# 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 Would make things like debugging more usable ## Suggestions for material to remove * Update/remove references to outdated topics/syntax (e.g. python 2) * meta programming (most of) * operators (less depth?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