Literaturnachweis - Detailanzeige
Autor/in | Hu, Yung-Hsiang |
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Titel | Using Few-Shot Learning Materials of Multiple SPOCs to Develop Early Warning Systems to Detect Students at Risk |
Quelle | In: International Review of Research in Open and Distributed Learning, 23 (2022) 1, S.1-20 (20 Seiten)Infoseite zur Zeitschrift
PDF als Volltext |
Sprache | englisch |
Dokumenttyp | gedruckt; online; Zeitschriftenaufsatz |
ISSN | 1492-3831 |
Schlagwörter | Dropout Prevention; At Risk Students; Online Courses; Private Colleges; College Students; Prediction; Integrated Learning Systems; Student Behavior; Progress Monitoring; Academic Failure; Models; Distance Education; Accuracy |
Abstract | Early warning systems (EWSs) have been successfully used in online classes, especially in massive open online courses, where it is nearly impossible for students to interact face-to-face with their teachers. Although teachers in higher education institutions typically have smaller class sizes, they also face the challenge of being unable to have direct contact with their students during distance teaching. In this research, we examined the online learning trajectories of students participating in four small private online courses that were all taught by one teacher. We collected relevant data of 1,307 students from the campus learning management system. Subsequently, we constructed 18 prediction models, one for each week of the course, to develop an EWS for identifying students in online asynchronous learning at risk of failing (i.e., students who fail their final examination). Our results indicated that the fifth-week model successfully predicted student performance, with an accuracy exceeding 83% from the eighth week onward. (As Provided). |
Anmerkungen | Athabasca University Press. 1200, 10011-109 Street, Edmonton, AB T5J 3S8, Canada. Tel: 780-497-3412; Fax: 780-421-3298; e-mail: irrodl@athabascau.ca; Web site: http://www.irrodl.org |
Erfasst von | ERIC (Education Resources Information Center), Washington, DC |
Update | 2024/1/01 |