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I (@ewallace) delivered to the EASTBIO PhD program in Scotland, 2022-12-06. We had about 18 people on the zoom call, 18 signed in. These are mostly biologists, some code. Sio Carroll was helper. Lesson was recorded so maybe there will be more feedback later?
Overall good and positive. We compressed into a 2.5hr lesson so did very little on Collaboration and nothing on Manuscripts (less appropriate for 1st year PhD students). I made it clear that we were giving an introduction / overview and they would need to come back to material for the details. Students were engaged in breakout rooms and in the collab doc, but didn't turn on cameras or speak out much.
Today the intro discussion "What can go wrong in research computing" covered a lot about data loss. It prepared well for the next Data Management episode.
A 3rd-year PhD student spoke out about how useful these tips were and how they wish they'd adopted them in the 1st year. That was helpful - we didn't have a designated helper this time, so this was an added bonus helper.
I felt that in delivering this lesson some of the places where DOIs and licences come in are not best placed. They break the flow.
The software episode could have as a key outcome "all data analysis is code". There's also a bigger picture that "code is data" at least for the purposes of data management. I'm thinking about how to address that in pull requests.
Evaluation and Feedback
Please list one thing you liked or found particularly useful
really like this interactive document+2
i thought it was nice and interactive with the use of the document and breakout rooms
I liked knowing that I'm not alone with having difficulties with organizing data, talking to other students was helpful
i liked the level of interactivity+1
Could have been quite a dry topic, but the way information was delivered was engaging. I will 100% be making a change log!
I thought a great range of information was provided, and I enjoyed the interactive component of the workshop
The interactive document gives a good opportunity to collaborate
Please list another thing you found less useful, or that could be improved
Would have liked a little bit more information about tracking changes in Git, but that would probably fall into another session about using Git properly
some people seemed overwhelmed by the interactive doucment, so some way of identifying those who are comfortable and ensuring there is at least one in each breakout room to act as a scribe
Though this document may stimulate more engagement from people who might not engage otherwise, I do feel like turning on the mic and speaking helps to create a more active environment. Then again, asking for people to speak up may result in a silent minute. It's a difficult balance...
The text was updated successfully, but these errors were encountered:
I (@ewallace) delivered to the EASTBIO PhD program in Scotland, 2022-12-06. We had about 18 people on the zoom call, 18 signed in. These are mostly biologists, some code. Sio Carroll was helper. Lesson was recorded so maybe there will be more feedback later?
Collaborative document: https://pad.carpentries.org/good-enough-practices-EASTBIO-2022-12-06
Instructor thoughts
Overall good and positive. We compressed into a 2.5hr lesson so did very little on Collaboration and nothing on Manuscripts (less appropriate for 1st year PhD students). I made it clear that we were giving an introduction / overview and they would need to come back to material for the details. Students were engaged in breakout rooms and in the collab doc, but didn't turn on cameras or speak out much.
Today the intro discussion "What can go wrong in research computing" covered a lot about data loss. It prepared well for the next Data Management episode.
A 3rd-year PhD student spoke out about how useful these tips were and how they wish they'd adopted them in the 1st year. That was helpful - we didn't have a designated helper this time, so this was an added bonus helper.
I felt that in delivering this lesson some of the places where DOIs and licences come in are not best placed. They break the flow.
The software episode could have as a key outcome "all data analysis is code". There's also a bigger picture that "code is data" at least for the purposes of data management. I'm thinking about how to address that in pull requests.
Evaluation and Feedback
Please list one thing you liked or found particularly useful
Please list another thing you found less useful, or that could be improved
The text was updated successfully, but these errors were encountered: