TECHNOLOGY FOR DEVELOPING INTELLECTUAL SYSTEMS FOR MONITORING STUDENTS’ LEARNING ACTIVITIES IN THE EDUCATIONAL PROCESS
Keywords:
Compared to traditional forms of monitoring, the advantages of intellectual systems, as well as their implementation mechanisms, performance indicators, and practical significance, are highlightedAbstract
The article scientifically substantiates the need to develop intellectual systems for monitoring students’ learning activities in the context of the modern digital educational environment. The possibilities of improving the quality of education through the use of artificial intelligence, intelligent data analysis, neural networks, and adaptive learning technologies are revealed.
References
1. Baker, R. S., & Siemens, G. (2014). Educational data mining and learning analytics. In K. Sawyer (Ed.), Cambridge Handbook of the Learning Sciences. Cambridge University Press.
2. Romero, C., & Ventura, S. (2020). Educational data mining: A review of the state of the art. IEEE Transactions on Systems, Man, and Cybernetics: Systems.
3. Siemens, G., & Long, P. (2011). Learning analytics: The emergence of a discipline. American Behavioral Scientist.
4. Koedinger, K., Corbett, A., & Perfetti, C. (2012). The Knowledge-Learning-Instruction framework: Bridging the science of learning and educational practice. Cognitive Science.
5. Aljawarneh, S. A. (2020). Review of intelligent tutoring systems. Journal of Intelligent Learning Systems and Applications.
