Coursera Plan!!

[avahoffman]

Breakdown for each module:

1. Overview of what's important for each module (short youtube video)
2. html embedded as core content - can download, copy paste etc
   • If you like to follow along on video, see that linked on youtube HERE.
3. Cheatsheets as a resource/additional reading (linked)
4. Lab becomes embedded as a practice quiz
5. Tweak lab slightly to make quizzes (made with AI, similar to the lab)

Specialization (Each course is 4-15 hrs) (For below, numbers indicate lessons per module)

Course 1

• Intro video for course 1
• Intro / Basic R (2)
• RStudio (1) + Input (2)
• Subsetting (3)
• Reproducibility (1) + AI and programming (1)
• Concluding video

Course 2

• Intro video for course 2
• Summarization (2) + Classes (1)
• Cleaning (2)
• Manipulation (2)
• Esquisse / ggplot (3)
• Ethical sources of data (could mention putting on github if appropriate to share) (1)
• Concluding video

Course 3

• Intro video for course 3
• Factors (1) + Stats (2)
• Output (1) + spatial visualization (1)
• Functions (2)
• Project walk-through and public sources of data (1)
• Concluding video

Common learning objectives for the "bank":

• Handle data in RStudio
• Practice writing and executing R code
• Interpret output and error logging in the R console

[carriewright11]

video ideas:

• talked about focusing on main concepts (so it would be more resilient to change), for cleaning it could be the overall process see (Cleaning data notes SISBID/Data-Wrangling#233) (could talk about overall data analysis process in later videos or something
• could also talk about common errors
• how we actually work (that we look up documentation and iteratively try things and check our work regularly) kind of thing.
• Could also point to other resources and explain what they are
• Could also talk about when we would use covered functions - bigger context
• Or specific topics - like what are useful ways to look at the data for example
• How to use logic to troubleshoot

[avahoffman]

For Quizzes:

• 12 modules
• Each one needs practice quiz and regular quiz. Number of questions doesn't matter.
• Do not repurpose labs into the quizzes. Make from scratch