Recommendation in E-Learning Based On Learning Style

Kotevski, Aleksandar and Mikarovski, Gjorgi and Kuzmanov, Ivo (2013) Recommendation in E-Learning Based On Learning Style. XLVIII INTERNATIONAL SCIENTIFIC CONFERENCE ON INFORMATION, COMMUNICATION AND ENERGY SYSTEMS AND TECHNOLOGIES. pp. 519-522.

27. icest_2013_02-pages-1-13,81-84.pdf

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This paper proposes a prototype of intelligent system for recommendation and delivering learning material to students in format and design that is adequate to students learning style. On the other words, the system should meet the needs of students, showing learning materials in acceptable format and style to the user. In order to make decision about the most adequate learning style, system is going to using VART classification to detect the student learning style. Furthermore, teachers can post learning materials in the system. They are going to receive suggestion for the most adequate category by using Vector-space models for information retrieval.

Item Type: Article
Subjects: Scientific Fields (Frascati) > Social Sciences > Educational sciences
Scientific Fields (Frascati) > Engineering and Technology > Mechanical engineering
Scientific Fields (Frascati) > Engineering and Technology > Other engineering and technologies
Divisions: Faculty of Technical Sciences
Depositing User: Prof. d-r. Ivo Kuzmanov
Date Deposited: 04 Apr 2020 17:09
Last Modified: 04 Apr 2020 17:09

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