can be adapted for specific purposes. Curricular Competencies The Curricular Competencies are organized under three headings: Applied Design Applied Skills Applied Technologies The Curricular Competencies under Applied Design are further organized under subheadings that reflect general stages of designing and making. For Grades 4 to 12, these are: Understanding context Defining Ideating Prototyping Testing Making Sharing Elaborations for the Curricular Competencies provide definitions for clarity. The subheadings for Kindergarten to Grade 3 are simplified in order to be developmentally appropriate; for example, young children do not prototype, test, and make as discernibly separate stages when they are designing and making through exploratory and purposeful play. The three stages of Applied Design that are identified for Kindergarten to Grade 3 encompass all of the stages of designing and making that are identified at higher grade levels, but in a naturalistic and developmentally appropriate way. They are: Ideating Making Sharing An important feature of the ADST curriculum is that the Curricular Competencies do not change for every grade. They remain the same for Kindergarten to Grade 3, and then there are sets for Grades 4 to 5, 6 to 8, 9 to 10, and 11 to 12. Even then, the changes are quite incremental. This aspect of the curricular design is intended to provide a consistent focus for both students and teachers on the “doing” aspect of the curriculum and to encourage student metacognition. Students use and develop the core competencies of creative and critical thinking, communication, and the personal and social competencies through the Curricular Competencies of ADST. The chart below gives some examples (but not an exhaustive list). K–3 4–5 6–8 9–10 11–12 Thinking Generate ideas from their experiences and interests Add to others’ ideas Generate potential ideas and add to others’ ideas Screen ideas against the objective and constraints Generate potential ideas and add to others’ ideas Screen ideas against criteria and constraints Take creative risks in generating ideas and add to others’ ideas in ways that enhance them Critically analyze and prioritize competing factors, including social, ethical, and sustainability considerations, to meet community needs for preferred futures Take creative risks to identify gaps to explore as design space Critically analyze how competing social, ethical, and sustainability considerations impact designed solutions to meet global needs for preferred futures Communication Demonstrate their product, tell the story of designing and making their product Demonstrate their product and describe their process Demonstrate their product and describe their process, using appropriate terminology and providing reasons for their selected solution and modifications Demonstrate their product to potential users, providing a rationale for the selected solution, modifications, and procedures, using appropriate terminology Share their progress while making to increase feedback, collaboration, and, if applicable, marketing Personal and Social Explain how their product contributes to the individual, family, community, and/or environment Determine whether their product met the objective and contributes to the individual, family, community, and/or environment Identify the personal, social, and environmental impacts, including unintended negative consequences, of the choices they make about technology use Evaluate the personal, social, and environmental impacts, including unintended negative consequences, of the choices they make about technology use Analyze the role and impact of technologies in societal change, and the personal, social, and environmental impacts, including unintended negative consequences, of their choices of technology use Content The ADST curriculum does not specify any Content learning standards for Kindergarten through Grade 5. The intent is for teachers to use the Curricular Competencies from ADST K–5 with grade-level content from other areas of learning to provide students with cross-curricular opportunities to develop foundational mindsets and skills in design thinking and making. For example, students might design and build something based on the Content learning standards in the Science or Social Studies curriculum. For Grades 6 to 12, the Content is concept-based and includes learning standards for the four existing Applied Skills disciplines (Business Education, Home Economics, Information Technology, and Technology Education) and for new and emerging fields such as Media Arts. Content learning standards are stated as topics. This creates the space for students to personalize their learning by making choices about what they design and make and the depth and breadth of their learning on a particular topic based on their own interests and passions. The generality of the Content learning standards also facilitates inclusion by allowing the teacher or the student to adjust depth and breadth to match abilities. Grades 6 to 9 are intended as exploration years. For Grades 6 and 7, this is a new provincial curriculum; for Grades 8 and 9, it is a redesigned curriculum. The curriculum provides one set of Content options for Grades 6 and 7 that are intended to be short modules that may be offered in rotation. Over the two years, students may be exposed to several of these and perhaps other locally developed options that also use the Curricular Competencies of ADST with locally developed content. This approach provides provincial recognition of the variety and scope of existing locally developed middle years programs and a template for the development of additional local programs. There are separate sets of Content options for Grade 8 and Grade 9. These may be offered as modular rotations of varying length, as is common for Grade 8 now, or as full-year courses, as is often the case in Grade 9 now. The Content elaborations are non-mandatory curricular supports that suggest possible depth and breadth for teaching concepts. The Content options for Grade 10, 11, and 12 have been significantly redesigned and reorganized to build on the new program in Kindergarten to Grade 7 and the redesigned program in Grades 8 and 9, to maintain a focus on designing and making, and to reflect developments in the domain. Some courses have been combined, some have been eliminated, some have been renamed, and some have been moved to and from other learning areas. Economics 12 has been moved to the Social Studies learning area; new Computer Science 11 and 12 courses have been developed in the Mathematics learning area; and Media Arts 10–12, with a focus on the application of digital technologies, has been moved to the Applied Design, Skills, and Technologies learning area. These elective courses are intended to offer students opportunities to continue exploring their interests or to specialize in an area of interest. Considerations for delivering ADST At all grade levels The focus on hands-on designing and making, acquisition and honing of skills, and choosing and applying technologies requires a high degree of student choice, although there may still be a place for common activities for specific purposes — for example, to introduce new skills or equipment, to communicate safety procedures, or to explicitly focus on one aspect of the design process The curriculum is inclusive of modern and traditional First Peoples design, skills, and technologies. Students should have opportunities to learn from local First Peoples. This will require an understanding by both students and teachers of appropriation issues and that some knowledge is considered sacred Kindergarten to Grade 5 Students can be given opportunities to develop foundational skills in ADST through exploratory and purposeful play, and through designing and making activities related to the content in other areas of learning. This is already a normal practice in K–5 classrooms and will not require additional time or resources A single set of Curricular Competencies for Kindergarten to Grade 3 provides common language and continuity for the first four years Another set of Curricular Competencies for Grades 4 and 5, with more stages delineated for Applied Design, encourages students to take a more purposeful approach to designing and making Grades 6 and 7 The curriculum is designed to be modular to allow for choice and a variety of delivery models depending on school configuration and student interest The requirement will be that students experience a minimum of three modules of ADST in each of Grades 6 and 7. Schools may choose from among the modules provided in the provincial curriculum or develop new modules that use the Curricular Competencies of ADST 6–7 with locally developed content. Locally developed modules can be offered in addition to, or instead of, the modules in the provincial curriculum Schools that currently have an exploratory rotation may choose to continue with that delivery model for ADST. Schools that do not currently have an exploratory rotation may wish to develop one, or to teach ADST modules in an integrated cross-curricular way with other areas of learning Grades 8 and 9 Schools will be able to accommodate the redesigned ADST curriculum within their current delivery models The curriculum may be offered as modular rotations of varying length, as is common for Grade 8 now, or as full courses, as is often the case in Grade 9 now There are more Content learning standards for Grade 9, as schools often offer these as full courses Schools are expected to offer students the equivalent of a “full-year” program in ADST. This can be made up of one or more modules Schools may choose from among the modules provided in the provincial curriculum or develop new modules that use the Curricular Competencies of ADST 8 or 9 with locally developed content. Locally developed modules can be offered in addition to, or instead of, the modules in the provincial curriculum As the new ADST curriculum has explorations starting in Grade 6, schools may wish to offer students more choice in Grades 8 and 9 than was offered previously Grades 10 to 12 Schools will be able to provide a variety of elective courses in Applied Design, Skills, and Technologies to meet student interests Current Board/Authority Authorized (BAA) courses remain approved. School and districts interested in revising BAA courses or developing new ones are encouraged to use the Curricular Competencies that are common for all Applied Design, Skills, and Technologies courses. Last updated: June 27, 2016 Applied Design, Skills and Technologies_Introduction | Building Student Success - BC's New Curriculum Label: grist Date: August 16, 2017 at 05:53PM Labeled: August 16, 2017 at 05:56PM via GitHub http://ift.tt/2vKqDOM August 16, 2017 at 06:01PM via GitHub http://ift.tt/2vKqDOM [100-days-of-writing] Applied Design Skills and Technologies_Goals and Rationale | Building Student Success - BC's New Curriculum Applied Design Skills and Technologies_Goals and Rationale | Building Student Success - BC's New Curriculum By janzeteachesit Assigned to Applied Design, Skills and Technologies_Goals and Rationale | Building Student Success - BC's New Curriculum http://ift.tt/2fMG4lP GRIST4 ADST DH DT Applied Design, Skills and Technologies Goals and Rationale Rationale The Applied Design, Skills, and Technologies curriculum builds on students’ natural curiosity, inventiveness, and desire to create and work in practical ways. It harnesses the power of learning by doing, and provides the challenging fun that inspires students to dig deeper, work with big ideas, and adapt to a changing world. It provides learning opportunities through which students can discover their interests in practical and purposeful ways. Applied Design, Skills, and Technologies includes skills and concepts from the disciplines of Business Education, Home Economics, Information Technology, and Technology Education, as well as rich opportunities for cross-curricular work and space for new and emerging areas, such as Media Arts. Business Education builds an understanding of business skills and concepts in the context of current technology, ethical standards, and an increasingly global economy, empowering students with economic, financial, consumer, and communication skills for lifelong participation in local and global contexts. Home Economics focuses on fundamental needs and practical concerns of individuals and families in a changing and challenging world, It integrates knowledge, processes, and practical skills from multiple areas, including foods, textiles, and family studies, and provides opportunities for creative applications and critical examination from global citizenship perspectives. Information Technology encompasses evolving processes, systems, and tools for creating, storing, retrieving, and modifying information. As students design, share, and adapt knowledge in critical, ethical, purposeful, and innovative ways, they gain perspective on the long-term implications of life in a digital, connected world and develop literacies to responsibly take ownership of such technologies to augment learning and benefit society. Technology Education involves students in the design and fabrication of objects using a variety of materials, methods, technologies, and tools in order to develop their ability to shape and change the physical world to meet human needs. It may include woodwork, metalwork, electronics, drafting, automotive technology, power mechanics, and robotics. Using creative and critical thinking, students can work collaboratively to problem find and solve by exploring materials, using tools and equipment, designing and building, developing processes, and communicating the merits of their work. They can learn to critically evaluate the appropriateness of the products they develop and those developed by others. As they explore the role of culture, including local Aboriginal cultures, in the development of practical and innovative solutions to human needs, they can develop a sense of personal and social responsibility for the products they use and develop, and their effects on individuals, communities, and the environment, now and in the future. Learning in Applied Design, Skills, and Technologies provides firm foundations for lifelong learning and, for some, specialized study and a diverse range of careers. It develops well-rounded citizens who are informed creators and consumers. It fosters the development of future problem solvers, innovators, and skilled tradespeople who can contribute to solving problems not yet anticipated with processes and technologies not yet imagined in order to improve their lives, the lives of others, and