Literaturnachweis - Detailanzeige
| Autor/in | Xu, Tonghui |
|---|---|
| Titel | Using Data Mining Models to Predict Students' Academic Performance before the Online Course Start |
| Quelle | In: Journal of Educators Online, 20 (2023) 1, (13 Seiten)Infoseite zur Zeitschrift
PDF als Volltext kostenfreie Datei |
| Sprache | englisch |
| Dokumenttyp | gedruckt; online; Zeitschriftenaufsatz |
| Schlagwörter | College Students; Online Courses; Academic Achievement; Data Analysis; Information Retrieval; Pattern Recognition; Models; Prediction; Interaction; Success; Algorithms; Student Behavior; Time Factors (Learning) |
| Abstract | The early detection of students' academic performance or final grades helps instructors prepare their online courses. In the Open University Learning Analytics Dataset, I found many online students clicked the course materials before the first day of class. This study aims to investigate how data mining models can use this student interaction data to predict their academic performance. In this study, this interaction information is called "week 0" data. The results suggest that "week 0" interaction data can be used to identify the academic success of online students and predict first assignment performance. (As Provided). |
| Anmerkungen | Journal of Educators Online. Grand Canyon University, 23300 West Camelback Road, Phoenix, AZ 85017. e-mail: CIRT@gcu.edu. Web site: https://www.thejeo.com |
| Erfasst von | ERIC (Education Resources Information Center), Washington, DC |
| Update | 2024/1/01 |
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