26 September 2022

Meeting Info

This is the UK Carpentry Community space for the UK Carpentry instructors, helpers and workshop coordinators (or anyone involved in training tech to researchers in general and outside of the UK) to get to know each other better, update the commmunity about developments, discuss issues and ideas, and encourage collaboration.

During these meetings, we will be conforming to The Carpentries Code of Conduct.

Meeting schedule: meetings happen on 4th Monday each month, 16:00-17:00 UK time, BST (UTC+1) or GMT (UTC+0) depending on the time of the year

Meeting details are shared via local-uk mailing list and The Carpentries community calendar.

Zoom URL: https://zoom.us/j/95360073649

Meeting Minutes

  • Chair: Mario Antonioletti
  • Timekeeper:
  • Notetaker: Phil Reed

Notetaker:

Agenda

  1. Assign notetaker & timekeeper
  2. Sign in & ice-breaker
  3. Review of actions
  4. Announcements
  5. Guest speaker + Q&A
    • Sarah Jaffa, UCL - "Silent disco teaching (self paced/flipped classroom)"
  6. Instructor Training checkout questions
  7. Wrap-up/AOB

Sign-in

Name/pronoun if you like/ institution / optionally put "(checkout)" if you are here for the Instructor Training checkout:

  1. Mario Antonioletti (he/his), SSI/EPCC/University of Edinburgh
  2. Phil Reed (he/him), University of Manchester
  3. Jonathan Stoneman (he/him) freelance trainer
  4. Matt Bawn University of Leeds (Checkout)
  5. Sarah Jaffa (she), UCL
  6. Andrew Walker (he/him), Oxford
  7. Colin Sauze (he/him), Aberystwyth University/Supercomputing Wales
  8. Juan Herrera (he/him), EPCC at The University of Edinburgh.
  9. Lucia Michielin (she/her), Centre for Data Culture and Society Edinburgh University
  10. James Byrne, British Antarctic Survey (Checkout)
  11. Nilani Ganeshwaran, University Of Manchester
  12. Winfred Gatua (she/her), University of Bristol
  13. James Allsopp, University of Birmingham (Checkout) …

Notes

Announcements

  • 17-20 October In person Data Carpentry in Edinburgh https://edcarp.github.io/2022-10-17-Data-Carpentry-Social-Science/
  • Phil talked about the Carpentry@Home curriculum development and communication.
  • Nilani and Phil (and another colleague Carlene) working on in-person Library Carpentry workshops again soon (SSI Fellowship). Series starting November, three over the year for the N8 group. Joining their community forum to make sure they have a place to embed their new skills. Considering follow-up sessions on Zoom (new idea). We may be looking for one helper.
    • Colin suggesting hacky hour follow-up as suggested in handbook. However, you tend to get the people who need the least help, not the most.
    • Sarah suggests talking to Alicia for her experience.
    • Jonathan is member of instructor development committee where this is much discussed.

Guest speaker Sarah Jaffa (UCL)

“Silent disco teaching (self paced/flipped classroom)”

Slides

Thinking about a possibily better or just different way to structure (online?) coding teaching.

Been an RSE since August, before was astrophysist writing code in C++ and Python. Attended talk on making code sharable, interesting delivery.

Common problems with teaching coding:

  • Different level of coding experience
  • Different research disciplines
  • Different learning styles

Words like "beginner/intermediate/novice" are meaningless without context. People get disengaged if you show them too much that's not relevant to their work. Some are used to collaboration and some really not. Online gives additional challenges (though helps with some).

Suggested flip classroom, self-placed learning. BYO[Code/Data/Software]. "Silent Disco" learning. Course plus blog on SSI website. Use Git branches to store the major steps/sections of the course so you can jump ahead to catch up.

Generalising the structure:

  • A small number of general topics, each broken down
    • short presentation on theory; discussions; independent time
  • Come back together a few times a day to discuss progress, challenges
  • Work together on small exercises to learn from each other
  • An example data set and code at each level to make sure those who get stuck can progress

Evaluating (looking for our help today)

  1. Is this just good for my [Sarah's] particular way of learning? Would others enjoy as much?
  2. How would this work in person instead of online? Over mulitple days?
  3. How would this work for other topics? How to group the skills/topics into neat discussion/theory blocks
Discussion

Matt: Would this align with set pegagogy from The Carpentries?

  • Keen on live coding in Carpentries, trying to get people to type themselves.
  • Could fit in parallel to Carpentries curricula.
  • Can use stronger people dispersed with weaker people, get them to become helpers.

Mario: If you did have your own code, would you fork the repository?

  • Used as inspiration. Could be harder on the instructor but gives more value to learners' own research.

Colin: What is the average level of people on this? Might be better for those who already have code to publish, perhaps Carpentries better for complete novice.

  • Prerequistes for people who have written some code already. Would be very different if you were teaching people to code. Would this work?
  • Could work for the huge range of intermediate level.
  • Colin tried a hybrid of this in the summer. Some Carpentries, some bring your own data… took 5 days total. Was in-person.

Instructor Training checkout questions

Matt: If you have 5-7 students per helper, that doesn't extend to undergraduate cohorts. How to do this?

  • Breakout rooms can help her. Helpers can have more than one breakout room.
  • Easier to get people to work together around a table (in person), on longer courses, especially if they are in the same groups.
  • Zoom breakout rooms sometimes work, sometimes they sit around in silence.
  • Can label Zoom rooms as "more talking room", "less talking room", "quiet room", and let people move between rooms for themselves. Can have multiple of each.

James A: Waiting to see Sarah's sessions in practice, making reproducable code, great for more advanced users. Want a group of student to do a Kaggle course for machine learning.

Select a repo