Artificial Intelligence in Teacher Education

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  • Title: Artificial Intelligence in Teacher Education: Exploring Pre-Service Teachers’ Perspectives Through Creative Music Projects for Professional Learning
  • Author(s): Sandrina Milhano
  • Publisher: Common Ground Research Networks
  • Collection: Common Ground Research Networks
  • Series: Common Ground Open
  • Journal Title: The International Journal of Learning in Higher Education
  • Keywords: Artificial Intelligence, Creativity, Music Education, Professional Learning, Teacher Education
  • Volume: 33
  • Issue: 2
  • Date: November 07, 2025
  • ISSN: 2327-7955 (Print)
  • ISSN: 2327-8749 (Online)
  • DOI: https://doi.org/10.18848/2327-7955/CGP/v33i02/143-165
  • Citation: Milhano, Sandrina . 2025. "Artificial Intelligence in Teacher Education: Exploring Pre-Service Teachers’ Perspectives Through Creative Music Projects for Professional Learning." The International Journal of Learning in Higher Education 33 (2): 143-165. doi:10.18848/2327-7955/CGP/v33i02/143-165.
  • Extent: 23 pages

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Abstract

This study explores the integration of generative artificial intelligence (AI) into the initial training of pre-service teachers through creative music projects. As AI becomes increasingly embedded in educational practice, teacher education must address its pedagogical potential and limitations. Grounded in qualitative, interpretive, and exploratory methods, the research examines how pre-service teachers engage with AI-supported music creation by comparing experiences with and without the use of generative AI tools, using individual reflections and group e-portfolios for triangulation. Thematic analysis of individual reflections and group e-portfolios identified key opportunities and challenges associated with AI integration. Findings suggest that generative AI can broaden access to creative engagement by enhancing inclusivity, encouraging experimentation, and expanding musical expression. However, tensions also emerged concerning authorship, learner autonomy, and dependence on algorithmic output. The comparative structure of the learning experience enabled participants to reflect critically on the pedagogical implications of AI use. While non-AI processes demanded greater technical skill, they were associated with deeper collaboration, creative decision-making, and artistic ownership. This study contributes to current discussions on digital pedagogy and teacher education by highlighting the need for ethically informed, critically guided AI practice in creative disciplines. It emphasizes the importance of interdisciplinary, reflective practice in developing teacher agency, digital competence, and inclusive pedagogical approaches within higher education.