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# System prepended metadata

title: Notes from RSE Course January

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# Notes from RSE Course January 

**Discussion Topics**
[TOC]

# How should we field questions?
* Having a dedicated contact person to send chat messages to and/or send to the whole group
 
# What should instructors/helpers be doing in breakout rooms?
* giving people answers or observing? Clarify this before going into the breakout room.

# How should breakout rooms be structured?
* groups that were pair-programming were more engaged
* Breakout rooms weren't totally effective. Ways to improve could be:
    * Ice-breakers to get students in breakout rooms comfortable talking to one another

# How can we confirm that students have understood the material?
* Equivalent of green/red notes?
* Summarise "here's what you need to know even if you've not been paying attention" at breakpoints
* Anonymous polls: built-in to Zoom or eg. Slido
  * Emphasise that these are anonymous to students

# What do the students think about the overall structure of the course?
* Some modules are very didactic with not much for students to do
* Some modules have several consecutive exercises with not much teaching in between
* Can we structure the course to have more targeted questions asked by the non-presenting instructor? Often students won't have a specific question but will be confused, and having an instructor to ask "dumb" questions to make them feel comfortable asking really simple things if they don't totally understand.
* Partially completed exercises with some comments that need to be converted into code?

# What do we think about the structure of the course?
* Schedule of 4hrs per day over 2 weeks works better than something more intensive

## Suggestions for material to add
* pandas
* better explanation of decorators
* type hinting
* visualizations
* Does scipy get covered?
* Would there be enough interest and appropriate level for fundamentals of machine learning? Could use end-user friendly packages like `scikit-learn`.
* IDE? pick any, lots of common features and we're already opinionated on things like github. Would make things like debugging  more usable

## Suggestions for material to remove
* Update/remove references to outdated topics/syntax (e.g. python 2)
* meta programming (most of)
* operators (less depth? more general on magic methods?)
* Remove/reduce the RDF/SPARQL ontologies section [📝 JH note - please don't take away my ontologies!!!]

# Misc.
* Can we use our connections with The Carpentries to get an external, education-oriented review of the course?
* We sometimes send out a pre-survey: "how would you rate your skills in coding, data science, whatever? What do you expect to learn from this course? Then post-survey: "Did you learn what you were expecting to?"
  * https://github.com/alan-turing-institute/the-turing-way/blob/master/workshops/boost-research-reproducibility-binder/feedback_form.md
  * Could help set tone for content and/or which exercises to focus on with the cohort
* How to merge back with the UCL fork of the course? James R has been in touch with David Perez-Suarez at UCL about this
* What should the course be? What’s in/out of scope of the course? What are our processes for reviewing PRs and deciding whether they are appropriate?

# Actions
- Vishi to set up a spreadsheet to coordinate updates to lessons
- James R to get in touch with David Perez-Suarez about merging with the UCL fork of the course
- James R to get in touch with Malvika/Toby about moving under the Carpentries umbrella