Literaturnachweis - Detailanzeige
| Autor/inn/en | Garcia, Patricio; Amandi, Analia; Schiaffino, Silvia; Campo, Marcelo |
|---|---|
| Titel | Evaluating Bayesian Networks' Precision for Detecting Students' Learning Styles |
| Quelle | In: Computers & Education, 49 (2007) 3, S.794-808 (15 Seiten)Infoseite zur Zeitschrift
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| Sprache | englisch |
| Dokumenttyp | gedruckt; online; Zeitschriftenaufsatz |
| ISSN | 0360-1315 |
| DOI | 10.1016/j.compedu.2005.11.017 |
| Schlagwörter | Student Behavior; Internet; Web Based Instruction; Artificial Intelligence; Cognitive Style; Bayesian Statistics; Models; Evaluation Research; Learning Processes; Educational Technology |
| Abstract | Students are characterized by different learning styles, focusing on different types of information and processing this information in different ways. One of the desirable characteristics of a Web-based education system is that all the students can learn despite their different learning styles. To achieve this goal we have to detect how students learn: reflecting or acting; steadily or in fits and starts; intuitively or sensitively. In this work, we evaluate Bayesian networks at detecting the learning style of a student in a Web-based education system. The Bayesian network models different aspects of a student behavior while he/she works with this system. Then, it infers his/her learning styles according to the modeled behaviors. The proposed Bayesian model was evaluated in the context of an Artificial Intelligence Web-based course. The results obtained are promising as regards the detection of students' learning styles. Different levels of precision were found for the different dimensions or aspects of a learning style. (Author). |
| Anmerkungen | Elsevier. 6277 Sea Harbor Drive, Orlando, FL 32887-4800. Tel: 877-839-7126; Tel: 407-345-4020; Fax: 407-363-1354; e-mail: usjcs@elsevier.com; Web site: http://www.elsevier.com |
| Erfasst von | ERIC (Education Resources Information Center), Washington, DC |
| Update | 2017/4/10 |
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