Princeton University Library Catalog

Experimental Measures of Difficulty for Princeton Courses

White, Joseph [Browse]
Senior thesis
Martonosi, Margaret R. [Browse]
Princeton University. Department of Computer Science [Browse]
Class year:
Summary note:
Course evaluations at Princeton lack numerical difficulty measures, but the textual evaluations are rich with student commentary about course difficulty. This suggests that there is an opportunity to generate a numerical difficulty score from the textual evaluations. In this project, we collect a data set via scraping and test several variations of a “bag of words” approach with the goal of determining whether such an approach holds promise as a difficulty measure. These variations are evaluated by testing their correlation with the number of pages of weekly reading assigned in a course. Surprisingly, the correlation is negative, perhaps because STEM courses are perceived as difficult and are prone to lighter reading loads. As a result, a research agenda is suggested for similar tools that can complement human academic advisors in helping students to choose better schedules.