ДИДАКТИЧЕСКО МОДЕЛИРАНЕ ЧРЕЗ ИЗКУСТВЕН ИНТЕЛЕКТ В ПОДГОТОВКАТА НА СТУДЕНТИ – БЪДЕЩИ УЧИТЕЛИ ПО ТЕХНОЛОГИИ И ПРЕДПРИЕМАЧЕСТВО

Василиса Павлова Валеова
Югозападен университет „Неофит Рилски“, Благоевград

DIDACTIC MODELING VIA ARTIFICIAL INTELLIGENCE IN THE PREPARATION OF STUDENTS – FUTURE TEACHERS OF TECHNOLOGIES AND ENTREPRENEURSHIP

Vasilisa Pavlova Valeova
Southwest University “Neofit Rilski”, Blagoevgrad

Abstract: This report explores the transformative role of artificial intelligence (AI) in didactic modeling for university preparation of future teachers. The theoretical aspects of didactic modeling are analyzed alongside contemporary applications of generative AI and adaptive educational environments tailored to the needs of technology and entrepreneurship education. Key advantages are examined, including personalized learning, the automation of pedagogical activities, and the development of digital and entrepreneurial competencies, as well as the main challenges related to ethics and the digital di vide. The scientific novelty of the study lies in the theoretical substantiation and structuring of an integrated conceptual model for didactic design that effectively integrates traditional educational components with the capabilities of modern AI tools. The work’s contribution is expressed in defining specific algorithmic steps that enable technology to transition from a passive tool to an active collaborator for the future teacher, supporting the simulation of pedagogical cases, the generation of personalized learning scenarios, and the prediction of educational outcomes in the respective subject area. In this sense, the developed approach offers an innovative methodological framework for modernizing higher pedagogical education amid accelerated digital transformation.

Keywords: Artificial Intelligence, Didactic Modeling, Digital Competencies, Pedagogical Training

References:

1. Andreev, M., Protsesat na obuchenieto. Didaktika. Sofia: Universitetsko izdatelstvo „Sv. Kliment Ohridski“, 2001.
2. Petrov, P., Didaktika. Sofia: Veda Slovena – ZhG, 1998.
3. Russell, S., Norvig, P., Artificial Intelligence: A Modern Approach (4th ed.). Pearson Education, 2021.
4. Khenissi, M. A., Essalmi, F., Jemni, M., Kinshuk, Learner Modeling Using Educational Games: A Review of the Literature. Smart Learning Environments, 2(1), 1 – 35, 2015.
5. Holmes, W., Bialik, M., & Fadel, C., Artificial Intelligence in Education: Promises and Implications for Teaching and Learning. Boston: Center for Curriculum Redesign, 2019
6. Marienko, M., Nosenko, Y., Sukhikh, A., Tataurov, V., & Shyshkina, M., Personalization of Learning through Adaptive Technologies in the Context of Sustainable Development of Teacher Education. E3S Web of Conferences, 166, 2020.
7. Niemi, H., Pea, R., & Lu, Y. (Eds.)., AI in Learning: Designing the Future. Cham: Springer, 2023.
8. Selwyn, N., Should Robots Replace Teachers? AI and the Future of Education. Cambridge: Polity Press, 2019.

(Endnotes:)

1. European Commission. (2020a). Digital Education Action Plan 2021 – 2027: Resetting education and training for the digital age. Publications Office of the European Union
2. European Commission. (2020b). European Skills Agenda for sustainable competitiveness, social fairness and resilience. Publications Office of the European Union.
3. European Commission, Joint Research Centre. (2022). The Digital Competence Framework for Citizens (DigComp 2.2): With new examples of knowledge, skills and attitudes (Y. Punie & S. N. Brande, Eds.)
4. UNESCO. (2021). AI and Education: Guidance for Policy-makers. Paris: UNESCO Publishing

READ FULL PAPER