Using the Motivated Strategies for Learning Questionnaire (MSLQ) to identify Latent Profiles of Online Learners

• In Event: Data-Driven Insights in Online Learning

Abstract

The study used the Motivated Strategies for Learning Questionnaire (MSLQ) to identify latent profiles of online motivated learning strategies and examine their relationships with students’ predicted grades (PGs) and grade point averages (GPAs). 1,392 students taking online courses at a USA university were asked to predict their course grade and complete the MSLQ. GPAs were obtained from the university records. A three-step latent profile analysis with PG as a covariate and GPA as a distal outcome yielded a four-profile optimal solution: Average (38.65%), Below-Average (30.60%), Above-Average (24.35%), and Well-Below-Average (6.4%). PGs significantly predicted profile memberships, which, in turn, significantly predicted student GPAs. Findings underscore considering individual differences and using the identified subgroups to tailor the support for optimal learning outcomes.

Authors

• Diana L. Mindrila, University of West Georgia

• Li Cao, University of West Georgia