Project information
Multimodal learning analytics to study self-regulated learning processes within learning management systems
- Project Identification
- GA21-08218S
- Project Period
- 4/2021 - 3/2024
- Investor / Pogramme / Project type
-
Czech Science Foundation
- Standard Projects
- MU Faculty or unit
- Faculty of Arts
- Keywords
- self-regulated learning, learning analytics, multimodal analytics, learning management systems, process mining
The research project focuses on the exploration of the self-regulated learning (SRL) processes and strategies followed by university students while studying within a learning management system (LMS). The project is based on a multimodal approach to the collection and analysis of data, aiming to combine different data collection techniques in order to capture various modalities through which students can learn within LMS. Specifically, four data types will be used in this project: data on student behaviour in LMS (logs), data from questionnaires focusing on various dimensions of SRL, qualitative data capturing the content of learning activities and materials in LMS, and data from an experiment focused on tracking student eye movements while studying in LMS. The process-oriented analytical techniques will play a dominant role in the data analysis. The project will contribute to the improvement of current methods and theoretical models of SRL in LMS. The main outputs of the project are six articles in top international scientific journals.
Sustainable Development Goals
Masaryk University is committed to the UN Sustainable Development Goals, which aim to improve the conditions and quality of life on our planet by 2030.
Publications
Total number of publications: 13
2022
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Support of Self-Regulated Learning in Blended Courses
Year: 2022, type: Appeared in Conference without Proceedings
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Využívání e-learningu na vysoké škole : Skladiště, učebnice, či funkční podpora seberegulovaného učení?
Year: 2022, type: Appeared in Conference without Proceedings
2021
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Patterns of academic success : data-driven typology of university students' approaches to learning, motivation, and academic achievement
ICERI2021 Proceedings, year: 2021