the environment. Goals The BC Applied Design, Skills, and Technologies curriculum contributes to students’ development as educated citizens through the achievement of the following goals. Students are expected to acquire practical skills and knowledge that they can use to bring their ideas from conception to fruition develop a sense of efficacy and personal agency about their ability to participate as inventors, innovators, and agents of change to solve practical problems in a rapidly changing world explore how the values and beliefs of cultures, including local Aboriginal cultures, affect the development of products, services, and processes understand the environmental implications of the products they are designing and constructing investigate and actively explore a variety of areas, including aspects of Business Education, Home Economics, Information Technology, and Technology Education, and new and emerging fields, in order to develop practical hands-on skills and make informed decisions about pursuing specialized interests for personal enjoyment or careers develop a lifelong interest in designing, making, and evaluating products, services, and processes, and contributing through informed citizenship, volunteer work, or their careers, to finding and solving practical problems Last updated: June 29, 2016 Applied Design, Skills and Technologies_Goals and Rationale | Building Student Success - BC's New Curriculum Label: grist Date: August 16, 2017 at 05:58PM Labeled: August 16, 2017 at 06:01PM via GitHub http://ift.tt/2v3c1bG August 16, 2017 at 06:06PM via GitHub http://ift.tt/2v3c1bG [100-days-of-writing] Applied Design Skills and Technologies_What's New | Building Student Success - BC's New Curriculum Applied Design Skills and Technologies_What's New | Building Student Success - BC's New Curriculum By janzeteachesit Assigned to Applied Design, Skills, and Technologies_What's New | Building Student Success - BC's New Curriculum http://ift.tt/2w3uMQJ GRIST4 DT DH ADST Applied Design, Skills, and Technologies What's New? As part of the current work of transforming the BC provincial curriculum, the intention is to bring applied learning to all curricula. This is being done in two ways. Firstly, individual areas of learning are being revised to place greater emphasis on curricular competencies, the doing part of the curricula. Secondly, the Applied Skills curricula are being re-envisioned as a K–12 program. The name “Applied Design, Skills, and Technologies” replaces “Applied Skills.” The new name is intended to better capture the scope and nature of the domain. Design involves the ability to combine an empathetic understanding of the context of a problem, creativity in the generation of insights and solutions, and critical thinking to analyze and fit solutions to the context. To move from design to final product or service requires skills and technology. Skills are the abilities gained through competence to do something and to do it increasingly well. Technologies are tools that enable human capabilities, and range from blunt-nosed scissors, to tablets, to drill presses, depending on the grade level, available resources, and facilities. In Applied Design, Skills, and Technologies (ADST), students will grow in their ability to use design thinking to gain an understanding of how to apply their skills to problem finding and solving, using appropriate technologies. Kindergarten to Grade 5 What's the same? Teachers will continue to provide students with opportunities to design and make things in the context of exploratory and purposeful play and learning in various areas of learning. What's new? This is a new provincial curriculum for Kindergarten to Grade 5. The K–5 curriculum consists only of Curricular Competencies and Big Ideas. These will provide a common focus and a common language for the designing and making activities that are currently a normal part of students’ learning experiences in K–5 classrooms. There is one set of Curricular Competencies for Kindergarten to Grade 3, with simplified design stages that are naturalistic and developmentally appropriate. There is another set of Curricular Competencies for Grades 4 and 5 with more detailed design stages, to reflect a developmental progression and encourage more purposeful designing and making. This is a simplified curriculum that has no Content learning standards for Kindergarten to Grade 5. The intent and requirement is that teachers use the learning standards for Curricular Competencies from ADST K–5 with gradelevel content from other areas of learning to provide students with crosscurricular opportunities to develop foundational mindsets and skills in design thinking and making. Grades 6 and 7 What's the same? Middle schools or other schools that currently offer a rotation of modular explorations will be able to accommodate the redesigned ADST curriculum within their current delivery models. What's new? This is a new provincial curriculum for Grades 6 and 7. The curriculum is modular in design to allow for choice and a variety of delivery models, depending on the school configuration and student interest. The curriculum is identical for the two grades. The intent is that students will experience at least three Content modules in each grade. The Curricular Competencies and Big Ideas are identical for all Content modules. Schools may choose from among the modules provided in the provincial curriculum or develop new modules that use the Curricular Competencies of ADST 6–7 with locally developed content. Locally developed modules can be offered in addition to, or instead of, the modules in the provincial curriculum. The curriculum has been developed to accommodate delivery in a variety of settings. Schools that currently have an exploratory rotation may choose to continue with that delivery model for ADST. Schools that do not currently have an exploratory rotation may wish to develop one, or to teach ADST modules in an integrated cross-curricular way with other areas of learning. Grades 8 and 9 What's the same? There are provincial curricula in Business Education, Home Economics, Information Technology, and Technology Education. Schools will continue to encourage exploration, as well as offering students choices. Schools will be able to accommodate the redesigned ADST curriculum within their current delivery models. What's new? The Curricular Competencies and Big Ideas for Grade 8 are the same as for Grade 7. The Curricular Competencies and Big Ideas for Grade 9 are continued for Grade 10. There are separate sets of Content options for Grade 8 and Grade 9. These These may be offered as modular rotations of varying length, as is common for Grade 8 now, or as full-year courses, as is often the case in Grade 9 now. The Curricular Competencies and Big Ideas are the same for all of the Content modules in a grade. Schools are expected to offer students the equivalent of a “full-year” program in ADST. This can be made up of one or more modules. Schools may choose from among the modules provided in the provincial curriculum or develop new modules that use the Curricular Competencies of ADST 8 or 9 with locally developed content. Locally developed modules can be offered in addition to, or instead of, the modules in the provincial curriculum. As the new ADST curriculum has explorations starting in Grade 6, schools may wish to offer students more choice in Grades 8 and 9 than was offered previously. Grades 10 to 12 What’s the same? There is provincial curriculum in the areas of Business Education, Culinary Arts, Home Economics, Information Technology, Media Arts, and Technology Education and related disciplines. Students in Grades 10 to 12 have opportunities to specialize in a specific area or to continue to explore their interests in more than one area. The specialization might be driven by students’ desire for practical skills in a particular area, their interests and passions, or their plans for post-secondary education or careers. School districts are able to continue to offer and develop local courses to augment provincial curricular offerings. Board/Authority Authorized (BAA) courses remain in effect. Skills Exploration courses and Industry Training Authority (ITA) curricula have not been revised and remain in effect. What’s new? The provincial curricula for Grades 10 to 12 have been reconfigured to match the intent and directions of ADST and to build on the explorations in Grades 6 to 9, and redesigned to match the current curricular design. The Curricular Competencies and Big Ideas for Grade 9 have also been used for all Grade 10 ADST curricula, for consistency and continuity. One set of Curricular Competencies and Big Ideas has been developed for Grades 11 and 12 and used for all Grade 11 and 12 ADST curricula. In all ADST curricula there is greater emphasis on student choice about what products to design and make. Content learning standards identify concepts and topics. This creates the space for students to personalize their learning by making choices about what they design and make, and the depth and breadth of their learning on a particular concept, based on their own interests and passions. The generality of the Content learning standards also facilitates inclusion by allowing the teacher or the student to adjust depth and breadth to match abilities. The Content options for Grades 10, 11, and 12 have been significantly redesigned and reorganized to build on the new program in K-7 and the redesigned program in Grades 8 and 9, to maintain a focus on designing and making, and to reflect enrolment numbers, developments in the domain, and policy considerations. Some courses have been combined, some have been eliminated, some have been renamed, and some have been moved to and from other learning areas. In Business Education, courses have been combined and reorganized, Economics 12 has been moved to the Social Studies learning area, and a new E-Commerce 12 course has been developed. Cafeteria 11 and 12 have been renamed Culinary Arts 11 and 12, and a new Culinary Arts 10 course has been developed to allow earlier specialization. In Home Economics, curricular content from Human Services 11 and 12 has been combined with content from Family Studies 11 and 12 to create new courses called Child Development and Caregiving 12 and Housing and Living Environments 12. Information and Communication Technology courses have been significantly updated and two new courses, Computer Science 11 and 12, have been developed as Mathematics courses with input from post-secondary institutions. Media Arts 10-12, with a focus on the application of digital technologies, has been moved to the Applied Design, Skills and Technologies learning area. Technology Education courses have been significantly reorganized. Some courses have been combined, and some courses have been eliminated as a result of policy development considerations (e.g., Technology Education 11A, B, C, and D courses). New courses, such as Coding for Manufacturing 12, Mechatronics 12, and ROVs and Drones 12, have been added to reflect developments in the discipline. The chart below shows current provincial Applied Skills curricula and the proposed new ADST 10-12 curricula. Current Applied Skills 10-12 curricula Applied Design, Skills, and Technologies 10-12 curricula Business Education Business Education 10: General Business Education 10: Communication Business Education 10: Entrepreneurship Entrepreneurship and Marketing 10 Business Education 10: Marketing Business Education 10: Finance and Economics Accounting 11 Accounting 11 Basic Computer Applications 11 Entrepreneurship 11 Marketing 11 Marketing and Promotion 11 Accounting 12 Accounting 12 Business Information Management 12 Data Management 12 Economics 12 Has been moved to Social Studies Financial Accounting 12 Financial Accounting 12 Management Innovation 12 Marketing 12 E-Commerce 12 Culinary Arts Culinary Arts 10 Cafeteria 11 Culinary Arts 11 Cafeteria 12 Culinary Arts 12 Home Economics Home Economics 10: General Home Economics 10: Foods and Nutrition Food Studies 10 Home Economics 10: Textiles Textiles 10 Home Economics 10: Family Studies Families and Society 10 Food Studies 11 Foods Studies 11 Textile Studies 11 Textiles 11 Family Studies 11 Interpersonal and Family Relationships 11 Human Services 11 Food Studies 12 Food Studies 12 Textile Studies 12 Textiles 12 Family Studies 12 Child Development and Caregiving 12 Housing and Living Environments 12 Human Services 12 Information and Communications Technology Information Technology 10 Web Development 10 Computer Studies 10 Information and Communications Technology: Applied Digital Communications 11 Digital Communications 11 Information and Communications Technology: Computer Information Systems 11 Computer Information Systems 11 Information and Communications Technology: Computer Programming 11 Computer Programming 11 Information and Communications Technology: Digital Media Development 11 Digital Media Development 12 Information and Communications Technology: Applied Digital Communications 12 Information and Communications Technology: Computer Information Systems 12 Computer Information Systems 12 Information and Communications Technology: Computer Programming 12 Computer Programming 12 Information and Communications Technology: Digital Media Development 12 Media Arts Visual Arts: Media Arts 10 Media Arts 10 Visual Arts: Media Arts 11 Media Arts 11 Visual Arts: Media Arts 12 Media Arts 12 Technology Education Technology Education 10: General Technology Education 10: Drafting and Design Drafting 10 Technology Education 10: Electronics Electronics and Robotics 10 Technology Education 10: Mechanics Power Mechanics 10 Technology Education 10: Metalwork Metalwork 10 Technology Education 10: Woodwork Woodwork 10 Automotive Technology 11 Automotive Technology 11 Carpentry and Joinery 11 Woodwork 11 Drafting and Design 11 Drafting 11 Electronics 11 Electronics 11 Robotics 11 Metal Fabrication and Machining 11 Metalwork 11 Automotive Technology 12 Automotive Technology 12 Automotive Technology 12: Automotive Electricity and Electronics Automotive Technology 12: Body Repair and Finish Automotive Technology 12: Engine and Drive Train Automotive Engine and Drivetrain 12 Carpentry and Joinery 12 Woodwork 12 Carpentry and Joinery 12: Cabinet Construction Carpentry and Joinery 12: CNC Wood Processes Carpentry and Joinery 12: Residential Construction Carpentry and Joinery 12: Woodcraft Products Furniture and Cabinetry 12 Drafting and Design 12 Drafting 12 Coding for Manufacturing 12 Drafting and Design 12: Advanced Design Drafting and Design 12: Architecture and Habitat Design Drafting and Design 12: Engineering and