ADAPTIVE LEARNING WITH ARTIFICIAL INTELLIGENCE: PEDAGOGICAL APPROACHES
Keywords:
artificial intelligence, adaptive learning, digital pedagogy, student model, individualized education, learning motivation.Abstract
This article analyzes the pedagogical foundations of AI-based adaptive learning technologies, their impact on the educational process, advantages, and implementation mechanisms. The study scientifically highlights the importance of adaptive systems in shaping individual learning trajectories, assessing students’ mastery levels, enhancing motivation, and developing independent learning skills.
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Anderson J.R. Anderson, J. R., Corbett, A. T., Koedinger, K. R., & Pelletier, R. "Cognitive Tutors: Lessons Learned." The Journal of Learning Sciences, 1995. - 4(2), 167–207.
Brusilovsky, P., & Millan, E., I.Selwyn “User Models for Adaptive Hypermedia and Adaptive Educational Systems.” In The Adaptive Web 2007. - (pp. 3–53). Berlin: Springer.
Brusilovsky, P. “Adaptive Hypermedia.” User Modeling and User-Adapted Interaction, 2001. - 11(1–2), 87–110.
Devedžić, V., & Yacef, K. “Intelligent Tutoring Systems and Learning Analytics.” International Journal of Artificial Intelligence in Education, 2018. - 28(3), 220–250.
Keller, J. M. Motivational Design for Learning and Performance: The ARCS Model Approach. New York: Springer. 2010. - pp. 180–215.
Selwyn, N. Should Robots Replace Teachers? AI and the Future of Education.Cambridge: Polity Press. 2019. - pp. 37–80; 120–147.
Woolf B.P. Building Intelligent Interactive Tutors: Student-Centered Strategies for Revolutionizing e-Learning. Cambridge, MA: MIT Press. 2009. pp. 1–25; 145–190.
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