Enhancing student engagement through webcam-based eye tracking and machine learning: A focus on English reading comprehension
Year: 2025
Type: article
Abstract: This study presents an innovative approach to monitoring student attention in real-time using unmodified webcams and machine learning algorithms, with a specific focus on improving English reading comprehension. The proposed system captures eye movement patterns and facial features to detect attentiveness levels, providing immediate feedback to both students and instructors. Additionally, the research explores how font optimization based on individual attention data can enhance reading efficiency. The system was implemented in Shenzhen Polytechnic University's School of Foreign Languages and Business, with participants showing a 32.7% improvement in focus during English reading tasks and a 28.4% increase in reading efficiency after font adjustments. These findings highlight the potential of non-intrusive attention monitoring systems combined with personalized typography optimization to enhance language learning outcomes.
Authors: Lei Yang, Run Zhong
Institution: Shenzhen Polytechnic University
Language: English
Subfield: Human-Computer Interaction
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: bronze
OpenAlex ID: W4412683697