Abstract
For decades, self-report instruments – which rely heavily on students’ perceptions and beliefs – have been the dominant way of measuring motivation and strategy use. Eventbased 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.
Original language | English |
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Pages (from-to) | 140-163 |
Number of pages | 24 |
Journal | Frontline Learning Research |
Volume | 8 |
Issue number | 3 |
DOIs | |
Publication status | Published - 30 Mar 2020 |
Bibliographical note
Special Issue: The Promise and Pitfalls of Self-report data for motivation and strategy use.Funding
This work is part of the project ?SURFnet Learning Analytics Hoger Onderwijs?, supported by the National Control Unit Educational research (NRO) (project-id 405-17-851).
Keywords
- Event-Based Measures
- Online Trace Data
- Self-Regulated Learning
- Self-Report Measures