Predicting Robust Learning With the Visual Form of the Moment-by-Moment Learning Curve
2013; Routledge; Volume: 22; Issue: 4 Linguagem: Inglês
10.1080/10508406.2013.836653
ISSN1532-7809
AutoresRyan S. Baker, Arnon Hershkovitz, Lisa M. Rossi, Adam B. Goldstein, Sujith M. Gowda,
Tópico(s)Online Learning and Analytics
ResumoWe present a new method for analyzing a student's learning over time for a specific skill: analysis of the graph of the student's moment-by-moment learning over time. Moment-by-moment learning is calculated using a data-mined model that assesses the probability that a student learned a skill or concept at a specific time during learning (Baker, Goldstein, & Heffernan, 2010 Baker, R. S. J. d., Goldstein, A. B. and Heffernan, N. T. 2010. "Detecting the moment of learning". In Proceedings of the 10th Annual Conference on Intelligent Tutoring Systems 25–34. In V. Aleven, J. Kay, & J. Mostow (Eds.),pp.Heidelberg, Germany: Springer.[Crossref] , [Google Scholar], 2011). Two coders labeled data from students who used an intelligent tutoring system for college genetics. They coded in terms of 7 forms that the moment-by-moment learning curve can take. These labels are correlated to test data on the robustness of students' learning. We find that different visual forms are correlated with very different learning outcomes. This work suggests that analysis of moment-by-moment learning curves may be able to shed light on the implications of students' different patterns of learning over time.
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