Capacity Tracing-Enhanced Course Recommendation in MOOCs

Autor/inn/en	Tian, Xuetao; Liu, Feng
Titel	Capacity Tracing-Enhanced Course Recommendation in MOOCs
Quelle	In: IEEE Transactions on Learning Technologies, 14 (2021) 3, S.313-321 (9 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Tian, Xuetao) ORCID (Liu, Feng)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1939-1382
DOI	10.1109/TLT.2021.3083180
Schlagwörter	Online Courses; Item Response Theory; Course Selection (Students); Artificial Intelligence; Computer Uses in Education + Suchen Sie Ihr Suchwort? Online course; Online-Kurs; Item-Response-Theorie; Course selection; Student; Students; Kurswahl; Künstliche Intelligenz; Computernutzung
Abstract	Massive open online courses (MOOCs) have been an important learning tool in education. In order to reduce the high dropout rate and improve learners' satisfactions, it is urgent for MOOCs platform to provide course recommendation and tutoring service. To achieve it, it is necessary to determine and trace learners' learning state. Cognitive diagnosis in psychometric is a good way to quantify learners' capacities, but it demands explicit learner feedback, which does not always exist in MOOCs platform, such a typical weak-interaction scenario. Therefore, in this article, multidimensional item response theory (MIRT) is exploratively integrated into recommendation models in MOOCs by introducing a time-effectiveness hypothesis to obtain the implicit response on a followed course. To dynamically update learners' capacities by considering real-time and capacity multidimensionality, MIRT is extended to a capacity tracing model. The estimation for learner capacity is treated as attributes and integrated into collaborative filtering framework in course recommendation. To the best of our knowledge, this is the first work to integrate capacity tracing into course recommendation in MOOCs. Extensive experiments are conducted on a real-world dataset, demonstrating that the capacity tracing-enhanced course recommendation has improved effectiveness and explainability in MOOCs. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01