Using Coherence Analysis to Characterize Self-Regulated Learning Behaviours in Open-Ended Learning Environments

Abstract

Researchers have long recognized the potential benefits of using open-ended computer-based learning environments (OELEs) to study aspects of students’ self-regulated learning behaviours. However, measuring self-regulation in these environments is a difficult task. In this paper, we present our work in developing and evaluating coherence analysis (CA), a novel approach to interpreting students’ learning behaviours in OELEs. CA focuses on the learner’s ability to interpret and apply information encountered while working in the OELE. By characterizing behaviours in this manner, CA provides insight into students’ open-ended problem-solving strategies as well as the extent to which they understand the nuances of their current learning task. To validate our approach, we applied CA to data from a recent classroom study with Betty’s Brain. Results demonstrated relationships between CA-derived metrics, prior skill levels, task performance, and learning. Taken together, these results provide insight into students’ SRL processes and suggest targets for adaptive scaffolds to support students’ development of science understanding and open-ended problem solving skills.