PEDAGOGICAL POSSIBILITIES OF USING ARTIFICIAL INTELLIGENCE TECHNOLOGIES IN THE MODERN EDUCATION SYSTEM
Keywords:
artificial intelligence, modern education, personalized learning, intelligent tutoring systems, educational technologies, adaptive learning, learning analytics, digital education, educational innovation, teaching effectiveness.Abstract
The rapid advancement of artificial intelligence (AI) technologies has significantly influenced the transformation of modern education systems. This study examines the pedagogical possibilities of integrating artificial intelligence technologies into educational processes and analyzes their impact on teaching effectiveness and learning outcomes. The research highlights key areas where AI can enhance education, including personalized learning, intelligent tutoring systems, automated assessment, and learning analytics. The findings indicate that AI technologies enable the creation of adaptive learning environments that respond to individual students’ needs, learning pace, and cognitive abilities. Additionally, AI tools assist teachers by automating routine tasks such as grading and monitoring student progress, allowing educators to focus more on instructional and mentoring activities. Despite these advantages, the implementation of AI in education also raises challenges related to ethical considerations, data privacy, and digital inequality. The study concludes that artificial intelligence should be viewed as a supportive pedagogical tool that enhances, rather than replaces, the role of teachers in modern education systems.
Downloads
References
Dede, C. (2014). The role of digital technologies in deeper learning. Students at the Center: Deeper Learning Research Series. Jobs for the Future.
Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial intelligence in education: Promises and implications for teaching and learning. Boston, MA: Center for Curriculum Redesign.
Holmes, W., Persson, J., Chounta, I. A., Wasson, B., & Dimitrova, V. (2022). Artificial intelligence and education: A critical view through the lens of human rights, democracy and the rule of law. Strasbourg: Council of Europe.
Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence unleashed: An argument for AI in education. London: Pearson Education.
Popenici, S. A. D., & Kerr, S. (2017). Exploring the impact of artificial intelligence on teaching and learning in higher education. Research and Practice in Technology Enhanced Learning, 12(22), 1–13.
Selwyn, N. (2019). Should robots replace teachers? AI and the future of education. Cambridge, UK: Polity Press.
Siemens, G., & Baker, R. S. J. d. (2012). Learning analytics and educational data mining: Towards communication and collaboration. Proceedings of the 2nd International Conference on Learning Analytics and Knowledge, 252–254.
Woolf, B. P. (2010). Building intelligent interactive tutors: Student-centered strategies for revolutionizing e-learning. Burlington, MA: Morgan Kaufmann.
Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education. International Journal of Educational Technology in Higher Education, 16(39), 1–27. https://doi.org/10.1186/s41239-019-0171-0
Downloads
Published
How to Cite
Issue
Section
License

This work is licensed under a Creative Commons Attribution 4.0 International License.
All content published in the Journal of Applied Science and Social Science (JASSS) is protected by copyright. Authors retain the copyright to their work, and grant JASSS the right to publish the work under a Creative Commons Attribution License (CC BY). This license allows others to distribute, remix, adapt, and build upon the work, even commercially, as long as they credit the author(s) for the original creation.