Proceedings of the International scientific and practical conference ―Synergy of Modern Science and Education‖ (February 2-4, 2026) / Publisher website: www.naukainfo.com. – New York, USA, 2026. - 324 p.

77 For large-scale application, accessible indicators are considered: behavioral interaction metrics and eye-based cues potentially readable via a webcam (taking into account accuracy limitations and privacy requirements), with the possibility of validation via short subjective scales (Paas). Concrete thresholds for transitions between states and metrics for evaluating effectiveness are defined, including long- term knowledge retention. Overall, the concept enables learning systems that adapt not only to the learner, but to the learner in the moment—supporting self-regulation and steady progress while maintaining ethical standards and user privacy. Research on self-regulated learning stresses that supportive systems build self-regulation and can improve long- term educational outcomes [19]. REFERENCES: 1. Loboda T. D., Brusilovsky P. User-adaptive explanatory program visualization: evaluation and insights from eye movements. User Modeling and User-Adapted Interaction. 2010. Vol. 20, No. 3. P. 191–226. DOI: 10.1007/s11257-010-9077- 1. 2. Rayner, K. (2009). Eye movements and attention in reading, scene perception, and visual search. Quarterly Journal of Experimental Psychology, 62(8), 1457– 1506. 3. Sweller, J. (2011). Cognitive Load Theory. Psychology of Learning and Motivation, 55, 37–76. 4. Kirschner, P. A., Sweller, J., & Clark, R. E. (2006). Why Minimal Guidance During Instruction Does Not Work: An Analysis of the Failure of Constructivist, Discovery, Problem-Based, Experiential, and Inquiry-Based Teaching. Educational Psychologist, 41(2), 75–86. 5. Negi, S., Mitra, R. (2020). Fixation duration and the learning process: an eye tracking study with subtitled videos. Journal of Eye Movement Research, 13(6). PMC8012014.