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Autor/inn/enOlsen, Jennifer; Aleven, Vincent; Rummel, Nikol
TitelStatistically Modeling Individual Students' Learning over Successive Collaborative Practice Opportunities
QuelleIn: Journal of Educational Measurement, 54 (2017) 1, S.123-138 (16 Seiten)Infoseite zur Zeitschrift
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Spracheenglisch
Dokumenttypgedruckt; online; Zeitschriftenaufsatz
ISSN0022-0655
DOI10.1111/jedm.12137
SchlagwörterMathematical Models; Information Retrieval; Data Analysis; Educational Research; Cooperative Learning; Learning Processes; Goodness of Fit; Educational Benefits; Outcomes of Education
AbstractWithin educational data mining, many statistical models capture the learning of students working individually. However, not much work has been done to extend these statistical models of individual learning to a collaborative setting, despite the effectiveness of collaborative learning activities. We extend a widely used model (the additive factors model) to account for the effect of collaboration on individual learning, including having the help of a partner and getting to observe/help a partner. We find evidence that models that include these collaborative features have a better fit than the original models for performance data and that learning rates estimated using the extended models provide insights into how collaboration benefits individual students' learning outcomes. (As Provided).
AnmerkungenWiley-Blackwell. 350 Main Street, Malden, MA 02148. Tel: 800-835-6770; Tel: 781-388-8598; Fax: 781-388-8232; e-mail: cs-journals@wiley.com; Web site: http://www.wiley.com/WileyCDA
Erfasst vonERIC (Education Resources Information Center), Washington, DC
Update2020/1/01
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