<?xml version="1.1" encoding="utf-8"?>
<article xsi:noNamespaceSchemaLocation="http://jats.nlm.nih.gov/publishing/1.1/xsd/JATS-journalpublishing1-mathml3.xsd" dtd-version="1.1" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"><front><journal-meta><journal-id journal-id-type="publisher-id">JCER</journal-id><journal-title-group><journal-title>Journal of Contemporary Educational Research</journal-title></journal-title-group><issn>2208-8466</issn><eissn>2208-8474</eissn><publisher><publisher-name>Bio-Byword Scientific Publishing Pty. Ltd.</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.26689/jcer.v9i9.12435</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title>Exploration and Practice of the Application of Eye-Tracking Technology in University Mathematics Teaching</title><url>https://artdesignp.com/journal/JCER/9/9/10.26689/jcer.v9i9.12435</url><author>WangZejun,YangMei,FanXingjing,LiMingyang</author><pub-date pub-type="publication-year"><year>2025</year></pub-date><volume>9</volume><issue>9</issue><history><date date-type="pub"><published-time>2025-10-21</published-time></date></history><abstract>As a tool for quantifying individuals’ visual attention and information processing, eye-tracking technology is gradually being applied in the reform of higher education. This paper focuses on issues in university mathematics teaching, such as heavy cognitive load, delayed feedback, and insufficient adaptability. Based on theories of cognitive psychology, the study explores application pathways of this technology in cognitive diagnosis, instructional optimization, classroom regulation, personalized support, and teaching assessment. Research shows that eye-tracking data can reveal key cognitive features during the learning process, enhance the visualization of instructional feedback, and improve the scientific basis of decision-making. This provides both theoretical support and practical reference for data-driven and precise transformation in university mathematics education.</abstract><keywords/></article-meta></front><body/><back><ref-list><ref id="B1" content-type="article"><label>1</label><element-citation publication-type="journal"><p>Zhang Z, Yang X, Xia D, 2021, A Study on Constructing Learning Engagement Profiles Based on Online Assignment Data. E-Education Research, 42(10): 84–91.</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B2" content-type="article"><label>2</label><element-citation publication-type="journal"><p>Da Silva Soares R, Barreto C, Sato J, 2023, Perspectives in Eye-Tracking Technology for Applications in Education. South African Journal of Childhood Education, 13(1): 1204.</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B3" content-type="article"><label>3</label><element-citation publication-type="journal"><p>Sáiz-Manzanares M, Marticorena-Sánchez R, Martín-Antón L, et al., 2023, Application and Challenges of Eye Tracking Technology in Higher Education. Comunicar: Media Education Research Journal, 31(76): 35–45.</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B4" content-type="article"><label>4</label><element-citation publication-type="journal"><p>Wang Y, Lu S, Harter D, 2021, Multi-Sensor Eye-Tracking Systems and Tools for Capturing Student Attention and Understanding Engagement in Learning: A Review. IEEE Sensors Journal, 21(20): 22402–22413.</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B5" content-type="article"><label>5</label><element-citation publication-type="journal"><p>Ayiei A, 2020, The Use of Eye Tracking in Assessing Visual Attention. Journal Of Aircraft and Spacecraft Technology, 4(1): 117–124.</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B6" content-type="article"><label>6</label><element-citation publication-type="journal"><p>Bitkina O, Park J, Kim H, 2021, The Ability of Eye-Tracking Metrics to Classify and Predict the Perceived Driving Workload. International Journal of Industrial Ergonomics, 86: 103193.</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B7" content-type="article"><label>7</label><element-citation publication-type="journal"><p>Li X, Zheng Y, Yang X, 2024, Educational Applications of Psychophysiological Data: Scientific Interpretation, Practical Exploration, and Development Trends. Modern Distance Education, 2024(5): 44–58.</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B8" content-type="article"><label>8</label><element-citation publication-type="journal"><p>Bannert M, 2002, Managing Cognitive Load—Recent Trends in Cognitive Load Theory. Learning And Instruction, 12(1): 139–146.</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B9" content-type="article"><label>9</label><element-citation publication-type="journal"><p>Wang C, Hung J, Chen S, et al., 2019, Tracking Students’ Visual Attention on Manga-Based Interactive E-Book While Reading: An Eye-Movement Approach. Multimedia Tools and Applications, 78(4): 4813–4834.</p><pub-id pub-id-type="doi"/></element-citation></ref></ref-list></back></article>
