ERIC Number: EJ1070073
Record Type: Journal
Publication Date: 2015
Pages: 12
Abstractor: As Provided
ISBN: N/A
ISSN: EISSN-1436-4522
EISSN: N/A
Analyzing Log Files to Predict Students' Problem Solving Performance in a Computer-Based Physics Tutor
Lee, Young-Jin
Educational Technology & Society, v18 n2 p225-236 2015
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.
Descriptors: 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
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
Publication Type: Journal Articles; Reports - Research
Education Level: Higher Education; Postsecondary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Location: Maryland
Grant or Contract Numbers: N/A