Literaturnachweis - Detailanzeige
| Autor/inn/en | Yang, Zongkai; Yang, Juan; Rice, Kerry; Hung, Jui-Long; Du, Xu |
|---|---|
| Titel | Using Convolutional Neural Network to Recognize Learning Images for Early Warning of At-Risk Students |
| Quelle | In: IEEE Transactions on Learning Technologies, 13 (2020) 3, S.617-630 (14 Seiten)Infoseite zur Zeitschrift
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| Zusatzinformation | ORCID (Yang, Juan) ORCID (Rice, Kerry) ORCID (Hung, Jui-Long) ORCID (Du, Xu) |
| Sprache | englisch |
| Dokumenttyp | gedruckt; online; Zeitschriftenaufsatz |
| ISSN | 1939-1382 |
| DOI | 10.1109/TLT.2020.2988253 |
| Schlagwörter | Distance Education; At Risk Students; Artificial Intelligence; Man Machine Systems; Models; Data Use; Character Recognition; Elementary Secondary Education; Kindergarten; Online Courses; Student Participation; Grades (Scholastic) |
| Abstract | This article proposes two innovative approaches, the one-channel learning image recognition and the three-channel learning image recognition, to convert student's course involvements into images for early warning predictive analysis. Multiple experiments with 5235 students and 576 absolute/1728 relative input variables were conducted to verify their effectiveness. The results indicate that both methods can significantly capture more at-risk students (the highest average recall rate is equal to 77.26%) than the following machine learning algorithms--support vector machine, random forest, and deep neural network--in the middle of the semester. In addition, the innovative approaches allow minor subtypes of at-risk student identification and provide visual insights for personalized interventions. Implications and future directions are also discussed in this article. (As Provided). |
| Anmerkungen | Institute of Electrical and Electronics Engineers, Inc. 445 Hoes Lane, Piscataway, NJ 08854. Tel: 732-981-0060; Web site: http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=4620076 |
| Erfasst von | ERIC (Education Resources Information Center), Washington, DC |
| Update | 2024/1/01 |
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