Conference proceeding
Probabilistic Motivation Profiles and Student Behaviors in Log Data
ISLS Annual Meeting 2023: Building Knowledge and Sustaining our Community - 17th International Conference of the Learning Sciences, ICLS 2023, Proceedings, pp.1390-1393
2023
DOI: 10.22318/icls2023.847189
Abstract
Motivation is a multi-faceted construct that has complex relationships with behavior. To better understand student motivations in a large introductory statistics course, we cluster different aspects of student motivation and investigate their link to observed student engagement in an online textbook. A soft clustering method reveals three distinct motivation profiles in students: reluctant, motivated, and confident. Membership in the confident group is associated with GPA and financial difficulties, but not with engagement metrics that reflect student choice, such as time spent. Contrary to the simple hypothesis that better motivation will lead to higher engagement, students with “reluctant” and “motivated” profiles seem to spend similar amounts of efforts for course preparation but spend less of it progressing with learning, and more time struggling.
Details
- Title: Subtitle
- Probabilistic Motivation Profiles and Student Behaviors in Log Data
- Creators
- Gahyun Sung - Harvard University
- Resource Type
- Conference proceeding
- Publication Details
- ISLS Annual Meeting 2023: Building Knowledge and Sustaining our Community - 17th International Conference of the Learning Sciences, ICLS 2023, Proceedings, pp.1390-1393
- DOI
- 10.22318/icls2023.847189
- ISSN
- 1573-4552
- Language
- English
- Date published
- 2023
- Academic Unit
- Psychological and Quantitative Foundations
- Record Identifier
- 9984825527202771
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