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Predicting Student Performance Based on Online Study Habits: A Study of Blended Courses
- Publication Year :
- 2019
-
Abstract
- Online tools provide unique access to research students' study habits and problem-solving behavior. In MOOCs, this online data can be used to inform instructors and to provide automatic guidance to students. However, these techniques may not apply in blended courses with face to face and online components. We report on a study of integrated user-system interaction logs from 3 computer science courses using four online systems: LMS, forum, version control, and homework system. Our results show that students rarely work across platforms in a single session, and that final class performance can be predicted from students' system use.<br />Comment: Published in the International Conference on Educational Data Mining (EDM 2018)
- Subjects :
- Computer Science - Computers and Society
Subjects
Details
- Database :
- arXiv
- Publication Type :
- Report
- Accession number :
- edsarx.1904.07331
- Document Type :
- Working Paper