Mechanical Drafting Drafting and Design 12: Technical Visualization Electronics 12 Electronics 12 Electronics 12: Analog Systems Electronics 12: Digital Systems Electronics 12: Robotics Robotics 12 Mechatronics 12 ROVs and Drones 12 Metalwork 12 Metal Fabrication and Machining 12: Advanced Fabrication Metal Fabrication and Machining 12: Advanced Machining Machining and Welding 12 Metal Fabrication and Machining 12: Advanced Welding Metal Fabrication and Machining 12: Art Metal and Jewellery Art Metal and Jewellery 12 Metal Fabrication and Machining 12: CNC Processes Metal Fabrication and Machining 12: Forging and Foundry Metal Fabrication and Machining 12: Sheet Metal Tourism Tourism 11 Tourism 11 Tourism 12 Tourism 12 Other Automotive Service Technician 1 These curricula have not been revised and are still in place. Carpentry Level 1 Professional Cook 1 Applied Skills 11 Skills Exploration 10 Skills Exploration 11 Skills Exploration 12 Last updated: August 12, 2016 Applied Design, Skills, and Technologies_What's New | Building Student Success - BC's New Curriculum Label: grist Date: August 16, 2017 at 06:07PM Labeled: August 16, 2017 at 06:11PM via GitHub http://ift.tt/2uKbWy5 August 16, 2017 at 06:16PM via GitHub http://ift.tt/2uKbWy5 [100-days-of-writing] Curriculum Overview | Building Student Success - BC's New Curriculum Curriculum Overview | Building Student Success - BC's New Curriculum By janzeteachesit Assigned to Curriculum Overview | Building Student Success - BC's New Curriculum http://ift.tt/2vKdrJR GRIST4 DT DH ADST Curriculum Overview Education for the 21st Century British Columbia has one of the best education systems in the world. Teachers are skilled, facilities are sound, and students are performing near the top of international assessments. Yet it is an education system modelled on the very different circumstances of an earlier century — when change was much more gradual than it is today. Conditions in the world are changing greatly and rapidly. Today’s students will grow into a world that is very different from and more connected than that of generations before. To maintain high achievement, British Columbia must transform its education system to one that better engages students in their own learning and fosters the skills and competencies students will need to succeed. One focus for this transformation is a curriculum that enables and supports increasingly personalized learning, through quality teaching and learning, flexibility and choice, and high standards. To guide the transformation, the province conducted reviews of trends in national and international jurisdictions and invited authorities on curriculum and assessment design to advise on proposed changes. In addition, as part of the work on core competencies, several commissioned researchers summarized the literature in critical thinking, creative thinking, and social and personal responsibility. Student Success Through Curriculum Transformation Today we live in a state of constant change. It is a technology-rich world, where communication is instant and information is immediately accessible. The way we interact with each other personally, socially, and at work has changed forever. Knowledge is growing at exponential rates in many domains, creating new information and possibilities. This is the world our students are entering. British Columbia’s curriculum is being redesigned to respond to this demanding world our students are entering, To develop new models, the Ministry consulted with experts in the field. They suggested that to prepare students for the future, the curriculum must be learner-centred and flexible and maintain a focus on literacy and numeracy, while supporting deeper learning through concept- based and competency-driven approaches. The redesign of curriculum maintains a focus on sound foundations of literacy and numeracy while supporting the development of citizens who are competent thinkers and communicators, and who are personally and socially competent in all areas of their lives. British Columbia’s redesigned curriculum honours the ways in which students think, learn, and grow, and prepares them for a successful lifetime of learning where ongoing change is constant. The Educated Citizen “A quality education system assists in the development of human potential and improves the well-being of each individual person in British Columbia society.” These words, along with the description of the educated citizen, became educational policy following the report of the Royal Commission on Education (known as the Sullivan Commission), in 1988. They continue to have meaning today. Achieving British Columbia’s social and economic goals requires well-educated citizens who are able to think critically and creatively and adapt to change. Progress toward the achievement of these goals also depends on the province having citizens who accept the tolerant and multifaceted nature of Canadian society and who are motivated to participate actively in our democratic institutions. To ensure the development of an educated society, government is responsible for providing all youth with the opportunity to obtain high-quality education. To that end, British Columbia’s schools assist in developing citizens who: Are thoughtful and able to learn and to think critically, and can communicate Information from a broad knowledge base Are creative, flexible, and self-motivated and have a positive self-image Are capable of making independent decisions Are skilled and able to contribute to society generally, including the world of work Are productive, gain satisfaction through achievement, and strive for physical well-being Are co-operative, principled, and respectful of others regardless of differences Are aware of the rights of the individual and are prepared to exercise the responsibilities of the individual within the family, the community, Canada, and the world The redesigned curriculum captures these qualities, both implicitly and explicitly, in the core and curricular competencies. The concept of the educated citizen will continue to guide educational decisions for years to come, ensuring that students across the province are supported and that future generations of British Columbians are empowered by their school experience. Personalized learning Personalized learning acknowledges that not all students learn successfully at the same rate, in the same learning environment, and in the same ways. It involves the provision of high-quality and engaging learning opportunities that meet the diverse needs of all students. Schools may provide flexible timing and pacing through a range of learning environments, with learning supports and services tailored to meet student needs. Personalized learning focuses on enhancing student engagement in learning and giving students choices — more of a say in what and how they learn — leading to lifelong, self-directed learning. Students and teachers develop learning plans to build on student’s interests, goals, and learning needs. Involving students in reflecting on their work and setting new goals based on their reflections allows them to take more control of their learning. Personalized learning also encompasses place-based learning, where learning experiences are adapted to the local environment or an individual context. Key features of redesigned curriculum At the heart of British Columbia’s redesigned curriculum are the Core Competencies, essential learning and literacy and numeracy foundations. All three features contribute to deeper learning. The Core Competencies Core Competencies underpin the curricular competencies in all areas of learning. They are directly related to the educated citizen and as such are what we value for all students in the system. Review the Core Competencies, including profiles and illustrations Essential learning The curriculum for each subject area includes the essential learning for students, which represent society’s aspirations for BC’s educated citizen. The redesigned curriculum develops around key content, concepts, skills and big ideas that foster the higher-order thinking demanded in today’s world. Literacy and numeracy foundations Literacy is the ability to understand, critically analyze, and create a variety of forms of communication, including oral, written, visual, digital, and multimedia, in order to accomplish one’s goals. Numeracy Is the ability to understand and apply mathematical concepts, processes, and skills to solve problems in a variety of contexts. Literacy and numeracy are fundamental to all learning. While they are commonly associated with language learning and mathematics, literacy and numeracy are applied in all areas of learning. Curriculum model All areas of learning are based on a “Know-Do-Understand” model to support a concept-based competency-driven approach to learning. Three elements, the Content (Know), Curricular Competencies (Do), and Big Ideas (Understand) all work together to support deeper learning. British Columbia’s curriculum design enables a personalized, flexible and innovative approach at all levels of the education system. All areas of learning have been redesigned using this model. Content (Know) The Content learning standards — the “Know” of the Know-Do-Understand model of learning — detail the essential topics and knowledge at each grade level. Curricular Competencies (Do) The Curricular Competencies are the skills, strategies, and processes that students develop over time. They reflect the “Do” in the Know-Do-Understand model of learning. While Curricular Competencies are more subject-specific, they are connected to the Core Competencies. Big Ideas (Understand) The Big Ideas consist of generalizations and principles and the key concepts important in an area of learning. They reflect the “Understand” component of the Know-Do-Understand model of learning. The big ideas represent what students will understand at the completion of the curriculum for their grade. They are intended to endure beyond a single grade and contribute to future understanding. Any of the elements may include elaborations. Elaborations are provided where necessary to clarify some words or statements and may include examples, key questions, definitions or be used to describe breadth and depth for content. Elaborations are presented as “mouse-over” links on the website. Concept-based, Competency-driven Curriculum British Columbia’s redesigned curriculum brings together two features that most educators agree are essential for 21st-century learning: a concept-based approach to learning and a focus on the development of competencies, to foster deeper, more transferable learning. These approaches complement each other because of their common focus on active engagement of students. Deeper learning is better achieved through “doing” than through passive listening or reading. Similarly, both concept-based learning and the development of competencies engage students in authentic tasks that connect learning to the real world. Concept-based learning A concept-based curriculum uses concepts to define standards of knowledge and skills associated with a given area of learning. It is focused on the key concepts, principles, and generalizations that are used to organize knowledge and solve problems within and across disciplines. A concept-based curriculum: Is built around higher-order standards and key ideas, allowing a more in-depth exploration of topics to gain deeper understanding Balances the study of factual information with the development of conceptual understanding and disciplinary skills Offers opportunities for the transfer of learning Is not a list of topics to cover in isolation from one another A concept-based curriculum allows for connections between big ideas — for example, through exploration of the concept of reoccurring patterns and comparison of how patterns appear in literature, geographical features, and the evolution of species. Competency-driven learning “Competency” and “competencies” are defined in different ways in different contexts. The terms have their own meanings when used by business and industry, where they generally refer to the skills needed to perform a given job. In the context of education, the terms refer to the ability of students to perform a task as expected within a specific discipline or area of learning. That ability represents a combination of skills, processes, behaviours, and habits of mind. Students are competent in an area of learning to the extent that they understand and can apply knowledge to new contexts. Competencies are often narrowly equated with skills, but in a 21st-century educational context, competencies represent a much broader and more adaptable achievement than a simple set of skills. The redesigned curriculum defines competencies at two levels: Core Competencies develop across the curriculum, and Curricular Competencies are explicit statements of what is expected at each grade level in each area of learning. Redesigned Curriculum In Action When planning, it is important to begin with a broad understanding of the curriculum being used. The rationale and goals provide the context for the area of learning and make clear its contribution to the development of educated citizens The rationale and goals provide a broad instructional and assessment context for the area of learning The introduction to each area of learning provides specifics about features, structure, and important considerations of the curriculum The curriculum for each area of learning is displayed in two ways—in HTML format on the website and in PDF or Word formats. The curriculum website will continue to evolve in ways that support planning for learning. At this point, several features are available such as: A search engine to allow teachers to search for key words or select key elements from specific grades or areas of learning The results of the search can be exported into a Word document for further manipulation PDF or Word versions of the curriculum can be printed Some resources for planning are included now and will be further expanded in the future This flexibility supports teachers to combine the learning standards in various ways. Teachers are encouraged to create courses, modules, thematic units or learning experiences that go beyond learning area borders to focus on students’ needs and interests or local contexts. The curriculum design and the website features provide the flexibility to serve the unique needs of classrooms, students, and teachers. Flexible learning environments Learning can take place anywhere, not just in classrooms. Many schools and teachers create learning environments that explore the use of time and space in creative ways. The