Keywords
Abstract
In the context of rapid digital transformation in education, adaptive teaching technologies have become an essential tool for improving the quality of learning in economics. This article examines the theoretical foundations, practical applications, and effectiveness of adaptive learning systems in teaching economics. The study focuses on personalized learning environments, artificial intelligence-based platforms, and data-driven instructional strategies. The findings demonstrate that adaptive technologies significantly enhance students’ comprehension of complex economic concepts, improve engagement, and foster independent learning skills. The paper concludes with recommendations for integrating adaptive technologies into higher education curricula.
References
1. Siemens G. Learning Analytics: The Emergence of a Discipline // American Behavioral Scientist. – 2013. – Vol. 57(10). – P. 1380–1400.
2. Woolf B.P. Building Intelligent Interactive Tutors: Student-Centered Strategies for Revolutionizing E-Learning. – Burlington: Morgan Kaufmann, 2010. – 512 p.
3. Becker W.E., Watts M. Teaching Economics at the Start of the 21st Century // American Economic Review. – 2001. – Vol. 91(2). – P. 446–451.
4. Pane J.F., Steiner E.D., Baird M.D., Hamilton L.S. Informing Progress: Insights on Personalized Learning Implementation and Effects. – Santa Monica: RAND Corporation, 2017. – 120 p.
5. Brusilovsky P., Millán E. User Models for Adaptive Hypermedia and Adaptive Educational Systems // The Adaptive Web. – Berlin: Springer, 2007. – P. 3–53.
6. Durlach P.J., Lesgold A.M. Adaptive Technologies for Training and Education. – Cambridge: Cambridge University Press, 2012. – 350 p.
7. Holmes W., Bialik M., Fadel C. Artificial Intelligence in Education: Promises and Implications for Teaching and Learning. – Boston: Center for Curriculum Redesign, 2019. – 120 p.