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Article: Promoting low-achieving students’ epistemic understanding of discourse: a video-based visual learning analytics approach

TitlePromoting low-achieving students’ epistemic understanding of discourse: a video-based visual learning analytics approach
Authors
Keywordsanalytics-supported reflection
epistemic understanding
low-achieving students
Productive discourse
visual scaffolds
Issue Date2-Jan-2024
PublisherTaylor and Francis Group
Citation
Interactive Learning Environments, 2024, v. 32, n. 10, p. 6967-6983 How to Cite?
AbstractThis study examined fostering low-achieving students’ epistemic understanding of discourse in knowledge building classrooms using video-based visual learning analytics. The participants were two Grade 9 visual arts classes of low-achieving students. The experimental class (n = 33) engaged in a knowledge building classroom supported by video-based visual learning analytics, and the comparison class (n = 29) in a regular knowledge building classroom. Quantitative analysis of questionnaire data indicated that the experimental class acquired a deeper epistemic understanding of discourse and domain knowledge than the comparison class. Four themes related to knowledge building principles were identified, including improving ideas, developing community knowledge, creating new knowledge, and synthesizing ideas. Qualitative analysis of classroom talk, interview responses, and prompt sheets described how the scaffolding of video-based learning analytics helped students develop their understanding. The implications of using video-based visual learning analytics as scaffolds to promote low-achieving students’ epistemic understanding are discussed.
Persistent Identifierhttp://hdl.handle.net/10722/361846
ISSN
2023 Impact Factor: 3.7
2023 SCImago Journal Rankings: 1.312

 

DC FieldValueLanguage
dc.contributor.authorTong, Yuyao-
dc.contributor.authorYang, Chao-
dc.contributor.authorWang, Pengjin-
dc.contributor.authorChen, Gaowei-
dc.date.accessioned2025-09-17T00:31:04Z-
dc.date.available2025-09-17T00:31:04Z-
dc.date.issued2024-01-02-
dc.identifier.citationInteractive Learning Environments, 2024, v. 32, n. 10, p. 6967-6983-
dc.identifier.issn1049-4820-
dc.identifier.urihttp://hdl.handle.net/10722/361846-
dc.description.abstractThis study examined fostering low-achieving students’ epistemic understanding of discourse in knowledge building classrooms using video-based visual learning analytics. The participants were two Grade 9 visual arts classes of low-achieving students. The experimental class (n = 33) engaged in a knowledge building classroom supported by video-based visual learning analytics, and the comparison class (n = 29) in a regular knowledge building classroom. Quantitative analysis of questionnaire data indicated that the experimental class acquired a deeper epistemic understanding of discourse and domain knowledge than the comparison class. Four themes related to knowledge building principles were identified, including improving ideas, developing community knowledge, creating new knowledge, and synthesizing ideas. Qualitative analysis of classroom talk, interview responses, and prompt sheets described how the scaffolding of video-based learning analytics helped students develop their understanding. The implications of using video-based visual learning analytics as scaffolds to promote low-achieving students’ epistemic understanding are discussed.-
dc.languageeng-
dc.publisherTaylor and Francis Group-
dc.relation.ispartofInteractive Learning Environments-
dc.subjectanalytics-supported reflection-
dc.subjectepistemic understanding-
dc.subjectlow-achieving students-
dc.subjectProductive discourse-
dc.subjectvisual scaffolds-
dc.titlePromoting low-achieving students’ epistemic understanding of discourse: a video-based visual learning analytics approach-
dc.typeArticle-
dc.identifier.doi10.1080/10494820.2023.2296517-
dc.identifier.scopuseid_2-s2.0-85181221188-
dc.identifier.volume32-
dc.identifier.issue10-
dc.identifier.spage6967-
dc.identifier.epage6983-
dc.identifier.eissn1744-5191-
dc.identifier.issnl1049-4820-

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