If you have ideas or would like to contribute to the discussion, please do so in the issues tracker. Below are the key topics raised to date and the general state of each discussion.
- Could continuous exposure to computation and data manipulation throughout a bachelor program, coupled with compelling
topic specific problems, be more effective than dedicated bioinformatics/statistics courses?
- Pull material out of a vacuum and into real(ish) world context.
- Empower students to begin using more sophisticated tools by guiding them through the initial learning curves.
- Implementation may involve first year core course (e.g., semester-long Data Carpentryesk course, perhaps called 'Data Literacy Skills for Biological Sciences'), followed by computation modules incorporated into later course labs.
- 'Competency' is very hard without significant time investment.
- We need curricula road maps; identify the short, medium, and long term learning objectives, and make a plan to get there.
- Can't assume current faculty will be able to do this on their own, so training TA's or having dedicated personnel may be important
- csteachingtips (or via Twitter)
- StackExchange Computer Science Educators channel
- Is there some cost associated with teaching undergrads the traditionally memory intensive biology content at the same time as the more logic focused computational content?
- How do we deal with coding fear?
- The very first skill students require is to not be terrified
- Semester long SWC/DC-esk course(s) very early
- Domain-specific skills will be important and even 'bioinformatics' is broad, so what commonalities can be extracted
to give students the best framework for branching into more specialized topics later?
- Basic coding skills
- Basic shell tools
- Focus on what to do with tabular data, statistics, modelling, noisy matrices
- Teach students to troubleshoot and to learn from manuals/forums/peers/etc
- Do's and don'ts for basic script design (antipatterns)
This repostitory has been created as an extension of a 'Birds of a Feather' discussion at the 2017 iEvoBio conference, where ideas where bandied about for building new undergraduate bioinformatics curricula and teaching undergraduates (in any field) computing generally. We wanted a centralized place to put those ideas, but also wanted to make sure they were accessible to the broader community. Thank you GitHub :)