worldbank/dime-r-training

Feedback from Nov-2020 course

Closed this issue · 4 comments

luisesanmartin commented

The course was held online. This feedback comes from the anonymized feedback survey results and from observations made by the DIME Analytics team that have not been applied yet to the materials.

  • Intro 2 session was the one attendants found the least useful. For future editions, we could consider spreading its content in the other sessions and increase the time of those.
  • The contents for Intro I, Intro II, and Data analysis are currently too much for 90 minutes sessions. For future editions we need to consider which ones we'll be moving to the annex.
  • Switching between the slides and the R window increased the difficulty of following the session. Some options:
  1. Keep R/RStudio and the slides on the same screen at the same time
  2. Focus on live code instead of the contents of the slides
  3. Embed R in the presentation -- there's a way to do this if the presentations are html
  • Edit presentations so the code section doesn't use the fira font. The problem with it is that it merges sets of two characters like <- or == into a single one
  • Session 1: exercise 7 was confusing. Consider dropping it or adding additional instructions to clarify
  • Session 2: before explaining why we usually don't use the equivalents to cd() and clear all add a slide explaining why we don't want previous objects to be loaded when we start a new session
  • Session 2: add "raising hands" example when explaining apply() -- ask Luis Eduardo about this
  • Session 2 slide 47: change image for loading package from stargazer to tidyverse
  • Session 1: mention explicitly that this training assumes knowledge in Stata
luisesanmartin commented

Additional comments for the presenters:

  • For session 1, explain before using the command print() that its content can use double or single quotes, and the difference between those

  • For every session: remind participants to save their edits in the scripts they write

  • Session 2, loading data exercise (4): explain why is it preferable to load data using code than point-and-click

  • Session 2: make sure every participant loads tidyverse before attempting to use the pipes

  • Session 1: explain the difference of running code from the script editor and from the console

  • Session 1, subset exercise:

    Tell people to do Ex 2 (subset data)
    Ask someone what they see (the full data)
    Ask someone else to explain what that's happening (not assigned to an object)
    Ask someone else how this can be fixed (using the assignment operator)

luizaandrade commented
  • analysis session: using weights
  • cheatsheet with commonly used packages
  • time management was a problem: leave more time for people to complete their own exercises
  • share code for people to start working from and build on
  • share slides ahead of time
  • leave homework/assignment to be completed: we can tell people that if they do something, we can give them some feedback on their code
luisesanmartin commented

I'm writing here tasks based on the previous comments on this issue:

Intro 1 @luisesanmartin

  • Shorten or move to the Annex contents in Intro 1
  • Exercise 7: add clarifications or consider dropping
  • Mention at the beginning that this training assumes knowledge from Stata

Intro 2 @luisesanmartin

  • Analyze which contents of Intro 2 session will be moved to previous sessions
  • Move Intro 2 session to the last
  • Shorten or move to the Annex contents in Intro 2
  • Add slide(s) explaining why we don't usually use the equivalents of cd() and clear all in R, and why we don't usually want objects from previous sessions to be loaded in the environment when we start a new session
  • add "raising hands" example when explaining apply()
  • slide 47: change image for loading packages from stargazer to tidyverse

Data processing @RRMaximiliano

  • Add a slide on what RProjects are and use projects to load the data
  • Mention that packages need to be loaded in every session
  • Shorten or move to the Annex contents in Data Analysis

General

luisesanmartin commented

All of these suggestions were addressed in the commits we produced for the April 2021 edition