Work

Data-Driven Insights into E-Learning: A Comprehensive Review of Eye-Tracking Applications in Learning Systems

Year: 2026

Type: article

Abstract: In the last few years, universities have increasingly implemented online learning environments, allowing students to study at their own pace. These environments utilize technological tools and implement methods to support training, deliver content, and promote the acquisition of new knowledge and skills. As an example of these technologies, eye tracking has emerged as a powerful tool for studying visual attention, cognitive processes, and learning behaviors. The main aim of this study is to provide a scoping review of recent eye-tracking research across diverse learner populations, ranging from K-12 students to university-level learners and educators. The present study examined recent advances in eye-tracking technologies, focusing on their potential, especially when combined with artificial intelligence (AI) techniques such as machine learning. It analyzed 54 empirical studies in the last few years, highlighting their applicability, strengths, and limitations. The research findings highlight the promise of eye-tracking technology to transform educational practices by providing data-driven insights regarding student behavior and cognitive processes. Future research must address implementation and data-analysis challenges to maximize the educational benefits of eye tracking.

Source: Journal of Eye Movement Research

DOI: 10.3390/jemr19020041

Authors: Safia Bendjebar, Yacine Lafifi, Rochdi Boudjehem, Aissa Laouissi

Institutions: University of Guelma, University Mohamed El Bachir El Ibrahimi of Bordj Bou Arreridj

Language: English

Topic: Gaze Tracking and Assistive Technology

Subfield: Human-Computer Interaction

Field: Computer Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: gold

Estimated APC paid: $1,207