Promoting pre-service music teachers’ TPACK with generative AI: an intervention through designing with AI

Generative artificial intelligence (GenAI) presents transformative opportunities for education, yet its integration into music teacher preparation remains underdeveloped. Two critical gaps exist: (1) scant empirical studies on how pre-service music teachers can leverage GenAI to develop their expertise; and (2) the potential of designing with AI to develop technological pedagogical content knowledge (TPACK) in music education is unexplored, despite evidence of the effectiveness of learning by design in other disciplines. This study implemented a six-week designing with AI intervention grounded in TPACK framework, engaging 59 pre-service music teachers in collaborative GenAI-assisted lesson design. Pre-service music teachers employed GenAI tools to develop music lesson plans incorporating the 5E instructional model. Mixed-methods analysis indicated that this program: (1) significantly enhanced pre-service music teachers’ GenAI-specific TPACK across all dimensions; (2) revealed three phases of pre-service teacher development of GenAI-supported music lesson design; and (3) fostered pre-service music teachers’ critical understanding of GenAI’s pedagogical affordances in music education. As an early empirical study investigating pre-service music teachers’ GenAI-TPACK development, this research demonstrates how collaborative design with AI fosters pre-service music teachers’ GenAI-TPACK development.

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Publication Details

Journal
Computers and Education Artificial Intelligence
Published
2025-12-01
DOI
https://doi.org/10.1016/j.caeai.2025.100525
Primary Topic
Diverse Music Education Insights
Type
article
Field-Weighted Citation Impact
0.00
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article

Promoting pre-service music teachers’ TPACK with generative AI: an intervention through designing with AI

Haiying Li, Ching Sing Chai, Xinlei Wang
Computers and Education Artificial Intelligence
Diverse Music Education Insights
article

Promoting pre-service music teachers’ TPACK with generative AI: an intervention through designing with AI

Haiying Li, Ching Sing Chai, Xinlei Wang
article en

Abstract

Generative artificial intelligence (GenAI) presents transformative opportunities for education, yet its integration into music teacher preparation remains underdeveloped. Two critical gaps exist: (1) scant empirical studies on how pre-service music teachers can leverage GenAI to develop their expertise; and (2) the potential of designing with AI to develop technological pedagogical content knowledge (TPACK) in music education is unexplored, despite evidence of the effectiveness of learning by design in other disciplines. This study implemented a six-week designing with AI intervention grounded in TPACK framework, engaging 59 pre-service music teachers in collaborative GenAI-assisted lesson design. Pre-service music teachers employed GenAI tools to develop music lesson plans incorporating the 5E instructional model. Mixed-methods analysis indicated that this program: (1) significantly enhanced pre-service music teachers’ GenAI-specific TPACK across all dimensions; (2) revealed three phases of pre-service teacher development of GenAI-supported music lesson design; and (3) fostered pre-service music teachers’ critical understanding of GenAI’s pedagogical affordances in music education. As an early empirical study investigating pre-service music teachers’ GenAI-TPACK development, this research demonstrates how collaborative design with AI fosters pre-service music teachers’ GenAI-TPACK development.

Computers and Education Artificial IntelligenceVol. 9
Chinese University of Hong Kong (HK), Perfect Harmony Health (US)
Openalex Percentile: Top 64%
Diverse Music Education Insights
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Promoting pre-service music teachers’ TPACK with generative AI: an intervention through designing with AI — Haiying Li, Ching Sing Chai, et al. · Computers and Education Artificial Intelligence (2025) | TGRS Research Map | TGRS