Modelling Students' Performance in MOOCs: A Multivariate Approach

Autor/inn/en	Carannante, Maria; Davino, Cristina; Vistocco, Domenico
Titel	Modelling Students' Performance in MOOCs: A Multivariate Approach
Quelle	In: Studies in Higher Education, 46 (2021) 11, S.2371-2386 (16 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Davino, Cristina)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0307-5079
DOI	10.1080/03075079.2020.1723526
Schlagwörter	Online Courses; Structural Equation Models; Least Squares Statistics; Measurement; Academic Achievement; Learning Analytics; Learner Engagement; Path Analysis + Suchen Sie Ihr Suchwort? Online course; Online-Kurs; Messverfahren; Schulleistung; Pfadanalyse
Abstract	Massive Open Online Courses, universally labelled as MOOCs, become more and more relevant in the era of digitalization of higher education. The availability of free education resources without access restrictions for a plenty of potential users has changed the learning market in a way unthinkable only few decades ago. This form of web-based education allows to track all the actions of the students, thus providing an information base to understand how students' behaviour can influence their performance. The paper proposes a structural equation model in the framework of the component-based approach to measure which are the main factors affecting students' performance (Partial Least Squares Path Modelling). The novelty of the approach is the simultaneous analysis of more than one factor that exerts an impact on the performance. The analysis is carried out on the log data of a course available on the edX MOOCs platform named FedericaX. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01