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Psychometrics of MOOCs: Measuring Learners’ Proficiency

Massive open online courses (MOOCs) generate learners’ performance data that can be used to understand learners’ proficiency and to improve their efficiency. However, the approaches currently used, such as assessing the proportion of correct responses in assessments, are oversimplified and may lead...

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Detalles Bibliográficos
Autores principales: Abbakumov, Dmitry, Desmet, Piet, Van den Noortgate, Wim
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Ubiquity Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7243831/
https://www.ncbi.nlm.nih.gov/pubmed/32477583
http://dx.doi.org/10.5334/pb.515
Descripción
Sumario:Massive open online courses (MOOCs) generate learners’ performance data that can be used to understand learners’ proficiency and to improve their efficiency. However, the approaches currently used, such as assessing the proportion of correct responses in assessments, are oversimplified and may lead to poor conclusions and decisions because they do not account for additional information on learner, content, and context. There is a need for theoretically grounded data-driven explainable educational measurement approaches for MOOCs. In this conceptual paper, we try to establish a connection between psychometrics, a scientific discipline concerned with techniques for educational and psychological measurement, and MOOCs. First, we describe general principles of traditional measurement of learners’ proficiency in education. Second, we discuss qualities of MOOCs which hamper direct application of approaches based on these general principles. Third, we discuss recent developments in measuring proficiency that may be relevant for analyzing MOOC data. Finally, we draw directions in psychometric modeling that might be interesting for future MOOC research.