integration of areas of learning and technology also have opened the door for teachers and schools to approach the use of time and space in creative ways — ways that adapt to the students’ needs and interests. Although the learning standards are described within areas of learning, there is no requirement for teachers to organize classrooms, schools or instruction in this manner. In effect, the Ministry of Education defines the “what” to teach but not the “how to organize the time, space or methods to teach it. The focus on personalization and the flexible structure of the curriculum support the configuration of combined grade classrooms. Classes of students of more than one grade provide opportunities for teachers to develop a mindset that sees all the students as a group of learners with a range of needs and interests. Multi-grade programs should find a comfortable fit with the curriculum. ICT-enabled learning environments Students need opportunities to develop the competencies required to use current and emerging technologies effectively in all aspects of their learning and life. Technology can facilitate collaboration between students, educators, parents, and classrooms while also providing schools with rich online resources. Today’s technology enables classrooms, communities, and experts around the world to share digitally in a learning experience, wherever they may be. Inquiry and question-based approaches Through demonstration of the core and curricular competencies, students are bound to form questions that provide teachers with insight into their thinking. Questions generated by both students and teachers are critical to encouraging a sense of wonder and curiosity among students. This dialogue can take place through many question-based approaches, including, but not limited to: Inquiry Project-based learning Problem-based learning Self-assessment Research skills Scientific methods Collaboration with community Learning can often be enriched through collaborations involving members of the community. Parents or guardians and others in the community may bring expertise and perspective from their own lives and experiences to enhance students’ learning. Teachers are encouraged to incorporate these experiences into their students’ learning when possible and appropriate. It is particularly helpful to co-operate and engage with experts from the community when learning about culture-specific contexts to avoid offence or misrepresentation or appropriation of culture. Cultural appropriation includes use of cultural motifs, themes, “voices,” images, knowledge, stories, songs, drama, and so on without permission or without appropriate context or in a way that may misrepresent the real experience of the people from whose culture they are drawn. Collaboration with community members exemplifies many of the First Peoples Principles of Learning and nurtures cross-generational and relational learning. When working with members of the community, teachers are encouraged to: Become familiar with school and board/authority policies for involving guest instructors in the classroom (e.g., reference checks) Arrange for a meeting to discuss appropriate learning expectations and to decide which areas of the curriculum are to be addressed Ensure that age-appropriate material is used Prepare students for the experience (e.g., discuss the expectations for process and etiquette, provide relevant background information) Determine the needs of the presenters (e.g., space, technology, materials) Debrief with students and guests Aboriginal Perspectives and Knowledge British Columbia has long had the goal of improving school success for all Aboriginal students. Achieving this goal will require that the voice of Aboriginal people be heard in all aspects of the education system; the presence of Aboriginal languages, cultures, and histories be increased in provincial curricula; and leadership and informed practice be provided. At the same time, Aboriginal perspectives and knowledge are a part of the historical and contemporary foundation of British Columbia and Canada. British Columbia’s education transformation therefore incorporates the Aboriginal voice and perspective by having Aboriginal expertise at all levels, ensuring that Aboriginal content is a part of the learning journey for all students, and ensuring that the best information guides the work. An important goal in integrating Aboriginal perspectives into curricula is to ensure that all learners have opportunities to understand and respect their own cultural heritage as well as that of others. Over the past decade, British Columbia’s curriculum has integrated Aboriginal content into specific courses. The redesigned curriculum builds on what has been learned and extends Aboriginal perspectives into the entire learning journey, rather than into specific courses or grade levels. This means that from Kindergarten to graduation, students will experience Aboriginal perspectives and knowledge as part of what they are learning. And because Aboriginal perspectives and knowledge are embedded in the curriculum, they will naturally influence the ways in which students will be assessed. The First Peoples Principles of Learning provided a crucial lens for teacher teams when drafting curricula, and all curriculum teams included Aboriginal representation. The teams put great effort into embedding Aboriginal knowledge and worldviews in curriculum in authentic and meaningful ways. Curriculum material was reviewed by Ministry staff as well as by Aboriginal teachers and other experts. References to Aboriginal perspectives and knowledge are both explicit and implicit in the redesigned curriculum and are evident in the rationale statements, goals, learning standards, and some of the elaborations. Rich instructional samples to inspire teaching and learning will be collected and shared online to provide examples of relevant teaching units and place-based learning. In all of the areas of learning, teachers are encouraged to teach in ways that respect the place in which the students are — to teach from within the school and its surrounding community. Program Considerations Valuing Diversity British Columbia’s schools include young people of varied backgrounds, interests, and abilities. The Kindergarten to grade 12 school system focuses on meeting the needs of all students. When selecting specific topics, activities, and resources to support the implementation of the curriculum, teachers are encouraged to ensure that these choices support inclusion, equity, and accessibility for all students. In particular, teachers should ensure that classroom instruction, assessment, and resources reflect sensitivity to diversity and incorporate positive role portrayals, relevant issues, and themes such as inclusion, respect, and acceptance. This includes diversity in family compositions and gender orientation. The school system strives to create and maintain conditions that foster success for all students. These conditions include: Equitable access to and equitable participation in quality education for all students School cultures that value diversity and respond to the diverse social and academic needs of individual students School cultures that promote understanding of others and respect for all School environments that are safe and welcoming Policies and practices that promote fair and equitable treatment Processes that give a voice to all members of the school community Honouring diversity within the school system is based on the principle that if our differences are acknowledged and utilized in a positive way, it is of benefit to the quality of our learning and working environments. More information is available at http://ift.tt/2w3eAPl. Supporting Diverse Learners BC educators strive to ensure that all learners are supported to participate in school, to develop their individual potential, and to acquire the knowledge, skills, and attitudes they need for a successful personal future and to contribute positively to society and to the economy. Curriculum used in British Columbia schools remains designed for the majority of students, with classroom teachers continually personalizing their instruction and assessment methods for students as appropriate. Government policy supports the principles of inclusion of all students. Students with special and/or ELL needs can achieve the prescribed learning standards through the strategic use of personalized instruction and assessment methods. Some students with special needs may require program adaptation or modification to facilitate their achievement of the learning standards in this curriculum. Adapted Programs An adapted program addresses the learning standards of the prescribed curriculum by providing accommodations to selected students. These accommodations may include alternative formats for resources, instructional strategies, and assessment procedures. Accommodations may also be made in areas such as skill sequence, pacing, methodology, materials, technology, equipment, services, and setting. Students on adapted programs are assessed using the learning standards and can receive full credit. Digital/audio texts or peer helper to assist with assigned readings Access to assistive tools/technology (e.g., word processor, calculator, text to speech/voice to text software, magnifier, FM system etc.) Alternative ways of demonstrating learning standards Graphic organizers/strategy lists to assist students Extended time to complete assignments or tests Support to develop and practice study skills; for example, in a learning assistance class Preteaching key vocabulary or concepts; multiple exposure to materials Working on select learning standards from different grade levels Modified programs A modified program has learning standards that are substantially different from the prescribed curriculum and specifically selected to meet the student’s special needs. A student on a modified program is assessed in relation to the goals and objectives established in the student’s IEP. The following are examples of strategies that may help students on modified programs: Specify personal support (by peers or educational assistants, for example) Set individualized goals that may consider learning standards but are developed to suit the student’s special needs Modify activities by providing parallel ones for students with special needs Inclusion British Columbia promotes an inclusive education system in which students with special needs are fully participating members of a community of learners. Inclusion describes the principle that all students are entitled to equitable access to learning, achievement, and the pursuit of excellence in all aspects of their educational programs. The practice of inclusion is not necessarily synonymous with full integration in regular classrooms, and goes beyond placement to include meaningful participation and the promotion of interaction with others. Placement A school board must ensure that a principal offers to consult with a parent or guardian of a child who has special needs regarding the student’s placement in an educational program. A school board must provide a student who has special needs with an educational program in a classroom where the student is integrated with other students who do not have special needs, unless the educational needs of the student with special needs or other students indicate that the educational program for the student with special needs should be provided otherwise. The emphasis on educating students with special needs in neighbourhood school classrooms with their age and grade peers, however, does not preclude the appropriate use of learning assistance rooms, self-contained classes, community-based programs, or specialized settings. Students with special needs may be placed in settings other than a neighbourhood school classroom with age and grade peers. This should only be done when the school board has made all reasonable efforts to integrate the student, and it is clear that a combination of education in such classes and supplementary support cannot meet the student’s educational or social needs, or when there is clear evidence that partial or full placement in another setting is the only option after considering the student’s educational needs or the educational needs of others. Integration Integration is one of the major strategies used to achieve inclusion, Students with special needs are included in educational settings with their peers who do not have special needs, and are provided with the necessary accommodations, determined on an individual basis, to enable them to be successful there. The principle of “placement in the most enabling learning environment” applies when decisions are made about the extent to which an individual student is placed in regular classrooms or is assigned to an alternate placement. English Language Learning (ELL)/Apprentissage de la langue anglaise (ALS) People from all parts of the globe contribute to the social, cultural, and linguistic fabric of British Columbia. This diversity is mirrored in our school populations, in both the contributions made and the unique needs that must be addressed. ELL/ALS students come from many linguistic and cultural backgrounds and have had a wide variety of life experiences — attributes that can significantly enrich the life of the school and help enhance learning for all students. English Language Learning (ELL)/Apprentissage de la langue anglaise (ALS) services enable students whose primary language or languages of the home is/are other than English to achieve the expected learning outcomes of the provincial curriculum and to develop their individual potential within British Columbia’s school system. Differentiated Instruction Differentiated Instruction (DI) is a flexible approach to teaching in which a teacher plans and carries out varied approaches to address content, learning processes, learning style, practical procedures, presentation strategies, and assessment tools. It results in a more personal, proactive learning environment, inclusive of a wide variety of learners. When teachers differentiate instruction, they provide students with the structures to maximize strengths, work around weaknesses, and experience timely remediation. This enables students to take advantage of effective learning strategies as they begin to understand their own personal learning styles, interests, and needs and engage with their learning. As a result, student motivation increases. Universal Design for Learning Universal Design for Learning (UDL) is a framework of instructional approaches that recognizes and accommodates varied learning styles. It provides learning