CarpentryCon session to onboard Instructors to the lesson?

[tobyhodges]

CarpentryCon@Home 2022 coincides fairly well with the timing of the beta release of the lesson. @K-Meech @quist00 @uschille @bobturneruk would any of you be willing to submit a proposal for a skill-up session onboarding Instructors to the curriculum? I'd be happy to co-host that call, but I would need at least one of you there to discuss the specifics of image processing.

[uschille]

Unfortunately the first week of August coincides with another conference for me.

[K-Meech]

I'm busy then too unfortunately

[bobturneruk]

I can do some dates around that time and can probably put in a proposal. Let me check dates and proposal requirements. I guess my role in the session would be to field anything very specific about the research area?

[tobyhodges]

Certainly I would need you to bring that aspect, @bobturneruk, but you are also welcome to more actively lead the session if that is something you would like to do. If not, no problem - I can facilitate and make sure the discussion keeps moving.

[quist00]

I can probably be available if you want to list me as a helper on your proposal, Bob.

Dave

From: bobturneruk @.> Date: Friday, May 20, 2022 at 1:16 AM To: datacarpentry/image-processing @.> Cc: Palmquist, David @.>, Mention @.> Subject: [External] Re: [datacarpentry/image-processing] CarpentryCon session to onboard Instructors to the lesson? (Issue #209) External Email Use Caution and Confirm Sender

I can do some dates around that time and can probably put in a proposal. Let me check dates and proposal requirements. I guess my role in the session would be to field anything very specific about the research area?

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[bobturneruk]

Thanks @quist00! Can you have a little look at the form and let me know what timezones you're comfortable with, please?

[quist00]

Hi, @bobturneruk

Probably best if you just go with what works for you as the main presenter and then can adjust to that since I think we are kind of polar opposites as timezones go if I recall.

Dave

[bobturneruk]

Title: Instructor Onboarding: Image Processing with Python (beta)

Keywords: onboarding, instructors, images, python

Prior knowledge: The Image Processing with Python lesson assumes you have a working knowledge of Python and some previous exposure to the Bash shell. These requirements can be fulfilled by: a) completing a Software Carpentry Python workshop or b) completing a Data Carpentry Ecology workshop (with Python) and a Data Carpentry Genomics workshop or c) independent exposure to both Python and the Bash shell.

If you’re unsure whether you have enough experience to participate in this workshop, please read over this detailed list, which gives all of the functions, operators, and other concepts you will need to be familiar with.

Abstract

Digital image data is a bit different to "tidy data" (where every column is a variable and every row an observation) that people may be familiar with. It needs some different approaches to be able to extract useful information. Such image data has become increasingly available and important given the rise of cameras in smartphones, the shift to digital cameras on microscopes and the growth of image data repositories available via the web.

The importance and wide applicability of image analysis led to a new lesson being developed and brought to beta (https://datacarpentry.org/image-processing/). This session will provide a tour of the lesson episodes and allow plenty of time for questions. It will be delivered by a carpentries instructor and an RSE with image analysis skills. At the end of the session, instructors should feel more confident in running a beta test of the lesson.

Interest

This session is aimed at instructors who are considering getting involved in the beta program for the Image Processing with Python lesson. However, it might be of interest to others who'd like to know more about working with image data. Digital images appear in a huge range of research areas such as microscopy in life and materials sciences, medical imaging (e.g. CT scans), large scale remote sensing satellite images and facial / object recognition in a wide range of social sciences research.

[bobturneruk]

Sorry this is getting near the deadline. It'd be great to have some feedback on the above @quist00, @tobyhodges. It's a bit short, but I think that's fine (or even good!) unless I'm missing key details.

[tobyhodges]

Looks good, @bobturneruk. I would only suggest minor changes:

1. It would probably help to mention more prominently that this is a Data Carpentry lesson, e.g. refer to it as "Data Carpentry: Image Processing with Python" or "... a new Data Carpentry curriculum being developed ...", etc
2. Rather than "This session is aimed at instructors who are considering getting involved in the beta program for the Image Processing with Python lesson", I think it will be more immediately clear to say "This session is aimed at instructors who are interested in teaching the Image Processing with Python lesson."
3. Perhaps good to link somewhere to the blog post announcing the curriculum beta?
4. I would move the prior knowledge part to the end - currently I fear it makes it seem a bit too much like a workshop where the lesson will actually be taught, rather than an onboarding for Instructors.

Otherwise, this looks good to go.

[bobturneruk]

Thanks @tobyhodges - that's all really useful. The "prior knowledge" bit is a box of it's own. Perhaps I'll provide shorter summary and link out to the course materials.

[bobturneruk]

Title: Instructor Onboarding for Data Carpentry: Image Processing with Python (beta)

Keywords: onboarding, instructors, images, python

Prior knowledge: A working knowledge of Python and some previous exposure to the Bash shell. The full lesson prerequisites are here https://datacarpentry.org/image-processing/

Abstract

Digital image data is a bit different to "tidy data" (where every column is a variable and every row an observation) that people may be familiar with. It needs some different approaches to be able to extract useful information. Such image data has become increasingly available and important given the rise of cameras in smartphones, the shift to digital cameras on microscopes and the growth of image data repositories available via the web.

The importance and wide applicability of image analysis led to a new Data Carpentry lesson being developed and brought to beta (https://carpentries.org/blog/2022/05/image-processing-beta-announcement/). This session will provide a tour of the lesson episodes and allow plenty of time for questions. It will be delivered by a carpentries instructor and an RSE with image analysis skills. At the end of the session, instructors should feel more confident in running a beta test of the lesson.

Interest

This session is aimed at instructors who are interested in teaching the Data Carpentry: Image Processing with Python lesson. However, it might be of interest to others who'd like to know more about working with image data. Digital images appear in a huge range of research areas such as microscopy in life and materials sciences, medical imaging (e.g. CT scans), large scale remote sensing satellite images and facial / object recognition in a wide range of social sciences research.

[bobturneruk]

I've put this amended version here for the record.

[tobyhodges]

excellent, thank you @bobturneruk. Please let me know if (when 😁) the proposal is accepted and the date/time of the session, and I will do my best to attend and provide support.

[quist00]

Amended looks great. I don't have any further insights to add beyond also keeping me posted on dates and times.

[tobyhodges]

The CarpentryCon session ran on 10th August 2022. A recording of the Instructor Onboarding has been uploaded to The Carpentries YouTube channel.