Time-Driven Modeling of Student Self-Regulated Learning in Network-Based Tutors

Autor/inn/en	Poitras, Eric G.; Doleck, Tenzin; Huang, Lingyun; Dias, Laurel; Lajoie, Susanne P.
Titel	Time-Driven Modeling of Student Self-Regulated Learning in Network-Based Tutors
Quelle	In: Interactive Learning Environments, 31 (2023) 4, S.2490-2511 (22 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Doleck, Tenzin) ORCID (Dias, Laurel)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1049-4820
DOI	10.1080/10494820.2021.1891941
Schlagwörter	Independent Study; Self Management; Time; Networks; Preservice Teachers; Educational Technology; Student Behavior; Planning; Knowledge Level; Scaffolding (Teaching Technique); Student Needs; Technological Literacy; Pedagogical Content Knowledge; Design + Suchen Sie Ihr Suchwort? Selbststudium; Selbstmanagement; Zeit; Unterrichtsmedien; Student behaviour; Schülerverhalten; Ablaufplanung; Planungsprozess; Wissensbasis; Technisches Wissen; Pädagogische Kompetenz
Abstract	This study applies a time-driven approach to model self-regulated learning (SRL) on the basis of elapsed time metrics in the context of open-ended learning environments (OELEs), specifically, network-based tutors. In doing so, we examine how students allocated attentional resources to distinct phases of SRL as a measure of depth of information processing. Student teachers (N=68) were assigned to two different versions of nBrowser: a "static version" where the network did not converge on the basis of student interactions and a "dynamic version" where the network was continually updated by the system. Students designed a lesson plan and completed pre- and post-test self-report measures of knowledge gains. In both the experimental conditions, the results show four distinct SRL profiles that are relatively consistent and can be detected on the basis of behavioral patterns logged by the system across behaviors, namely, planning, requesting hints, studying examples, and monitoring. Although students who allocated more attentional resources to studying examples performed more poorly, their efforts to engage in planning, requesting hints, and monitoring were found to predict knowledge gains and design skills. Furthermore, students assigned to the dynamic version of the system outperformed those assigned to the static version in pedagogical knowledge gains. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01