activities that expand students’ opportunities for acquiring information and demonstrating learning, as well as for enhancing social participation and inclusion. The driver for universal design is the philosophy of proactively addressing needs. Universal Design for Learning is integrated into regular instructional planning as a mechanism to make diversity the norm. It provides support for all students and motivates through the element of choice. Response to Intervention Response to Intervention (RTI) is a framework for formative assessment that involves collecting data on a regular basis to make instructional decisions in a multi-tier model. RTI is based on the principle of prevention and early intervention. By using ongoing assessment to inform teaching practice and allocate instructional resources, teachers are able to provide appropriate, evidence-based interventions. Central elements of all RTI models include early screening of all students to identify those at risk for academic difficulties, implementing research-based interventions matched to student need and increasing intensity of intervention when needed. RTI also involves continuous monitoring and recording of student progress during interventions to guide decisions for both the student (e.g., further assessment, individualized planning) and the teacher (e.g., using small-group or one-to-one learning contexts, topics for professional development). Although RTI originates from special education, it is intended for use with all students in general education. Personal safety To ensure a safe learning environment, teachers may consider the following questions before, during, and after instruction: Are students aware of established rules and procedures for safety? Do students fully understand the instructions? Is the activity suitable to each student’s interest, confidence, and ability? Has the instruction been sequenced progressively to ensure safety? Are students being properly supervised? Are facilities, equipment, and technologies suitable and in good repair? Some areas of learning make use of specific safety guides and manuals. These should be employed to ensure that students and teachers can enjoy safe learning activities at all times. In addition to physical safety, teachers should consider the emotional safety of students when planning instruction. This includes, but is not limited to: Being sensitive to individual students Being prepared to respond to unique situations Employing creative strategies to deal with rivalry, stress, fear of failure, performance anxiety, and so on As well, teachers should be mindful of activities that may cause emotional or psychological stress for individual students (e.g., blindfolding, working in closed environments, solo performance, body contact, heterogeneous groupings), and be prepared to offer alternative strategies as needed. Alternative Delivery policy The Alternative Delivery policy outlines how students and their parents or guardians, in consultation with their local school authority, may choose means other than instruction by a teacher within the regular classroom setting for addressing the learning standards contained in the health component of the Physical and Health Education curriculum. The Alternative Delivery policy applies only to the health-related learning standards (Note: the policy will be revised in the 2015/16 school year). The policy recognizes the family as the primary educator in the development of children’s attitudes, standards, and values, but it still requires that all learning standards be addressed and assessed in the agreed-upon alternative manner of delivery. It is important to note the significance of the term “alternative delivery” as it relates to the Alternative Delivery policy. The policy does not permit schools to omit any of the learning standards within the Physical and Health Education curriculum. Neither does it allow students to be excused from meeting any learning standards related to health. it is expected that students who arrange for alternative delivery will address the health-related learning standards and will be able to demonstrate their understanding of these learning standards. Curriculum Overview | Building Student Success - BC's New Curriculum Label: grist Date: August 16, 2017 at 06:08PM Labeled: August 16, 2017 at 06:11PM via GitHub http://ift.tt/2v3y2qB August 16, 2017 at 06:16PM via GitHub http://ift.tt/2v3y2qB [100-days-of-writing] A New Kind of Classroom: No Grades No Failing No Hurry - The New York Times A New Kind of Classroom: No Grades No Failing No Hurry - The New York Times By janzeteachesit Assigned to http://ift.tt/2w3FM0n GRIST4 STEM A New Kind of Classroom: No Grades, No Failing, No Hurry - The New York Times Label: grist Date: August 16, 2017 at 09:21PM Labeled: August 16, 2017 at 09:26PM via GitHub http://ift.tt/2fM9UqG August 16, 2017 at 09:26PM via GitHub http://ift.tt/2fM9UqG [100-days-of-writing] Vim isnt that scary. Here are 5 free resources you can use to learn it. Vim isnt that scary. Here are 5 free resources you can use to learn it. By janzeteachesit Assigned to Vim isn’t that scary. Here are 5 free resources you can use to learn it. http://ift.tt/2uK5YNU GRIST4 CSP VIM Vim isn’t that scary. Here are 5 free resources you can use to learn it. Fatos MorinaAug 16 Passionate Team Lead, Computer Science Graduate, Open Source Enthusiast at http://ift.tt/2rJjttT, Blogger at http://ift.tt/2wjEM8d This is a view from this open source project that displays cryptocurrencies values like Bitcoin, Ethereum and Nasdaq There unknown can be frightening. The unknown is usually followed by a type of resistance. Vim is not an exception. Despite the fact that a StackOverflow question asking about ways of exiting from it has been seen more than one million times, Vim is still one of the most used editors by developers around the world. Many people who do not use Vim are accustomed to other editors and think that they do not need to switch to it. They do not want to leave their comfort zone. They think that Vim takes too much time and effort to learn and that it does not make that much of a difference after all. By taking the time to read this article, you have shown that you already have some type of interest about Vim. Before we see some resources that make it easier for you to learn Vim, let’s see the reasons why should we should even consider using this 1980s text editor. Why should you learn Vim in the first place? “To use Vim is one of the best choices I’ve made in my programming career.” — Lucas Oman It is reasonable that you may need some reasons to know why learning Vim is worth the effort. After all, it may affect your entire workflow. It may even seem unreasonable to start learning something that does not look suitable for you. Vim is used by almost everybody at thoughtbot which is one of the most recommended companies in Bay Area. Knowing this might make it compelling for you to start learning it. Aside from that, there are other reasons worth mentioning. Let’s begin. It is like playing a game When you want to start playing a game, you do not step back from playing it just because it is hard. You actually get motivated to play it because it gives you pleasure. Developing with Vim is similar. When you start to see that it is fast and intuitive, you may start to enjoy the experience. You can even get more hooked on it once you learn some of the more advanced commands that increase your productivity. No need for a mouse You have many shortcuts to navigate through the code and files, which can actually help you get rid of the need to use your mouse at all. As a result, you do not need to get your fingers off the keyboard, which speeds up your coding. In other words, you can code in Vim as fast you can type. It is fast. Even the word Vim means energy and enthusiasm. Many powerful commands The list of commands that you can use is pretty long. You do not have to learn each one, you simply need to learn a few in the beginning and then try to learn new ones as you go. You may learn something new and important that is in Vim even many years after your first lesson. Highly customizable There are configurations that you can use and change based on your own preference. There are hundreds of colors schemes that you can download. Moreover, you can use a large number of plugins that enhance your editor and make it as powerful as modern IDEs. It is text-centered Modern IDEs have a lot of built in features. They usually come with a lot of buttons and a rich user interface to make it easier for you to use all the functionalities that are in it. Vim on the other hand is generally text centered. This makes it easier for you to focus only on the code and get rid of other distractive icons and options that are not code related. It is present in every Linux machine The vast majority of servers use Linux as their operating system. When you are familiar with the basics of Vim, you may become comfortable with the deployments and server maintenance. These are not the only reasons why Vim needs your attention. But they represent some of the most important ones. If they resonate with you, then you may give learning Vim a chance. 5 free online resources to learn Vim Here are a few resources that you can use to help you in your learning journey. Do not pretend to learn everything related to Vim at once. There are people who have been using Vim for 20 years and they are still learning new things related to it. VimTutor If you are using a Unix-based machine, you can go to your shell and type vimtutor. If you are on Windows, you can see some of the answers to open it here. You will have an excellent tutorial that will help you learn the basics of Vim in a few minutes. When you are done, you will already see why Vim is amazing. OpenVim This is an interactive tutorial that you can use to get a solid understanding of the basics in Vim. You can also use it to test your existing Vim skills. Vim Adventures If you like learning while playing games, then this resource may be valuable for you. In this game, you can learn to use Vim commands for navigation, which are essential for you to navigate the maze. You can always type :help for any hint. The basics of Vim Derek Wyatt has prepared an album with 13 videos where he teaches Vim. These videos have been seen several thousand times and are very valuable resources for you to learn the basics of Vim. If you are still doubting whether you should learn Vim, then these videos can give you more reasons to learn. Vim Cheat Sheet Print this cheat sheet and leave it next to your desk. From time to time, take a few seconds to look through the list and try to use something from it. This way you can memorize new commands on the go and also reinforce the ones that you already one. Conclusion If you’re new to Vim, then it may be better to not start to use it immediately in your work projects, because you may get frustrated and never get back to it. You should initially use it in your side projects, and only start using it in your full time job once you are pretty comfortable. Try using Vim for a few days in a side project that you have and see how it goes. If you enjoy using it, then you can stick to it. I am a Passionate Software Engineer, currently serving as a Team Lead Developer for a group of enthusiastic developers that specialize in developing web and mobile applications, mostly using Ruby on Rails and React JS. I am currently looking for a remote job. Please contact me for new opportunities. Show your support Clapping shows how much you appreciated Fatos Morina’s story. freeCodeCamp Our community publishes stories worth reading on development, design, and data science. Vim isn’t that scary. Here are 5 free resources you can use to learn it. Label: grist Date: August 17, 2017 at 08:31AM Labeled: August 17, 2017 at 08:40AM via GitHub http://ift.tt/2wTccbv August 17, 2017 at 08:56AM via GitHub http://ift.tt/2wTccbv [100-days-of-writing] Interactive Vim tutorial Interactive Vim tutorial By janzeteachesit Assigned to http://ift.tt/nHAJaF GRIST4 CSP Interactive Vim tutorial Label: grist Date: August 17, 2017 at 08:36AM Labeled: August 17, 2017 at 08:40AM via GitHub http://ift.tt/2vGBxqH August 17, 2017 at 08:56AM via GitHub http://ift.tt/2vGBxqH [100-days-of-writing] Stop Forming Habits and Start Keeping Habits: the Shift in Mindset that Makes all the Difference Stop Forming Habits and Start Keeping Habits: the Shift in Mindset that Makes all the Difference By janzeteachesit Assigned to Stop Forming Habits and Start Keeping Habits: the Shift in Mindset that Makes all the Difference http://ift.tt/2fQSn0F GRIST4 Writing Stop Forming Habits and Start Keeping Habits: the Shift in Mindset that Makes all the Difference Michael J. MottaAug 16 Professor. Author of LONG TERM PERSON, SHORT TERM WORLD. Doesn’t believe in mailing lists. mjmottajr.com I put a checkmark next to all of my intentioned actions today. Hopefully I will do the same tomorrow, but I might not. And that’s OK. I’ll still keep my habits. Life’s a rollercoaster and I’m not focused on waiting in line and taking my seat. I’m focused on knowing that the ups will become downs and the downs will become ups. I have wined and dined with kings and queens, and I’ve slept in alleys and dined on pork and beans. — Dusty Rhodes Here’s an example. I’ve journaled for 5 years… except that I haven’t. Visit productivityjournals.com for context. Here’s what I mean. In 5 years, I’ve actually only journaled in: 35 of 60 months. That’s less than 60% of months. 91 of 240 weeks. That’s only 38% of weeks. 