Sparse Factor Analysis for Learning and Content Analytics

Developed at Rice University, SPARFA (short for SPArse Factor Analysis), is an analytical tool for large educations datasets where students interact with homework and test questions.  SPARFA uses powerful statistical models to decompose educational data as consisting of a small number of educational concepts. From the concept-centric view of the data, SPARFA perform two important educational tasks:

1) Learning Analytics: SPARFA analyzes educational data to determine how well students have mastered various educational concepts.
2) Content Analytics: SPARFA additionally educational test items to determine which concepts are related to various test items.

By performing these tasks, SPARFA automatically enables a number of important educational tasks, such as providing feedback to students, instructors, and educational content authors in order to improve the educational experience.