THE EFFECTIVENESS OF ARTIFICIAL INTELLIGENCE TOOLS IN THE PEDAGOGICAL EDUCATION PROCESS
Keywords:
Artificial intelligence, pedagogical education, teacher trainingAbstract
The rapid development of digital technologies and artificial intelligence (AI) has significantly transformed modern education systems. In pedagogical education, AI tools create new opportunities for improving teaching and learning processes, enhancing instructional quality, and developing future teachers’ professional competencies. This study examines the effectiveness of using artificial intelligence tools in the pedagogical education process. The research highlights the pedagogical potential of AI technologies in supporting personalized learning, increasing student engagement, facilitating assessment, and improving educational management. Furthermore, the study analyzes the advantages and challenges associated with integrating AI tools into teacher education programs. The findings indicate that the effective implementation of AI technologies contributes to the development of pedagogical skills, critical thinking, and digital competence among future educators. Therefore, the integration of artificial intelligence tools into pedagogical education is considered an important factor in modernizing educational practices and increasing the overall effectiveness of teacher preparation.
References
Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial Intelligence in Education: Promises and Implications for Teaching and Learning. Center for Curriculum Redesign.
Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence Unleashed: An Argument for AI in Education. Pearson Education.
UNESCO. (2021). AI and Education: Guidance for Policy-makers. United Nations Educational, Scientific and Cultural Organization.
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(1), 39.
Baker, R. S., & Inventado, P. S. (2014). Educational data mining and learning analytics. In Learning Analytics (pp. 61–75). Springer.
Chen, L., Chen, P., & Lin, Z. (2020). Artificial intelligence in education: A review. IEEE Access, 8, 75264–75278.
Williamson, B., & Eynon, R. (2020). Historical threads, missing links, and future directions in AI in education. Learning, Media and Technology, 45(3), 223–235.
Siemens, G., & Baker, R. S. (2012). Learning analytics and educational data mining. Proceedings of the 2nd International Conference on Learning Analytics and Knowledge.
Huang, R. H., Spector, J. M., & Yang, J. (2019). Educational Technology: A Primer for the 21st Century. Springer.
OECD. (2021). Digital Education Outlook: Pushing the Frontiers with AI, Blockchain and Robots. OECD Publishing.