750 of 1,825 days. Only 41% of possible days. For a “daily” habit that I write a lot about, that’s hypocritical. My habit is demonstrably inconsistent. But I learned years ago that I’m not good at forming habits. For the first few days, sure, I’d do the thing. Then life came along and the habit withered, only to return a few months down the road. Only to meet the same fate again. This is why I don’t place my emphasis on forming habits. I don’t try to do something for 66 days in a row or whatever science says I should do. Instead, I focus on keeping habits. Consistency is Overrated When you miss doing Habit X for a day, week, month, or even a year, a voice in your head declares: “It’s all ruined now. Might as well accept defeat!” That’s why one missed day turns into two days, one week into three, one month into a year. It’s why so many habits are start-stop, start-stop for our entire lives. It’s why so many of my habits fell by the wayside only to be “reformed” later. Consistency is both necessary and sufficient for forming a habit; however, it is neither necessary nor sufficient for keeping a habit. In other words: Don’t let convince yourself that you’ve lost the war when you’ve lost one measly battle. Grit is Underrated More important than consistency is the willingness to return to a practice after an absence. Grit. How many have almost reached the goal of their ambition, but, losing faith in themselves, have relaxed their energies, and the golden prize has been lost forever. — P.T. Barnum If you accept that you’ll drop the ball and neglect habits, and if you expect that your inner self will seize the opportunity to deflate your ambitions, you’ll be prepared to soldier on. Slowly, over time, you’ll build confidence in your ability to pick the habit back up. You will no longer beat yourself up. You will no longer have to worry about reforming the habit because you’ll have the habit. Strategy To keep the habit, you must anticipate threats. While threats are unpredictable, they are predictably unpredictable. We don’t know when these threats will come but we know that they will come. Here are some threats I’ve encountered over the years and how I’ve dealt with them (or how I wish I dealt with them.) TRAGEDY STRIKES It’s hard to focus on keeping a habit when you aren’t sure if you can make it through the day. Eventually, we’ll want a distraction from our emotions. We can choose whether the distraction is Netflix or our journal, or a run, or a book, or anything else related to our goals and habits. DEATH BY A MILLION PAPER CUTS The most existential threat to habit-keeping isn’t the worst the world throws at us — it’s the small, barely perceptible wounds we give ourselves everyday. Every time we make a short term decision (such as getting lost in a Facebook rabbit hole), we give ourselves a little cut. We justify the decision and promise never to do it again. But each time we make such a decision, we increase the chances that we’ll make the same decision again. And again. And again. The only strategy for preventing death by a million paper cuts is to prevent the cut if we can, and if we can’t, to make the cuts small and shallow. Lower your expectations in order to fulfill your intentions. Give yourself permission to compromise with yourself. Do the thing but change up the routine. Try a different workflow. Do something else first then come back to it. Or, if you must, go into “Survival Mode” where you write one line of code, do one push-up, write one line in the journal, or watch a leaf fall slowly from a tree instead of meditating. Seemingly “small” actions, if they keep a habit, are worth their weight in gold. There are two mistakes one can make along the road to truth — not going all the way, and not starting. — Gautama Buddha HYPER-FOCUS Sometimes we face the opposite problem: We become obsessed with one goal and hyper-focus upon it, ultimately to the detriment of other goals. We feel like we’re being productive, and technically we are, but we’re leaving a path of destruction behind us. After you finish this important project or accomplish this critical goal, you will live to fight another day for another cause — hopefully many days and many causes. You will be in this same situation again and again, finding yourself hyper-focusing on one thing while neglecting others. How you perform now is probably how you will perform then. When I feel myself becoming hyper-focused, I make myself work five or ten minutes on one of my neglected projects. This has several benefits. I make progress, and I keep the habit. This also provides insight into why I’m hyper-focusing. Is it because I’m procrastinating in some other area of my life? Or am I genuinely passionate? Once I know this, I can make an informed decision regarding how to proceed. You can also use this extra motivation for accomplishing Goal A to help you accomplish goals B and C. Force yourself to complete other tasks before allowing yourself to work on the preferred task. By rewarding yourself, you’re in effect taking the excess motivation and distributing it elsewhere. ACCEPT, AND EXPLICITLY DEFINE, LIMITATIONS It is suboptimal to do all things optimally. When all the elements of a system are at capacity, the system itself is over capacity. You must find elements of your system where you are willing to accept limitations. Example: I have zero ambition of running a marathon or being in anything close to “elite” shape. I will probably never try to extend my meditation sessions beyond 20 or 30 minutes. I cannot commit to writing several pages in my journal with much regularity. Such “limitations” in one place also make it possible to have “unlimitations” elsewhere. VACATION Personally, if I take a week off from all of my habits, I have a very hard time getting back into the swing of things. Maybe you are more disciplined and can do that. If you cannot, my recommendation is this: At a bare minimum, keep performing at least one action related to your long term goals. This need not take much time at all and will make it infinitely easier to get the system back up-and-running when you return. Take a vacation, but not from everything. Go for a run, or just do a push-up. Write in your journal, even if it’s only one line. Keeping something going is almost as good as keeping everything going. RE-ENTRY PLANS Vacations will not be the only time your habits will come to a halt. Inevitably, you will neglect them. A day here or there, a week, maybe a month or more. You can, of course, summon enough grit to pick the entire habit back up. But there’s a way to make it easier: re-entry plans. Re-entry plans are a failsafe. They prevent neglect from becoming abandonment. You can make plans for specific actions (e.g., “What To Do If I Stop Working Out”) or you can have a plan that applies to all actions. It doesn’t matter. The important thing is to have a plan that requires nominal grit. If you lose your exercise habit, the plan might be to go for a walk. If you stop writing 1,000 pages a day, the plan might be for 50 words. I use one action: I write a single line in my journal. I do this when I drop the ball on journaling or any other habit — or all of them. Each time, I’ve kept writing, wanting to tell the story of why I’d been away from the particular habit(s). Like catching up with an old friend, doing sogives me enough of a spark to do something else, then something else. And, soon enough, I’m back on track. WRONG HABIT Maybe you’ve dropped the habit because something more fundamental is amiss. Have a series of questions ready to ask yourself. Maybe your goals have changed or maybe there’s a better way to go about achieving them. Maybe your sleeping habits have changed, affecting when you feel at your peak. Maybe the winter makes running difficult. Maybe your shin splints suggest you should run less and practice yoga more. Whatever the reason, find it, then adjust as necessary. (I believe journaling makes such shifts perceptible earlier than they otherwise would be.) A Final Quote and a Final Note I love this quote: How we spend our days is how we spend our lives. — Annie Hillard But I ultimately disagree with it. How we spend most of our days is how we spend our lives. You can learn more about keeping habits in my book, on my blog, and by following me here on Medium. If you enjoyed this story, please recommend and share to help others find it! Feel free to leave a comment below. The Mission publishes stories, videos, and podcasts that make smart people smarter. You can subscribe to get them here. Show your support Clapping shows how much you appreciated Michael J. Motta’s story. Michael J. Motta Medium member since Apr 2017 Professor. Author of LONG TERM PERSON, SHORT TERM WORLD. Doesn’t believe in mailing lists. mjmottajr.com Stop Forming Habits and Start Keeping Habits: the Shift in Mindset that Makes all the Difference Label: grist Date: August 17, 2017 at 04:05PM Labeled: August 17, 2017 at 04:10PM via GitHub http://ift.tt/2fP9sYD August 17, 2017 at 04:11PM via GitHub http://ift.tt/2fP9sYD [100-days-of-writing] A Primer to Colors in Digital Design uxdesign.cc A Primer to Colors in Digital Design uxdesign.cc By janzeteachesit Assigned to A Primer to Colors in Digital Design – uxdesign.cc http://ift.tt/2wogWIw GRIST4 GR A Primer to Colors in Digital Design Archit JhaJul 16 Digital Designer | Front-end Enthusiast | UI/UX Aficionado | HCI Lover Source: As a beginner in the world of design, I often struggled with picking the right colors to provide visual depth to my artworks. Consequently, my initial works seemed out of balance as the colors lacked contrast and harmony, robbing my illustrations of the much needed visual acuity. Since painting wasn’t my forte, I hadn’t experimented enough with mixing physical colors using brushes in the past and felt overwhelmed just by looking at the color picker in tools such as Illustrator and Photoshop. Although it took time to educate myself on color theory and principles of harmony in design, the lessons I imbibed along the way certainly helped boost my confidence in picking colors. COLOR THEORY Our brain helps us perceive colors when light reflected off an object is received by the eyes. Objects do not inherently bear color, albeit it is the interplay of absorption and reflection of a choice of continually distributed wavelengths from the visible spectrum by the object that determines its appearance. Therefore, two of the most basic colors, ‘Black’ and ‘White’ respectively denote absence and presence of light and aren’t actually colors. Sunlight, considered as the natural source of light is characteristically ‘White’ but with a pinch of salt. Each white light source has a degree of ‘warmth’ attached to it which is determined by a property called ‘Color Temperature’. This property varies for different light sources as we find the warmth of a halogen bulb, an artificial source of light, inclining towards the yellow side of the spectrum, making the spectral distribution different than daylight. In simple words, appearance of an object depends on the properties of incident light(s) and is never really a single color. COLOR MODELS AND SYSTEMS Color Models are a popular way to represent a range of colors. The underlying principle for almost all color models is the concept of primary colors. Primary colors represent a small set of colors that can be combined to generate all possible colors in the range. These colors maintain an individual identity of their own and cannot be used to generate each other. Colors on Screen Colors on screens and displays are intangible and are generated artificially by combining lights of different colors. They are therefore represented by what is known as ‘Additive Color Models’. RGB RGB is an additive color model used to represent colors on scanners and displays. With ‘Red’, ‘Green’ and ‘Blue’ as the primary colors, RGB color model can be used to produce 16 million (16777216 to be precise) colors as each of R,G and B use 8 bits to take a value between 0 to 255 to construct colors in the range. Red, Green and Blue combine to form ‘White’ [R:255, G:255, B:255], while the absence of all of them produces Black [R:0, G:0, B:0]. On LED screens, each pixel fundamentally comprises a subpixel grid of Red, Green and Blue LEDs which light up at a given intensity to produce the required color in that space on the screen. Additive models are device dependent as the rendering of color varies for monitors. Therefore, a color in RGB space, say [R:32, G:64, B:128], may appear different on different screens. RGB spaces can be customized by using new primaries for Red, Green and Blue and selecting a gamma value. Therefore, other open-ended RGB spaces exist such as the Photo RGB, DCI-P3Pro, Rec 209. Rec 2020, scRGB and ACES(Academy Color Encoding System) some of which are used and were developed primarily for motion pictures by film academies. sRGB(developed by HP and Microsoft together) and Adobe RGB are the two defaults on computers and the internet. 2. HSV and HSL RGB, although very helpful in making computers understand color doesn’t agree much with human perception of colors. It makes more sense to think in terms of ‘lightness’, ‘darkness’ and ‘intensity’ of the color rather than contemplating numeric values of R,G and B to get to the right color. Therefore, HSL (Hue, Saturation, Lightness) and HSV(Hue, Saturation, Value) exist as transformations of RGB model to make a designer’s life easier. 3. Indexed ColorThis system, simply put, assigns a number or ‘index’ to each color in the palette. Images with limited colors in the range save memory and can be refreshed quickly on displays. thereby consuming less power. An index system helps the cause by only requiring the computer to store the indexed number instead of the entire color table. 4. BitmapAnother memory friendly image representation system that uses 1 bit per pixel. Images are stored as a 2-dimensional grid (map) of pixels. 5. GrayscaleCommonly referred to as ‘Black and White’, this image system has no color and just stores the value of intensity of light (White: High Intensity, Black: Low Intensity) 6. YUV Bandwidth comes at a premium and back in the days of Black and White televisions, the analog age, signal transmission capabilities were limited and the system required a way to compress data to be transmitted. Human visual system(HVS) is more sensitive to intensity of light than colors and it receives low frequencies(in Visible EM spectrum) better over the high frequencies. Tapping into workings of human visual system allowed the engineers to create the YUV color space that worked as a color encoding system for broadcasting purposes. While Y captured luma (or luminance i.e perceptive brightness), U and V are chromacities that captured color as factor of difference from Y component. Unlike RGB, where all three values use 8 bits, YUV space allots more space to Y, which stores intensity information, than U and V as HVS is more sensitive to intensity over color, thereby compressing the overall data stream. Among analog television systems PAL(Europe except France and Southeast Asia) used YUV, NTSC(Americas, Japan, South Korea and Suriname) adopted YIQ, a variation of YUV and SECAM utilized YDbDr. In the YUV family of spaces, YCbCr is another variation popular for digital image compression and forms the basis of the JPEG and MPEG algorithms. All three color spaces are fundamentally similar and work as storage and transmission channel intermediates that cannot be rendered directly on screen. Colors in Print Colors you can touch are ‘tangible’ and exist due to natural(or natural + artificial) lighting in the environment. Since these are a result of light reflected off of an object, they are represented by what are called ‘Subtractive Color Models’. A plain paper is perceived as ‘white’ as it reflects all the cored wavelengths of light that fall on it. With the help of ink ,the white paper can be made to absorb some of the colored wavelengths such that a color appears on paper. This is how inks fundamentally operate, however there are two mechanisms to achieve this: I Spot Colors based PrintWhen each color in the print job is achieved with a separate ink, the print is Spot colored based since spots from individual colored inks or pigments are used to obtain the final print. Spot colored prints produce the best output as the colors are exact but prove expensive with increasing number of colors in the final job. Some standard proprietary spot color systems are ANPA, Colour Index International, DIC, FOCOLTONE, HKS, Munsell, NCS, Pantone, RAL, TOYO and Truematch. Pantone Matching System(PMS) PMS is a proprietary color space owned by Pantone Inc.