METHODOLOGICAL APPROACHES TO DEVELOPING THE PROFESSIONAL COMPETENCE OF FUTURE MUSIC TEACHERS USING GENERATIVE ARTIFICIAL INTELLIGENCE TECHNOLOGIES
Abstract
The purpose of the study is to identify pedagogical conditions that facilitate the integration of the capabilities of generative artificial intelligence with the goals, content, methods, and assessment system of music education, as well as to develop practical and methodological recommendations. The study employed the methods of analyzing scientific and pedagogical literature, comparative analysis, systematization, modeling, and pedagogical design. Pedagogical appropriateness, teachers’ digital-pedagogical competence, students’ artificial intelligence literacy, pedagogical expertise, individualized learning, creative activity, academic integrity, a safe digital environment, and reflective assessment were identified as the main pedagogical conditions. The proposed model is aimed at developing the musical-creative, methodological, digital, and reflective-ethical competencies of future music teachers.
References
1. Peng, X., Sun, K., Shan, X., & Zhang, J. (2026). Empowerment or dependency? A systematic review of the impacts of intelligent assessment and generative AI on learners’ self-beliefs and cognitive agency in music education. Frontiers in Psychology, 17, 1776445. DOI: 10.3389/fpsyg.2026.1776445.
2. UNESCO. (2021). Recommendation on the Ethics of Artificial Intelligence. UNESCO.
3. U.S. Department of Education, Office of Educational Technology. (2023). Artificial Intelligence and the Future of Teaching and Learning: Insights and Recommendations. U.S. Department of Education.
4. Zhang, Y., Beh, W. F., Zhang, C., & Pi, S. (2024). Transforming music education through artificial intelligence: A systematic literature review on enhancing music teaching and learning. International Journal of Interactive Mobile Technologies, 18(18), 76–93. DOI: 10.3991/ijim.v18i18.50545.
