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Assessing Learning Styles Through Eye Tracking for E-Learning Applications

Nahumi Nugrahaningsih¹, Marco Porta² and Aleksandra Klašnja-Milićević³

1. University of Palangkaraya, Department of Informatics
   Kampus Unpar Tunjung Nyaho, Jl. Yos Sudarso, Palangkaraya 73112, Indonesia
   nahumi@it.upr.ac.id
2. University of Pavia, Department of Electrical, Computer and Biomedical Engineering
   Via A. Ferrata 5, 27100, Pavia, Italy
   marco.porta@unipv.it
3. University of Novi Sad, Department of Mathematics and Informatics
   Trg Dositeja Obradovica 3 – 21 000 Novi Sad, Serbia
   akm@dmi.uns.ac.rs

Abstract

Adapting the presentation of learning material to the specific student’s characteristics is useful to improve the overall learning experience and learning styles can play an important role to this purpose. In this paper, we investigate the possibility to distinguish between Visual and Verbal learning styles from gaze data. In an experiment involving first year students of an engineering faculty, content regarding the basics of programming was presented in both text and graphic form, and participants’ gaze data was recorded by means of an eye tracker. Three metrics were selected to characterize the user’s gaze behavior, namely, percentage of fixation duration, percentage of fixations, and average fixation duration. Percentages were calculated on ten intervals into which each participant’s interaction time was subdivided, and this allowed us to perform time-based assessments. The obtained results showed a significant relation between gaze data and Visual/Verbal learning styles for an information arrangement where the same concept is presented in graphical format on the left and in text format on the right. We think that this study can provide a useful contribution to learning styles research carried out exploiting eye tracking technology, as it is characterized by unique traits that cannot be found in similar investigations.

Key words

e-learning, learning models, learning styles, eye tracking, gaze behavior

Digital Object Identifier (DOI)

https://doi.org/10.2298/CSIS201201035N

Publication information

Volume 18, Issue 4 (September 2021)
Year of Publication: 2021
ISSN: 2406-1018 (Online)
Publisher: ComSIS Consortium

Full text

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How to cite

Nugrahaningsih, N., Porta, M., Klašnja-Milićević, A.: Assessing Learning Styles Through Eye Tracking for E-Learning Applications. Computer Science and Information Systems, Vol. 18, No. 4, 1287–1309. (2021), https://doi.org/10.2298/CSIS201201035N