Analyzing Log Files to Predict Students' Problem Solving Performance in a Computer-Based Physics Tutor

Autor/in	Lee, Young-Jin
Titel	Analyzing Log Files to Predict Students' Problem Solving Performance in a Computer-Based Physics Tutor
Quelle	In: Educational Technology & Society, 18 (2015) 2, S.225-236 (12 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1436-4522
Schlagwörter	Physics; Science Instruction; Computer Software; Accuracy; Intelligent Tutoring Systems; Regression (Statistics); Problem Solving; Prediction; Computer Assisted Instruction; Databases; Introductory Courses; Academic Achievement; Undergraduate Students; Military Schools; Teaching Methods; Maryland + Suchen Sie Ihr Suchwort? Physik; Teaching of science; Science education; Natural sciences Lessons; Naturwissenschaftlicher Unterricht; Intelligentes Tutorsystem; Regression; Regressionsanalyse; Problemlösen; Vorhersage; Computer based training; Computerunterstützter Unterricht; Datenbank; Einführungskurs; Schulleistung; Militärschule; Teaching method; Lehrmethode; Unterrichtsmethode
Abstract	This study investigates whether information saved in the log files of a computer-based tutor can be used to predict the problem solving performance of students. The log files of a computer-based physics tutoring environment called Andes Physics Tutor was analyzed to build a logistic regression model that predicted success and failure of students' problem solving from their past interactions with the computer-based tutor. The logistic regression model developed in this study was able to correctly identify about 70% of the observed problem solving performance. The 10-fold cross-validation and the Receiver Operating Characteristic (ROC) curve analyses suggest that the developed logistic regression model can predict students' problem solving performance on unseen new problems with a similar accuracy in the future. (As Provided).
Anmerkungen	International Forum of Educational Technology & Society. Athabasca University, School of Computing & Information Systems, 1 University Drive, Athabasca, AB T9S 3A3, Canada. Tel: 780-675-6812; Fax: 780-675-6973; Web site: http://www.ifets.info
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01