Main points of the paper

[mbonsma]

These are @joelostblom's and my ideas of what could be our main points. Feel free to edit / comment!

• Intro & Motivation

  • actual skills for students: coding + data analysis (Data carpentry paper)

  • What’s lacking in traditional teaching format

  • they do real science in a team

  • get to explore the cutting edge of tools + methods(Data carpentry paper)

    • How team work is closer to what is done IRL

  • This is a good idea because reasons:

  • student motivation

  • actual skills for students: coding + data analysis Data carpentry paper

  • they do real science in a team - get to explore the cutting edge of tools + methods (Data carpentry paper)

  • making use of 'neglected' or underused open datasets (part of christie's motivation)

  • reproducible research skills (Rundel paper)

  • Overview of what other people are doing:

  • other courses like this

  • other research on education methods and techniques

  • explain our choice of tools and their role (mention that there are other ways, e.g. jupyter notebooks) (Rundel paper)

• Methods

  • This is what we did (details of implementation)
  • teaching structure
    • How we did it first then we modified it in this way for the second year, and why we did this
  • topics/lessons
  • assessment
  • group project

• Results

  • These are our lessons learned (Library carpentry paper)
  • what we will change for next time
  • what we recommend (this would maybe be more in conclusions?)

• Conclusion Step-by-step guide / roadmap (Library carpentry paper)

  • how to prepare
  • when to do things
  • who to get involved
  • things to think about

[linamnt]

Should we at some point we should justify our choice of tools used/taught (R, Tidyverse, Git/GitHub, knitr etc. over alternatives). Maybe under the first point, how each of these contributes to reproducible research skills?

[linamnt]

This looks great btw! :)

[joelostblom]

@linamnt Added

[joelostblom]

Keep in mind that we choose the following points to be the paper focus (from the brainstorming in #1).

1. As a tool/process for other groups to try and emulate
2. (originally point 3) As an argument to show that hands on, project focused courses should be the primary types of style that upper level courses have, based on the student feedback
3. (originally point 4) As resources for how to create a hands on data analysis course, a sorta "lessons" learned.

As I mentioned in #1, I think all of these can be included in different parts (1 in intro & results, 2 in conclusions/recommendations, and 3 in results).

[joelostblom]

I structured a bit more and added some of our references from #5 where I think they will be the most useful (without having fully ready all papers yet...).

[lwjohnst86]

For now, we'll deal with this after submitting to JOSE. These points will be used more for the results paper.