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Identifying regulation profiles during computer-supported collaborative learning and examining their relation with students' performance, motivation, and self-efficacy for learning

Liesje De Backer (UGent) , Hilde Van Keer (UGent) , Fien De Smedt (UGent) , Emmelien Merchie (UGent) and Martin Valcke (UGent)
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Abstract
The present study unravels profiles of regulators, based on online measures of collaborative learners' adoption of individual-oriented and socially shared metacognitive regulation (SSMR) during asynchronous computer-supported collaborative learning (CSCL). Additionally, it investigates how the regulation profiles are related to students' conceptual understanding after CSCL and to their motivation and self-efficacy for learning. 196 university students participated in the study. Hierarchical and k-means cluster analysis are adopted to identify the regulation profiles, whereas ANCOVA and MANOVA are run to study how the regulation profiles are related to respectively students' performance and learner characteristics. The results revealed three regulation profiles, labelled as 'all-round-oriented and affirming regulator' (AOAR), 'social-oriented and elaborating regulator' (SOER), and 'individual-oriented and passive regulator"(IOPR). The regulation profiles differed significantly in their conceptual understanding, motivation for learning, and self-efficacy beliefs. The current results serve as a stepping stone for lecturers and researchers to design customized metacognitive scaffolds in CSCL-environments and to examine their effectiveness in future intervention studies, advancing both the emerging literature on SSMR and educational practice.
Keywords
Shared regulation, Regulation profiles, Performance, Learner characteristics, Higher education, SOCIALLY SHARED REGULATION, METACOGNITIVE REGULATION, SEQUENTIAL PATTERNS, COLLEGE-STUDENTS, ACHIEVEMENT, CHALLENGES, QUALITY

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Citation

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MLA
De Backer, Liesje, et al. “Identifying Regulation Profiles during Computer-Supported Collaborative Learning and Examining Their Relation with Students’ Performance, Motivation, and Self-Efficacy for Learning.” COMPUTERS & EDUCATION, vol. 179, 2022, doi:10.1016/j.compedu.2021.104421.
APA
De Backer, L., Van Keer, H., De Smedt, F., Merchie, E., & Valcke, M. (2022). Identifying regulation profiles during computer-supported collaborative learning and examining their relation with students’ performance, motivation, and self-efficacy for learning. COMPUTERS & EDUCATION, 179. https://doi.org/10.1016/j.compedu.2021.104421
Chicago author-date
De Backer, Liesje, Hilde Van Keer, Fien De Smedt, Emmelien Merchie, and Martin Valcke. 2022. “Identifying Regulation Profiles during Computer-Supported Collaborative Learning and Examining Their Relation with Students’ Performance, Motivation, and Self-Efficacy for Learning.” COMPUTERS & EDUCATION 179. https://doi.org/10.1016/j.compedu.2021.104421.
Chicago author-date (all authors)
De Backer, Liesje, Hilde Van Keer, Fien De Smedt, Emmelien Merchie, and Martin Valcke. 2022. “Identifying Regulation Profiles during Computer-Supported Collaborative Learning and Examining Their Relation with Students’ Performance, Motivation, and Self-Efficacy for Learning.” COMPUTERS & EDUCATION 179. doi:10.1016/j.compedu.2021.104421.
Vancouver
1.
De Backer L, Van Keer H, De Smedt F, Merchie E, Valcke M. Identifying regulation profiles during computer-supported collaborative learning and examining their relation with students’ performance, motivation, and self-efficacy for learning. COMPUTERS & EDUCATION. 2022;179.
IEEE
[1]
L. De Backer, H. Van Keer, F. De Smedt, E. Merchie, and M. Valcke, “Identifying regulation profiles during computer-supported collaborative learning and examining their relation with students’ performance, motivation, and self-efficacy for learning,” COMPUTERS & EDUCATION, vol. 179, 2022.
@article{8732272,
  abstract     = {{The present study unravels profiles of regulators, based on online measures of collaborative learners' adoption of individual-oriented and socially shared metacognitive regulation (SSMR) during asynchronous computer-supported collaborative learning (CSCL). Additionally, it investigates how the regulation profiles are related to students' conceptual understanding after CSCL and to their motivation and self-efficacy for learning. 196 university students participated in the study. Hierarchical and k-means cluster analysis are adopted to identify the regulation profiles, whereas ANCOVA and MANOVA are run to study how the regulation profiles are related to respectively students' performance and learner characteristics. The results revealed three regulation profiles, labelled as 'all-round-oriented and affirming regulator' (AOAR), 'social-oriented and elaborating regulator' (SOER), and 'individual-oriented and passive regulator"(IOPR). The regulation profiles differed significantly in their conceptual understanding, motivation for learning, and self-efficacy beliefs. The current results serve as a stepping stone for lecturers and researchers to design customized metacognitive scaffolds in CSCL-environments and to examine their effectiveness in future intervention studies, advancing both the emerging literature on SSMR and educational practice.}},
  articleno    = {{104421}},
  author       = {{De Backer, Liesje and Van Keer, Hilde and De Smedt, Fien and Merchie, Emmelien and Valcke, Martin}},
  issn         = {{0360-1315}},
  journal      = {{COMPUTERS & EDUCATION}},
  keywords     = {{Shared regulation,Regulation profiles,Performance,Learner characteristics,Higher education,SOCIALLY SHARED REGULATION,METACOGNITIVE REGULATION,SEQUENTIAL PATTERNS,COLLEGE-STUDENTS,ACHIEVEMENT,CHALLENGES,QUALITY}},
  language     = {{eng}},
  pages        = {{17}},
  title        = {{Identifying regulation profiles during computer-supported collaborative learning and examining their relation with students' performance, motivation, and self-efficacy for learning}},
  url          = {{http://dx.doi.org/10.1016/j.compedu.2021.104421}},
  volume       = {{179}},
  year         = {{2022}},
}

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