(now under X-Rite) and is the leading standard for spot colors in the printing industry. Each of the 1,114 spot colors in the PMS system could be identified by it’s unique PMS number. PMS is preferred across the industry to maintain consistent branding across the globe. Only a small subset PMS colors can be reproduced using the CMYK model which is used for process printing. II Process Colors based PrintProcess printing works on the concept of primary colors where a handful of spot colors are used to create new colors. Reprographic techniques such as ‘Halftone’ in process color printing create an optical illusion of a new color by strategically spacing differently sized dots of spot colors in a way that they appear as a new color or a smooth transition between colors. Although, not as vivid as spot color print, process printing saves costs. CMYK (C)Cyan, (M)Magenta, (Y)Yellow and (K)Key-Black is a subtractive color model that can be used to achieve a range of colors. Combining C,M,Y and K at 100% each produces pure black while absence of all is white which is opposite to the RGB model as CMYK is implemented using inks and pigments rather than light. When inks combine in full concentration they absorb all the light, producing black. Reproduction of image using CMYK bases process printing produces different results as this model is also device dependent. Optical Illusion when using Process Colors Device Independent Color Device dependent color management system often have suppressed gamuts(range of colors). Age, make, subpixel arrangement, display panel type (OLED, LCD, Plasma) affect the rendering of color in monitors. Similarly among printers, paper type, nozzle make and dye account for variations in color reproduction. International Consortium on Illumination (CIE) began work on color spaces that would provide a nexus between physical wavelengths in visible spectrum and human perception of colors as early as 1931. This was before the age of transistors and the system developed was device independent. It started with CIE XYZ and subsequently CIE LUV and CIE LAB were derived. LAB Derived from the CIE XYZ color space, CIE LAB is the mathematical representation of all perceivable colors in a 3-dimensional space. While ‘L’ defines lightness on one axis, ‘A’ and ‘B’ are color channels. The LAB space creates a much wider gamut than RGB and encompasses 50% more colors. In fact, a lot of values on LAB space are not even colors since they fall outside the spectrum of perceivable colors by the human visual system. The displays aren’t capable of rendering all the values in LAB either and therefore it finds it’s rare but very important use in medical imaging and computer vision applications where pushing RGB spaces just produces white instead of a possible color value. You can’t depend on your eyes when your imagination is out of focus. -Mark Twain COLOR WHEEL The quote from Twain provides us a segue into the artistic(and more designer friendly) phase of this article after the overdose of color lingo from the vocabulary of computer graphics. A color wheel is a concept in art(not technology) that arranges colors in a circular fashion in order to establish relations between the primary secondary and tertiary colors. In practice(painting), primary colors can be used to produce other colors mixing them: Primary [ Red, Blue, Yellow ] Primary + Primary = Secondary [ Violet(Red+Blue), Green(Blue+Yellow), Orange(Yellow+Red)] Primary + Secondary = Tertiary [ Green-Yellow, Yellow–Orange, Orange-Red, Red–Violet, Violet-Blue and Blue–Green ] Visual Parameters of Color Hue: The property to significantly distinguishes a breed of colors from other in the spectrum Value: The lightness or darkness of a color. The term value is often used interchangeably with ‘Brightness’, ‘Lightness’ and ‘Luminosity’. However, in physics, the terms bear a subtly different meaning. Saturation: The intensity of a color. It determines the purity of a color and is often denoted by terms ‘colorfulness’ or ‘chroma’. Shade: A darker variant of a color obtained by adding black. Tint: A lighter variant of a color obtained by adding white. Tone: Both tinting or toning a color or adding grays produces tones of a color SIDE NOTE: ‘Pastel’ is a special family of hues that have relatively low saturation but high values. These ‘muted’ colors appear soft and evoke soothing, calming sensations. Harmonies in Color Colors create both a visceral and a visual sensation and a portion of both helps us establish relations between them. On the color wheel, primaries Red, Blue and Yellow are equidistant are located at 120 degrees from each other. Going clockwise on the color wheel from Red-Violet to Yellow, gives a sensation of warmth and these 6 adjacent colors are referred to as ‘Warm Hues’. On the other half, the remaining colors from Violet to Yellow-Green are referred to as ‘Cool Hues’. Colors add depth to design and generate emotions. It is important to balance them in a way that they produce sufficient contrast to draw the viewer in and add a pep to the creativity that lies underneath. Although sky is the limit to creativity, some basic rules govern the laws of harmony. The rules aren’t perfect and art lies in bending them the right way. Color schemes(read ‘Palettes’) that inform the design could be developed based on the foundation of these classical rules: Analogous: Colors contiguous colors on the wheel are analogous to each other. Complementary: Colors at a radial separation of 180 degrees are complementary to each other. Monochromatic: A single hue on the color wheel with varying levels of saturation forms a monochromatic relationship with it’s variants. Split-Complimentary: A base color with colors on either side its complement are said to be in a split-complimentary relationship. Triadic: Colors at a redial separation of 120 degrees from each other form a triad. Choosing Colors Color palette for an artwork is developed by starting with a base color and gradually picking other colors that form a visual harmony with the base color. Playing around with value(Lightness/Darkness) of a color helps fine tune the contrast and creates a sense of balance. Classical rules are good start but one should never be afraid to bend the rules. At times, a color choice out of nowhere could generate a better emotion over the classic alternative. Color Picker Navigation It is important to note that colors around a color will impact how it feels to the user. Some values may make your base color feel too dark or too light while some hues may make it look to warm or cold (observe the text labels on axis in the picture above closely). Robert Plutchik’s Wheel of Emotion Colors elicit emotions and bear a meaning which varies with cultures, beliefs, geographies and other demographics. For example, RED in China indicates luck while in South Africa it is the color of mourning. Russia associates Red with communism while the countries in the west attribute it to fervor and intensity. It is fascinating how colors can be used to create moods. Forming relations is a very human way of processing things and colors are just the right tool build them. Good Practices in Design The world of digital design, especially branding is a challenging space for designers as the scale of your artwork’s reproduction is sometimes unfathomable. A company’s logo, for example, dwells on a breath of materials in both physical and virtual forms. To get an an idea, consider these: Displays(LCD, Plasma, CRT, LED, OLED) Papers(Coated, Uncoated, Cardstock) Clothing(Flags, T-shirts, Caps) Equipment/Devices(Metals, Ceramics, Glass) Merchandise(Leather, Wood, Plastic, Cardboard) As a designer, you job is to create a uniform experience across all of the above such that the aesthetics of the company is diffused into the environment wherever there is a possible interaction. It is a complex job, but some good practices make the ride smoother. Even if your artwork isn’t a logo, following these rules would help you in the longer run. Always work in CMYK space — The conversion from CMYK to RGB produces better results then the other way round. The Adobe suite of applications use the Adobe RGB color space which is a compressed gamut. Blacks tend to lose their intensity when transformed from RGB to CMYK and miss that pop when you observe them closely. Start with Grayscales — Play around with just the value in the beginning without introducing colors. If your grayscale variant has enough contrast to make a visual appeal, adding hues to the values will usually form a good harmony. Pick Pantones for Branding Projects —The advantage of spot colors is they appear identical regardless of where they are printed in the world. Having standard spot colors, Pantones especially, would make sure the visual identity of your branding artwork is retained. Know the Mood and the Purpose — Ask yourself what is the purpose of your illustration? What do you want your users to feel when they see your work? What do you want to convey with your artwork? Answering these questions will help you make a decision in picking a base color and balancing the warm and cool hues in your artwork. Remember that colors carry meaning and have the power to evoke emotions. Choose wisely. Target good contrast — Experiment with hues to create contrast of hue, saturation and value. Highly intense colors stab the eye instead of pleasing it. If there’s text on your illustration, make it readable by using high contrast colors (Black text on White is the best contrast). Follow WCAG guidelines if you will. Warm and Cool hues on each other aren’t good for type and some colors are just intrinsically difficult for humans to differentiate (Green on Red or vice versa, blue on green). Work with a Palette — Adding shadows and highlights to your work adds visual detail and makes it look both professional and creative. Work with ‘Tonal Families’ which is your color palette replete with shades and tints of your choice of colors. There are some great online tools out there to help you create and maintain your color palette — Adobe Color, CheckMyColors, Colrd, ColorExplorer, ColorHunter, ColourLovers, ColorMatters, ColourMod, Coolers, Designspiration, Paletton, Pitaculous. Seek Inspiration — A nice trick to create good color palettes is to pick(read ‘borrow’)colors from an artwork you really like. Both digital graphics and paintings by masters from the renaissance can turn out to be great sources of colors that work well together. Respect the environment — If you have an image that goes with your design, try to pick colors from that to create a sense of balance across the space. Magazines are some really good examples. Notice how the text and other visual artefacts of design that reside nearby blends with each other creating a harmony that leads you into it. Bend the rules — This point cannot be stressed enough. Don’t be shy to experiment. Practice! Practice! Practice! —The more you do, the more you learn. Follow popular artistes on dribbble and behance. Try to deconstruct their style and implement it and one day you’ll have one of your own Show your support Clapping shows how much you appreciated Archit Jha’s story. Archit Jha Digital Designer | Front-end Enthusiast | UI/UX Aficionado | HCI Lover A Primer to Colors in Digital Design – uxdesign.cc Label: grist Date: August 18, 2017 at 08:28AM Labeled: August 18, 2017 at 08:40AM via GitHub http://ift.tt/2vPHPCG August 18, 2017 at 08:45AM via GitHub http://ift.tt/2vPHPCG [100-days-of-writing] 12 extensions that will make any UX Designer 12 extensions that will make any UX Designer By janzeteachesit Assigned to 12 extensions that will make any UX Designer’s life easier http://ift.tt/2wcbusK GRIST4 GR 12 extensions that will make any UX Designer’s life easier KaylaMatthewsAug 16 If a person has only 15 minutes to spend on content, around 75% prefer to read a page with good design over reading something without much pizzazz. Designers seem to intrinsically understand this fact and will spend hours getting coloring and spacing just right. Fortunately, there are a number of tools that will make any UX designer’s life easier and speed up the process a bit. Here’s an even dozen for you to check out. 1. Window Resizer Today’s UX designers understand that different people access the internet on different screen sizes, including smaller devices like smartphones. The Window Resizer Chrome browser extension allows you to quickly adjust your screen size to see how a screen will look on different devices. This is vital for developing the best user experience possible. 2. MultiClipboard Designing means doing a lot of coding work. When coding, designers tend to copy and paste from one place to the next. You might grab some code from a design you completed last year with a specific element or you might look up code and grab it. You might also be in the process of debugging and need to get some feedback on some copied-and-pasted code. The MultiClipboard plugin makes it easy to have several clipboards going at one time so you can easily grab a bit of code from here and paste it into a different notepad file. 3. AutoSave You’ve just spent an hour coding a particularly challenging piece of PHP when your laptop battery runs down and your computer shuts off. And you thought you had it plugged in! If you’ve remembered to hit Ctrl/S over and over again, you’ll be fine. However, if you forgot, you will have to start over. Unless, that is, you’ve already downloaded the Notepad plugin called AutoSave. AutoSave automatically saves your work every so many seconds so you don’t have to worry about losing vital coding and having to start over from scratch. In a pinch, this plugin can really save you both frustration and time. 4. HTML2WordPress Do you have a static HTML website that you’d like to convert to WordPress? In the past, this has been a real headache. tags and other issues crop up with conversion and can take hours upon hours to debug. On top of that, HTML coding doesn’t always translate well into PHP and you’re left with strange-looking conversions that might not be very user-friendly. That’s where the HTML2WordPress plugin comes into play. HTML2WordPress takes your static coding and converts it into WordPress language, making the process of converting your website much easier. 