Combining Self-Reported and Observational Measures to Assess University Student Academic Performance in Blended Course Designs

Abstract

This study combined the methods from student approaches to learning and learning analytics research by using both self-reported and observational measures to examine the student learning experience. It investigated the extent to which reported approaches and perceptions and observed online interactions are related to each other and how they contribute to variation in academic performance in a blended course design. Correlation analyses showed significant pairwise associations between approaches and frequency of the online interaction. A cluster analysis identified two groupings of students with different reported learning orientations. Based on the reported learning orientations, one-way ANOVAs showed that students with understanding orientation reported deep approaches to and positive perceptions of learning. The students with understanding orientation also interacted more frequently with the online learning tasks and had higher marks than those with reproducing orientation, who reported surface approaches and negative perceptions. Regression analyses found that adding the observational measures increased 36% of the variance in the academic performance in comparison with using self-reported measures alone (6%). The findings suggest using the combined methods to explain students’ academic performance in blended course designs not only triangulates the results but also strengthens the acuity of the analysis.