You are here:

Optimizing E-Learning Cognitive Ergonomics Based on Structural Analysis of Dynamic Responses

, Information Technology Department College of Computer and Information Sciences King Saud University Riyadh Saudi Arabia ; , King Saud University

iJET Volume 14, Number 10, ISSN 1863-0383 Publisher: International Journal of Emerging Technology in Learning, Kassel, Germany


Smart Assistive Technologies (SAT) can be a powerful tool in supporting education environments and inclusion for learners with visual/hearing impairments. For example, while captions in videos are a necessity for deaf users, audio reading is inevitable for blind ones. Including such technologies into a smart e-learning environment provide huge opportunities to customize the content presentation to needs and ability of learners. Despite the number of models being introduced during the last decade, acceptance model and behavioral model are, yet, exhibiting design drawbacks for learners with visual and hearing impairments. Meanwhile, the e-learning initiatives in the universities have paid great efforts in order to optimize usability of conventional e-learning systems. However, optimizing assistive e-learning systems is not covered in the recent research. Central to e-learning optimization is the learners’ realization problem; in terms of the size of gap between learners’ expectations and real interaction measures. This paper presents a study of measure the usability of assistive e-learning systems and modeling better interaction based on adjusted Fitt’s Law to consider time of movement for assistive technologies embedded in e-learning systems. The proposed usability evaluation considers the hardness of mental operations during e-learning various activities.


Chorfi, H. & Al-hudhud, G. (2019). Optimizing E-Learning Cognitive Ergonomics Based on Structural Analysis of Dynamic Responses. International Journal of Emerging Technologies in Learning (iJET), 14(10), 150-160. Kassel, Germany: International Journal of Emerging Technology in Learning. Retrieved November 28, 2020 from .