Open psteinb opened 3 years ago
So I guess, my question is what to do about this? Is this something being discussed among other instructors and lessons?
Ah, the timing question!
I would say is that it's important to set realistic timings, which can only really be arrived at by teaching the material a few times and recording how long it took. As far as I know there's no mechanism to record this easily. However, unrealistically short timings are prevalent throughout the carpentries' lesson, but this is demotivating for both instructors and learners.
I brought this up for the shell lesson https://github.com/swcarpentry/shell-novice/issues/928 and we had a few timings reported as comments on the issue.
Great comment @gcapes which I totally agree with. And I believe you put your finger right where it hurts: if the frontmatter lists a time which is unreasonable, this is a problem for me. So, how about two radical ideas:
only include those times in the front matter which are based on at least 10 timing measurements (e.g. their mean/median value)
rename these two fields:
---
title: "Classification by a Neural Network using Keras"
likely_teaching: 30
likely_exercises: 20
We could and should discuss facilities in the lesson template which support people to record their timings (and submit them through a PR). Because only this view of a bunch of numbers (or summary statistics thereof) can provide me with a feeling of how long this module normally takes to teach. And normal here not only refers to the name of a distribution, but also to conveying and conceiving an expectation.
While working on our deep-learning-intro lesson, the data scientists in us bumped our heads onto the question how to log individual teaching times per teaching module in the current lesson setup. The quick hack we came up with was to add a comment to the
teaching
field in the jekyll front matter.For example, something like this:
For me as an instructor, a distribution of times helps tremendously to establish a trustworthy reference.
See also: https://github.com/carpentries-incubator/deep-learning-intro/issues/124