Here's an example: https://youtu.be/eHwy-neG_W8?t=791

It's from an introductory course on Algorithms; the dataset is the students' programming assignments, rated for similarity by an off-the-shelf similarity scorer.

This heatmap example is presented in the class on Kruskal's algorithm. We normally think of Kruskal's algorithm as a method for finding a minimum spanning tree, but it can also be thought of as building a classification tree -- which means we can use it for seriation. It's not the best method for seriation by any means, but it's nice just to see it used in this unconventional way.

It's always fun showing this in class, on the coursework that the students submitted just a few weeks ago!

I was a grad student at a major State university. We had a “defensive” grading rubric which caused cheating to be self-defeating. We’d do analyses like this to visualize the cheaters, and try to predict the GPA average of the class (section). Our goal was to speed up or slow down the material to make sure the largest number of students actually learned the core topics of the course and didn’t flunk. (Our worst case scenario was the class of student who’d “get it” at the end of the semester — but too late to pass.)

Very nice video!

See http://www.brendangregg.com/HeatMaps/subsecondoffset.html

Also compare to DSMs which have the same problem where column and row order can matter a lot to making the diagram clearer: https://web.mit.edu/eppinger/www/SDE-MIT/DSM_Book.html