Self-Directed Learning using Eye-Tracking: A Comparison between Wearable Head-worn and Webcam-based Technologies

Khosravi, S., Khan, A. R., Zoha, A. and Ghannam, R. (2022) Self-Directed Learning using Eye-Tracking: A Comparison between Wearable Head-worn and Webcam-based Technologies. In: IEEE Global Engineering Education Conference (EDUCON2022), Tunis, Tunisia, 28-31 March 2022, pp. 640-643. ISBN 9781665444347 (doi: 10.1109/EDUCON52537.2022.9766468)

Abstract

The COVID-19 pandemic has accelerated our transition to an online and self-directed learning environment. In an effort to design better e-learning materials, we investigated the effectiveness of collecting psychophysiological eye-tracking data from participants in response to visual stimuli. In particular, we focused on collecting fixation data since this is closely related to human attention. Current wearable devices allow the measurement of visual data unobtrusively and in real-time, leading to new applications in wearable technology. Despite their accuracy, head-mounted eye trackers are too expensive for deployment on large-scale deployment. Therefore, we developed a low-cost, webcam-based eye tracking solution and compared its performance with a commercial head-mounted eye tracker. Four-minute lecture slides on the 3 rd year electronic engineering course were presented as stimuli to eight learners for data collection. Their eye movement was collected within the pre-defined area of interest (AOI). Our results demonstrate that a low-cost webcam-based eye-tracking solution, combined with machine learning algorithms, can achieve similar accuracy to the head-worn tracker. Based on these results, learners can use the eye tracker for attention guidance. Our work also demonstrates that these webcam-based eye trackers can be scaled up and used in large classrooms to provide real-time information to instructors regarding student attention and behaviour.

• Item Type: Conference Proceedings
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Zoha, Dr Ahmed and Khosravi, Sara and Khan, Ahsan Raza and Ghannam, Professor Rami
• Authors: Khosravi, S., Khan, A. R., Zoha, A., and Ghannam, R.
• College/School: College of Science and Engineering > School of Engineering; College of Science and Engineering > School of Engineering > Electronics and Nanoscale Engineering
• ISBN: 9781665444347
• Published Online: 11 May 2022
• Copyright Holders: Copyright © 2022 IEEE
• Publisher Policy: Reproduced with the permission of the author

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