HP Learning Lab: Using machine learning to measure student learning by North-west University
Channel: NewMediaConsortium
Date: 2011-10-18

For students from backgrounds that were excluded from formal learning in the past — such as many from the historically disadvantaged communities of South Africa — the path to STEM+ excellence is steep. Conventional learning environments do not account for the strengths and weaknesses of such students. North-West University will quantify these differences in capabilities by measuring behaviors of students engaged in real-world learning tasks.

Electronic courseware will be instrumented to measure — and subsequently improve — the ways in which students utilize various resources in tutorial sessions. Methods from statistics and machine learning will be employed to gain an understanding of the relationships between student behaviors and the different performance measures. Clustering will be used to extract meaningful groups of student behaviors; classifiers will be designed and analyzed to determine student behaviors that predict successful learning, and outputs from these analyses will be used to suggest learning interventions.

The proposed work will extend current research of our Counseling Psychology department on "the first year student experience in SET learning." Because South African students come from many diverse backgrounds, this study will offer new insights on how the learning patterns of different students are conditioned by their earlier learning experiences.