眼动追踪技术在个性化在线学习中的应用
Application of Eye-Tracking Technology in Personalized Online Learning
摘要: 学习材料的科学设计是其促进个性化学习的前提；基于眼动追踪技术的研究可为个性化学习提供技术支撑。但在教育研究中的应用较少。因此本研究从眼动追踪技术在学习过程中测量认知负荷；监测学习参与度；眼动样例对于学习者的实时指导；以及基于眼动的机器学习所提供的实时反馈和干预方面展开，以帮助形成完善的个性化学习提供技术支撑。未来研究应整合现有的研究并继续深入，完善已有的技术。
Abstract: The scientific design of learning materials is the premise of promoting personalized learning; re-search based on eye-tracking technology can provide technical support for personalized learning. But it is less used in educational research. Therefore, this study starts with eye-tracking technology to measure cognitive load during learning; monitoring learning engagement; real-time guidance of learners with eye-tracking samples; and real-time feedback and intervention provided by eye-tracking-based machine learning, to provide technical support to help form complete personalized learning. Future research should integrate existing research and continue to deepen and improve existing technologies.
文章引用：陈登水. 眼动追踪技术在个性化在线学习中的应用[J]. 社会科学前沿, 2022, 11(11): 4901-4905. https://doi.org/10.12677/ASS.2022.1111669

参考文献

[1] Lai, M.-L., Tsai, M.-J., Yang, F.-Y., Hsu, C.-Y., Liu, T.-C., Lee, S.W.-Y., Lee, M.-H., Chiou, G.-L., Liang, J.-C. and Tsai, C.-C. (2013) A Review of Using Eye-Tracking Technology in Exploring Learning from 2000 to 2012. Educational Research Review, 10, 90-115. [Google Scholar] [CrossRef] 
[2] Kruger, J.L., Doherty, S., Fox, W. and De Lissa, P. (2018) Multimodal Measurement of Cognitive Load during Subtitle Processing. In: Lacruz, I. and Jääskeläinen, R., Eds., Innovation and Expansion in Translation Process Research, John Benjamins Publishing, Amsterdam & Philadelphia, 267-294. [Google Scholar] [CrossRef] 
[3] Loschky, L.C., Ringer, R.V., Johnson, A.P., Larson, A.M., Neider, M. and Kramer, A.F. (2014) Blur Detection Is Unaffected by Cognitive Load. Visual Cognition, 22, 522-547. [Google Scholar] [CrossRef] [PubMed]
[4] Zu, T., Hutson, J., Loschky, L.C. and Rebello, N.S. (2020) Using Eye Movements to Measure Intrinsic, Extraneous, and Germane Load in a Multimedia Learning Environment. Journal of Educational Psychology, 112, 1338-1352. [Google Scholar] [CrossRef] 
[5] D’Mello, S. and Graesser, A. (2012) Dynamics of Affective States during Complex Learning. Learning and Instruction, 22, 145-157. [Google Scholar] [CrossRef] 
[6] Krithika, L.B. and Priya, G.L. (2016) Student Emotion Recognition System (SERS) for E-Learning Improvement Based on Learner Concentration Metric. Procedia Computer Science, 85, 767-776. [Google Scholar] [CrossRef] 
[7] Rosengrant, D., Hearrington, D. and O’Brien, J. (2021) Investigating Student Sustained Attention in a Guided Inquiry Lecture Course Using an Eye Tracker. Educational Psychology Review, 33, 11-26. [Google Scholar] [CrossRef] 
[8] Goldberg, P., Sümer, Ö., Stürmer, K., Wagner, W., Göllner, R., Gerjets, P., Kasneci, E. and Trautwein, U. (2019) Attentive or Not? Toward a Machine Learning Approach to Assessing Students’ Visible Engagement in Classroom Instruction. Educational Psychology Review, 33, 27-49. [Google Scholar] [CrossRef] 
[9] Król, M. and Król, M. (2019) Learning from Peers’ Eye Movements in the Absence of Expert Guidance: A Proof of Concept Using Laboratory Stock Trading, Eye Tracking, and Machine Learning. Cognitive Science, 43, e12716. [Google Scholar] [CrossRef] [PubMed]
[10] Faber, M., Bixler, R. and D’Mello, S.K. (2018) An Automated Behavioral Measure of Mind Wandering during Computerized Reading. Behavior Research Methods, 50, 134-150. [Google Scholar] [CrossRef] [PubMed]
[11] Yang, F.Y., Tsai, M.J., Chiou, G.L., Lee, W.Y. and Chen, L.L. (2018) Instructional Suggestions Supporting Science Learning in Digital Environments Based on a Review of Eye Tracking Studies. Educational Technology & Society, 21, 28-45.
[12] Liu, T.S.-W., Liu, Y.-T. and Chen, C.-Y.D. (2018) Meaningfulness Is in the Eye of the Reader: Eye-Tracking Insights of L2 Learners Reading E-Books and Their Pedagogical Implications. Interactive Learning Environments, 27, 181-199. [Google Scholar] [CrossRef] 

为你推荐