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Clustering and Profiling Students According to their Interactions with an Intelligent Tutoring System Fostering Self-Regulated Learning
2013
Zenodo
In this paper, we present the results obtained using a clustering algorithm (Expectation-Maximization) on data collected from 106 college students learning about the circulatory system with MetaTutor, an agent-based Intelligent Tutoring System (ITS) designed to foster self-regulated learning (SRL). The three extracted clusters were validated and analyzed using multivariate statistics (MANOVAs) in order to characterize three distinct profiles of students, displaying statistically significant
doi:10.5281/zenodo.3554613
fatcat:eaeu335si5hjnobd26xrw5336a