The bioc-intro workshop was organised at taught at the Center for Computational Biomedicine, Harvard Medical School, Boston on the 3 - 7 April 2023. A total of 35 people total registered and the attendance was 17 on day 1, 12 on day 2, 10 on day 3 and 8 on day 4.
Here's both feedback from the post-survey and some thoughts from the trainer and organiser, Chris Magnano and Jaclyn Mallard.
Post-Survey Feedback (n=7):
Overall, feedback from participants was almost universally positive. 5/7 felt the workshop exceeded expectations, with 1 saying it "met all" and 1 saying it "met most".
Most participants said that their skill level analyzing data with R and Bioconductor went from "Novice" to "Basic", which I would say is a good but not over-confident result from a single workshop.
When asked which parts of the workshop were most valuable almost everyone mentioned the data visualization lesson, the majority mentioned the manipulating data lesson, and about a third mentioned the tabular data lesson.
When asked what participants felt least confident about, there was no consensus, with single participants mentioning visualization, base R commands, and dplyr.
Finally, one participant mentioned that they would appreciate more resources for practicing ggplot after the workshop is finished.
A nice quote I wanted to share:
"I also love the training materials. Very organized and simple to follow and practical."
My thoughts
We gave this workshop in 4 3-hour sessions over zoom. The registration to no-show rate was fairly standard for other zoom workshops we and others at HMS have put on. We had some drop off from session to session, which was exacerbated by some folks during the first session who I believe just wanted to grab the materials, the sessions being very long for zoom sessions, and that we were hosting the sessions in the late afternoon right as we got our first days of warm, sunny Spring weather.
These are materials are well-made and very polished, with a nice balance of exercises throughout. Participants were engaged and really seemed to get a lot out of it. I thought that the spreadsheet data and the manipulating data lessons are especially well done.
I found the materials easy to prep for as an instructor, and the estimated lesson times were mostly spot on - I didn't feel like I had to skip anything due to running out of time.
It would be nice if the summary/schedule page was expanded to include some overall learning objectives and a description of the workshop, both for participants to see and for instructors to have a blub to advertise the workshop with.
It might also be useful to split some of the longer lessons up into multiple smaller lessons. The data manipulation lesson especially will probably be broken up by at least a break or two (I had to split it across multiple days). Choosing a good breakpoint or two to split the lesson up into 2-3 smaller lessons would make these points consistent between instructors and would allow some design around where participants might need a post-break refresher to get back into things.
Overall, this was a great workshop to teach and it hits on important skills for working with real-world data.
The bioc-intro workshop was organised at taught at the Center for Computational Biomedicine, Harvard Medical School, Boston on the 3 - 7 April 2023. A total of 35 people total registered and the attendance was 17 on day 1, 12 on day 2, 10 on day 3 and 8 on day 4.
Here's both feedback from the post-survey and some thoughts from the trainer and organiser, Chris Magnano and Jaclyn Mallard.
Post-Survey Feedback (n=7):
Overall, feedback from participants was almost universally positive. 5/7 felt the workshop exceeded expectations, with 1 saying it "met all" and 1 saying it "met most".
Most participants said that their skill level analyzing data with R and Bioconductor went from "Novice" to "Basic", which I would say is a good but not over-confident result from a single workshop.
When asked which parts of the workshop were most valuable almost everyone mentioned the data visualization lesson, the majority mentioned the manipulating data lesson, and about a third mentioned the tabular data lesson.
When asked what participants felt least confident about, there was no consensus, with single participants mentioning visualization, base R commands, and dplyr.
Finally, one participant mentioned that they would appreciate more resources for practicing ggplot after the workshop is finished.
A nice quote I wanted to share:
My thoughts
We gave this workshop in 4 3-hour sessions over zoom. The registration to no-show rate was fairly standard for other zoom workshops we and others at HMS have put on. We had some drop off from session to session, which was exacerbated by some folks during the first session who I believe just wanted to grab the materials, the sessions being very long for zoom sessions, and that we were hosting the sessions in the late afternoon right as we got our first days of warm, sunny Spring weather.
These are materials are well-made and very polished, with a nice balance of exercises throughout. Participants were engaged and really seemed to get a lot out of it. I thought that the spreadsheet data and the manipulating data lessons are especially well done.
I found the materials easy to prep for as an instructor, and the estimated lesson times were mostly spot on - I didn't feel like I had to skip anything due to running out of time.
It would be nice if the summary/schedule page was expanded to include some overall learning objectives and a description of the workshop, both for participants to see and for instructors to have a blub to advertise the workshop with. It might also be useful to split some of the longer lessons up into multiple smaller lessons. The data manipulation lesson especially will probably be broken up by at least a break or two (I had to split it across multiple days). Choosing a good breakpoint or two to split the lesson up into 2-3 smaller lessons would make these points consistent between instructors and would allow some design around where participants might need a post-break refresher to get back into things.
Overall, this was a great workshop to teach and it hits on important skills for working with real-world data.