An intelligent agent to detect learner's learning style automatically through E-learning system in Saudi Arabia

Joint Authors

Assiri, Aliyah Abd al-Rahman
Abd al-Aziz, Azrilah

Source

Journal of Engineering Sciences and Information Technology

Issue

Vol. 1, Issue 4 (31 Dec. 2017), pp.55-84, 30 p.

Publisher

National Research Center

Publication Date

2017-12-31

Country of Publication

Palestine (Gaza Strip)

No. of Pages

30

Main Subjects

Educational Sciences
Information Technology and Computer Science

Abstract EN

Most of the successful conventional E-learning system lack of automatic detecting of learner learning style based on their preference.

An Automatic approach marked as a better approach to characterize learning style because it is based on real student behavior.

The purpose of this study is to propose a new literature-based method (Automatic approach) using intelligent agents to identify learner's learning style based on behavior using Felder-Silverman Learning Style Model (FSLSM).

The new method implemented in new developed LMS.

After obtaining the proposed method result, the result validates and compared with Felder-Silverman Learning Style Model questionnaire (ILS) and García method .After comparing the proposed method with the results of previous studies, the researcher got satisfactory results on precision percentage and the lowest percentage in the results was 66.6 %.

American Psychological Association (APA)

Abd al-Aziz, Azrilah& Assiri, Aliyah Abd al-Rahman. 2017. An intelligent agent to detect learner's learning style automatically through E-learning system in Saudi Arabia. Journal of Engineering Sciences and Information Technology،Vol. 1, no. 4, pp.55-84.
https://search.emarefa.net/detail/BIM-890007

Modern Language Association (MLA)

Abd al-Aziz, Azrilah& Assiri, Aliyah Abd al-Rahman. An intelligent agent to detect learner's learning style automatically through E-learning system in Saudi Arabia. Journal of Engineering Sciences and Information Technology Vol. 1, no. 4 (Dec. 2017), pp.55-84.
https://search.emarefa.net/detail/BIM-890007

American Medical Association (AMA)

Abd al-Aziz, Azrilah& Assiri, Aliyah Abd al-Rahman. An intelligent agent to detect learner's learning style automatically through E-learning system in Saudi Arabia. Journal of Engineering Sciences and Information Technology. 2017. Vol. 1, no. 4, pp.55-84.
https://search.emarefa.net/detail/BIM-890007

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references : p 81-84

Record ID

BIM-890007