International Journal of Electrical and Computer Engineering
Vol 9, No 5: October 2019

Identifying learning style through eye tracking technology in adaptive learning systems

Inssaf El Guabassi (Abdelmalek Essaadi University)
Zakaria Bousalem (Hassan 1st University)
Mohammed Al Achhab (Abdelmalek Essaadi University)
Ismail Jellouli (Abdelmalek Essaadi University)
Badr Eddine EL Mohajir (Abdelmalek Essaadi University)



Article Info

Publish Date
01 Oct 2019

Abstract

Learner learning style represents a key principle and core value of the adaptive learning systems (ALS). Moreover, understanding individual learner learning styles is a very good condition for having the best services of resource adaptation. However, the majority of the ALS, which consider learning styles, use questionnaires in order to detect it, whereas this method has a various disadvantages, For example, it is unsuitable for some kinds of respondents, time-consuming to complete, it may be misunderstood by respondent, etc. In the present paper, we propose an approach for automatically detecting learning styles in ALS based on eye tracking technology, because it represents one of the most informative characteristics of gaze behavior. The experimental results showed a high relationship among the Felder-Silverman Learning Style and the eye movements recorded whilst learning.

Copyrights © 2019






Journal Info

Abbrev

IJECE

Publisher

Subject

Computer Science & IT Electrical & Electronics Engineering

Description

International Journal of Electrical and Computer Engineering (IJECE, ISSN: 2088-8708, a SCOPUS indexed Journal, SNIP: 1.001; SJR: 0.296; CiteScore: 0.99; SJR & CiteScore Q2 on both of the Electrical & Electronics Engineering, and Computer Science) is the official publication of the Institute of ...