For decades, self-report instruments – which rely heavily on students’ perceptions and beliefs – have been the dominant way of measuring motivation and strategy use. Event-based measures based on online trace data arguably has the potential to remove analytical restrictions of self-report measures. The purpose of this study is therefore to triangulate constructs suggested in theory and measured using self-reported data with revealed online traces of learning behaviour. The results show that online trace data of learning behaviour are complementary to self-reports, as they explained a unique proportion of variance in student academic performance. The results also reveal that self-reports explain more variance in online learning behaviour of prior weeks than variance in learning behaviour in succeeding weeks. Student motivation is, however, to a lesser extent captured with online trace data, likely because of its covert nature. In that respect, it is of importance to recognize the crucial role of self-reports in capturing student learning holistically. This manuscript is ‘frontline’ in the sense that event-based measurement methodologies with online trace data are relatively unexplored. The comparison with self-report data made in this manuscript sheds new light on the added values of innovative and traditional methods of measuring motivation and strategy use.

Reference:
van Halem, N., van Klaveren, C., Drachsler, H., Schmitz, M., Cornelisz, I. (2020). Tracking Patterns in Self-Regulated Learning Using Students’ Self-Reports and Online Trace Data. Frontline Learning Research Vol. 8 no 3 special issue (2020) 142 – 165 ISSN 2295-3159