5. Brackets Extensions You may already be using Brackets software to more easily code, but did you know there are numerous extensions for Brackets that can save you even more time on coding tasks? For example, you can use the Autoprefixer, which will add vendor prefixes via support data from your browser and help you figure out on-the-fly if a specific prefix is needed and can be used. In addition, the extension will take out any vendor prefixes that aren’t needed and clean up your code. 6. Monster Widget When you’re in the middle of designing a new WordPress site, you may want to test out a number of different plugins to see what gives you the look and function you need. However, this can be extremely time-consuming, as you will have to add and remove widgets over and over. With Monster Widget, you can see at-a-glance the impact different widgets will have on a theme’s look. 7. What Font Did you see a font on another website that you loved and really want to replicate in one of your designs? There are so many fonts these days that it can be difficult to know 100% which font another site is using. However, if you download the What Font Chrome extension, you can simply click on the text on the page and find out what font is being used. This allows you to incorporate the look of text you really love into a fresh, new design all your own. 8. PSD to WordPress Do you have a design you created in Photoshop that you want to easily move over to WordPress? Fortunately, Photoshop has an extension that allows you to easily convert so that everything is coded perfectly for WP. PSD to WordPress speeds up the process and allows you to design once and then convert easily without additional hours spent coding and recoding files. 9. Spectrum When designing a website, you want the colors to look just so. However, one thing that’s easy to forget is that there are people out there with visual challenges who might not be able to see your site the way you think they will. This can include visual impairment or color blindness. Spectrum allows you to see the website you’re creating through their eyes. You simply use the extension and you can see how different colors look and whether or not there’s enough contrast for someone who has a color vision deficiency. 10. CSS3 Generator Some coding tasks are straightforward and easy, but some are more complex. Finding shortcuts can save you a ton of time. The CSS3 Generator is a Chrome app that allows you to create different snippets of CSS code, such as grabbing Hex/RGBA coding or creating CSS columns. 11. Check My Links Checking links within your design might sound simplistic, but it can greatly impact user experience if links are broken. It’s time-consuming to click on each link, make sure the page loaded, etc. Check My Links works with Chrome. You simply start Check My Links and the plugin will crawl through the links on your website and report any broken links. This is also a smart thing to utilize from time to time as you update your site or a bit of time passes to make sure everything is still functional for the user. 12. Eye Dropper Sometimes you see a color on another website that you fall in love with. While you don’t want to copy another design, inspiration from a particular color is common. You could screen-capture the page, plug the screenshot into a photo editor and use the eye dropper tool to try to figure out what the exact formulation of the color is, but that’s time-consuming and not always accurate. Another option is to download the Eye Dropper Chrome extension. With this extension, you just click on the color on the actual site and you will find out the exact color. You can then use it in your design or avoid it like the plague if you hate it. These extensions will make your life as a designer a bit easier and speed up the time it takes you to code. There are many other extensions out there, but these 12 will give you a good start. 12 extensions that will make any UX Designer Label: grist Date: August 18, 2017 at 08:29AM Labeled: August 18, 2017 at 08:40AM via GitHub http://ift.tt/2w9835L August 18, 2017 at 08:45AM via GitHub http://ift.tt/2w9835L [100-days-of-writing] Thoughts on Skeuomorphic Menu Systems Charlie Deets Medium Thoughts on Skeuomorphic Menu Systems Charlie Deets Medium By janzeteachesit Assigned to Thoughts on Skeuomorphic Menu Systems – Charlie Deets – Medium http://ift.tt/2uVlYrq GRIST4 GR Thoughts on Skeuomorphic Menu Systems The tradeoffs and benefits of pseudo-realistic menu design Charlie DeetsAug 13 Product Designer at WhatsApp / charliedeets.com Recently I’ve been playing Splatoon 2, which is a team-based third-person shooter available on the Nintendo Switch. To move between different styles of gameplay, the player must physically move their character in 3D space around a place called Inkopolis Square. This isn’t necessarily a new mechanic in games, but Splatoon’s implementation of it is particularly bold. Moving through 3D space to make selections The square acts as the main menu to the game, giving players the ability to start solo play, online play, local play, purchase items from vendors, and more. Most of the areas have non-obvious names like Octo Canyon, The Shoal, Grizzco, and Galleria. The game encourages players to move around the square and figure out what these various places do. My Squid Kid in the middle of Inkopolis Square, the main menu of Splatoon 2 At the same time, there is a persistent overlay in the bottom right corner which lets the player know they can access a menu with the X button. When the player taps the menu button they get a more traditional menu system which allows them to quick travel to any of the available locations. It also shows them where these locations exist on a map and if they are currently available. Splatoon 2’s traditional menu system One of the benefits of moving around the 3D space of Inkopolis Square is that you run into other players. Walking by certain players will reveal drawings they made which give you a sense of what people are thinking about or inside community jokes. Players can also check out each others gear and order the items other players are wearing. All this creates a sense of culture and community in Splatoon 2. Viewing another player’s drawing The main disadvantage to this system is speed. It takes a lot longer to move around this space than it does to make a selection from a list menu. A player can become distracted from their objective moving around the square. They can get lost trying to find the place they are going. This is why Nintendo included the X button menu. When I first discovered the menu, I was relieved that there was an faster way to start games. After thinking about it, I found myself disappointed because it undermines the core value proposition of the skeuomorphic menu by giving players a way to avoid it. Destiny, an online-multiplayer first-person shooter by Bungie, uses ‘social spaces’ in a similar way to Splatoon. Players must physically walk to vendors, mission guides and postmasters. They must board their spaceship before they can fly to a mission. Unlike Splatoon, Destiny does not offer an alternative 2D menu for these actions. Physical motion of your character in 3D space is required to engage with play modes and vendors. The Tower, a social space in Destiny, featuring vendors such as a postmaster, cryptarch, vaults, and more. One of the reasons this paradigm might be so impactful, even if it is inefficient, is that it supports a game world’s sense of immersion and helps suspend disbelief. In a traditional UI this is rarely important, but in a game UI it is advantageous to keep players immersed in the game world. Inventory management paradigms In Destiny, players must be in physical proximity to a vendor in order to purchase gear. When acquiring loot during gameplay, players physically pick up gear from dropped engrams. The reliance on physical space for these transactions adds a realism to the idea that the player acquired something. When the player manages their inventory, they must move their character to the ‘vault’, which allows them to store their weapons. Approaching this ATM-like console ends up giving the player the feeling their weapons are physically stored somewhere when they are not using them. The action helps keep the player immersed in the experience much better than moving items from one menu to another less prominent menu. A player using a vault in Destiny PlayerUnknown’s Battlegrounds also uses physicality in an interesting way with their inventory menu. When the player encounters loot in the game, they can pick it up one of two ways. In the 3D world they can tap the F key, their avatar will bend over and pick up the item. The player can also press the tab key to open a menu that allows them to see what loot is physically near them presented in a list view. PlayerUnknown’s Battlegrounds inventory menu, the list on the left are items in your reachable vicinity When the player is in that menu, they must drag-and-drop the items from the left side of the screen to their avatar on the right side of the screen. The developers could have solved this by allowing players to click on the items they want, but the physicality of dragging the loot to the character gives the player a sense of ‘acquiring’ in a more realistic way. When a player drops loot for their teammates, they drag the loot to the left side of the screen and let it go, ‘dropping’ it on the ground for them. Historical references The Splatoon 2 menu system reminds me of some old school 90s UI design paradigms. Between 1994 and 1996, Apple had an online service called eWorld. It catered to those who were coming online for the first time. Apple decided to describe features such as email and bulletin board systems as physical locations that mirrored their real life equivalents. Apple’s eWorld menu http://ift.tt/1F7fI16 There was an Arts & Leisure Pavilion, Marketplace, Newsstand, Community Center and more. For those who didn’t understand BBSes, email, and content browsers this design offered assistance in the helping the user understand their choices. The user had to ‘travel’ to each feature, which helped educate the user that in order to use other features they would have to ‘return’ to the main menu. AOL, another online service provider used a less skeuomorphic UI during this time for its main navigation. My guess is people found navigation and repetitive actions easier with a UI that valued visual clarity of choices over education. AOL main menu in 2003 via http://ift.tt/2vEQGXN Super Mario Bros. 3 was an early example where physical space and menu systems converged. The game navigation in SMB3 looks like a physical map the player moves their character over. It also acts as a non-linear menu system because the player can select anything that has been unlocked by moving their character to the option. World 2 map in Super Mario Bros. 3 featuring card games, levels, mushroom houses, castles and warp zones If you take this same paradigm and move it to a contemporary game like Breath of the Wild you can see how this interaction still applies to the game modes. With contemporary games, the behavior tends to feel more fluid and less obvious because of how avatars flow between various states. Not all contemporary games employ this technique, for example Ultra Street Fighter II: The Final Challengers is a great example of a list based menu system. No frills, just options presented as text. Ultra Street Fighter II: The Final Challengers is a contemporary game that features a list based menu system Wrap-up Most user interfaces generally need to be fast and obvious because people perform repeated navigation actions in them. Experiencing the Splatoon 2 menu system was shocking to me at first because it felt so inefficient, but there are real advantages to increasing friction by using skeuomorphic design patterns in three-dimensional space. These menus can help create a sense of immersion, develop social interactions, explain complex concepts quickly by referencing real-life counterparts, and even create a sense of mystery and intrigue by obscuring how simple the system might actually be. Come hang out and play some Splatoon, my friend code is SW-5160–0900–5248 I’d love to know your thoughts on menu systems, games that use skeuomorphic design to enhance the experience and games that work great with a traditional UI. You can find me on Twitter @charliedeets. I also have a podcast called Games UX. You can listen to episodes on the website or follow along on Twitter @games_ux. My Switch friend code is: SW-5160–0900–5248. Show your support Clapping shows how much you appreciated Charlie Deets’s story. Charlie Deets Medium member since Apr 2017 Product Designer at WhatsApp / charliedeets.com Thoughts on Skeuomorphic Menu Systems – Charlie Deets – Medium Label: grist Date: August 18, 2017 at 08:58AM Labeled: August 18, 2017 at 09:00AM via GitHub http://ift.tt/2v84l7Y August 18, 2017 at 09:08AM via GitHub http://ift.tt/2v84l7Y [100-days-of-code] Speech API - Speech Recognition | Google Cloud Platform Speech API - Speech Recognition | Google Cloud Platform By janzeteachesit Assigned to http://ift.tt/2fRuo14 aimlnn Speech API - Speech Recognition | Google Cloud Platform Label: AI-NN-ML Date: August 18, 2017 at 09:39AM Labeled: August 18, 2017 at 09:40AM via GitHub http://ift.tt/2wodQEm August 18, 2017 at 09:40AM via GitHub http://ift.tt/2wodQEm [100-days-of-writing] Make: - YouTube Make: - YouTube By janzeteachesit Assigned to https://www.youtube.com/channel/UChtY6O8Ahw2cz05PS2GhUbg GRIST4 STEM Make: - YouTube Label: grist Date: August 19, 2017 at 02:34PM Labeled: August 19, 2017 at 02:40PM via GitHub http://ift.tt/2wbXNKc August 19, 2017 at 02:45PM via GitHub http://ift.tt/2wbXNKc [100-days-of-writing] (13) Kids Make: - YouTube (13) Kids Make: - YouTube By janzeteachesit Assigned to https://www.youtube.com/channel/UCDdMryhO2umklbFW8GZA3-w GRIST4 STEM (13) Kids Make: - YouTube Label: grist Date: August 19, 2017 at 02:35PM Labeled: August 19, 2017 at 02:40PM via GitHub http://ift.tt/2vSOEmR August 19, 2017 at 02:45PM via GitHub http://ift.tt/2vSOEmR Github Weekly Summary
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Date: August 19, 2017 at 07:29PM