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dc.contributor.authorDever, Daryn A.
dc.contributor.authorSonnenfeld, Nathan
dc.contributor.authorWiedbusch, Megan D.
dc.contributor.authorAzevedo, Roger
dc.identifier.citationDever, D. A., Sonnenfeld, N., Wiedbusch, M. D., & Azevedo, R. (2023). Identifying transitions between self-regulated learning operations during game-based learning. In Blikstein, P., Van Aalst, J., Kizito, R., & Brennan, K. (Eds.), Proceedings of the 17th International Conference of the Learning Sciences - ICLS 2023 (pp. 1106-1109). International Society of the Learning Sciences.en
dc.descriptionShort Paperen
dc.description.abstractSelf-regulated learning (SRL) is essential while learning with a game-based learning environment (GBLE) to effectively interact with instructional materials, monitor and regulate SRL strategy use, and increase domain knowledge. The field of SRL has had little progress in understanding how learners temporally deploy SRL operations, including Searching, Monitoring, Assembling, Rehearsing, and Translating (SMART; Winne, 2018) , during game-based learning. This study recruited 56 undergraduate students to play Crystal Island, a GBLE focused on increasing microbiology domain knowledge. Using both log-file and eye-tracking data, learners’ SMART operations were captured as they completed the game. Results found that learners engaged in Searching and Assembling/Rehearsing significantly more than any other operations. Transition matrices revealed that while some transition sequences were detrimental to learning, directly monitoring after assembling/rehearsing information were positively related to learning gains. These results have implications for designing GBLEs whose features simultaneously promote and discourage the sequential deployment of SMART operations.en
dc.publisherInternational Society of the Learning Sciences
dc.relation.ispartofProceedings of the 17th International Conference of the Learning Sciences - ICLS 2023, pp. 1106-1109
dc.subjectLearning Sciencesen
dc.titleIdentifying Transitions Between Self-Regulated Learning Operations During Game-Based Learningen
Appears in Collections:ISLS Annual Meeting 2023

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