Using Educational Data Mining to Identify and Analyze Student Learning Strategies

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dc.contributor.authorAllen, Gove
dc.contributor.authorDavies, Randy
dc.contributor.authorBall, Nicholas
dc.contributor.authorAlbrecht, Conan
dc.contributor.authorBakir, Nesrin
dc.date.accessioned2019-01-02T23:36:47Z
dc.date.available2019-01-02T23:36:47Z
dc.date.issued2019-01-08
dc.description.abstractThis paper explores student learning strategies in an introductory spreadsheets course. Student study habits were tracked at a level of detail not available in previous research. Detailed data were collected regarding reading, video watching, actions in practice assignments, references to assignment instructions, and actions in graded assignments. The analysis indicates that student strategies cluster into four primary learning groups. The study provides insight into how instructors can develop their courses and lectures in ways that better match the learning strategies of their students.
dc.format.extent9 pages
dc.identifier.doi10.24251/HICSS.2019.004
dc.identifier.isbn978-0-9981331-2-6
dc.identifier.urihttp://hdl.handle.net/10125/59442
dc.language.isoeng
dc.relation.ispartofProceedings of the 52nd Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectAdvances in Teaching and Learning Technologies
dc.subjectCollaboration Systems and Technologies
dc.subjecteducational strategies, learning strategies, online courses, student learning
dc.titleUsing Educational Data Mining to Identify and Analyze Student Learning Strategies
dc.typeConference Paper
dc.type.dcmiText

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