Predicting Robust Learning with the Visual Form of the Moment-by-Moment Learning Curve

Autor/inn/en	Baker, Ryan S.; Hershkovitz, Arnon; Rossi, Lisa M.; Goldstein, Adam B.; Gowda, Sujith M.
Titel	Predicting Robust Learning with the Visual Form of the Moment-by-Moment Learning Curve
Quelle	In: Journal of the Learning Sciences, 22 (2013) 4, S.639-666 (28 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1050-8406
DOI	10.1080/10508406.2013.836653
Schlagwörter	Learning Processes; Intelligent Tutoring Systems; Probability; Skill Development; Data Collection; Problem Solving; Learning Modules; Pretests Posttests; Graphs; Predictor Variables; Regression (Statistics); Models; Coding; Undergraduate Students; Evaluation Methods; Genetics; Correlation; Biology; Pennsylvania + Suchen Sie Ihr Suchwort? Learning process; Lernprozess; Intelligentes Tutorsystem; Wahrscheinlichkeitsrechnung; Wahrscheinlichkeitstheorie; Kompetenzentwicklung; Qualifikationsentwicklung; Data capture; Datensammlung; Problemlösen; Learning module; Lernmodul; Grafische Darstellung; Prädiktor; Regression; Regressionsanalyse; Analogiemodell; Codierung; Programmierung; Humangenetik; Korrelation; Biologie
Abstract	We 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, 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. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10