Topic Extraction from Item-Level Grades

Titus Winters, Christian Shelton, Tom Payne, and Guobiao Mei

The most common form of dataset within the educational domain is likely the course gradebook. Data mining on the assignment-level scores is unlikely to provide meaningful results, but a matrix recording scores for every student and every question may provide hidden insight into the workings of a course. Here we will investigate collaborative filtering techniques applied to such data in an attempt to discover what the fundamental topics of a course are and the proficiencies of each student in those topics.


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