How Do We Model Learning at Scale? A Systematic Review of Research on MOOCs

Autor/inn/en	Joksimovic, Srecko; Poquet, Oleksandra; Kovanovic, Vitomir; Dowell, Nia; Mills, Caitlin; Gaševic, Dragan; Dawson, Shane; Graesser, Arthur C.; Brooks, Christopher
Titel	How Do We Model Learning at Scale? A Systematic Review of Research on MOOCs
Quelle	In: Review of Educational Research, 88 (2018) 1, S.43-86 (44 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Joksimovic, Srecko) ORCID (Kovanovic, Vitomir)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0034-6543
DOI	10.3102/0034654317740335
Schlagwörter	Online Courses; Educational Research; Literature Reviews; Nonformal Education; Outcome Measures; Learner Engagement; Research Methodology; Academic Achievement; Cognitive Development; Academic Persistence; Dropout Rate; Affective Measures; Multidimensional Scaling; Predictor Variables; Statistical Analysis; Search Strategies; Multivariate Analysis + Suchen Sie Ihr Suchwort? Online course; Online-Kurs; Bildungsforschung; Pädagogische Forschung; Non-formal education; Non formal education; Nichtformale Bildung; Research method; Forschungsmethode; Schulleistung; Kognitive Entwicklung; Mehrdimensionale Analysis; Prädiktor; Statistische Analyse; Suchstrategie; Multivariate Analyse
Abstract	Despite a surge of empirical work on student participation in online learning environments, the causal links between the learning-related factors and processes with the desired learning outcomes remain unexplored. This study presents a systematic literature review of approaches to model learning in Massive Open Online Courses offering an analysis of learning-related constructs used in the prediction and measurement of student engagement and learning outcome. Based on our literature review, we identify current gaps in the research, including a lack of solid frameworks to explain learning in open online setting. Finally, we put forward a novel framework suitable for open online contexts based on a well-established model of student engagement. Our model is intended to guide future work studying the association between contextual factors (i.e., demographic, classroom, and individual needs), student engagement (i.e., academic, behavioral, cognitive, and affective engagement metrics), and learning outcomes (i.e., academic, social, and affective). The proposed model affords further interstudy comparisons as well as comparative studies with more traditional education models. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01