ScholarWorks@숙명여자대학교

초록

This study investigated how pre-service music teachers engaged with ChatGPT when designing music lessons, using an integrated framework of Expectation-Confirmation Theory (ECT) and the Technology Acceptance Model (TAM). 29 pre-service music teachers from two universities in South Korea participated in a six-week practicum. Quantitative data were collected through structured surveys, complemented by qualitative insights from reflective journals. The results revealed that expectation significantly influenced both confirmation and satisfaction, while confirmation marginally affected satisfaction. Satisfaction emerged as the strongest predictor of sustained usage intention, whereas social influence and facilitating conditions did not show significant direct effects. Qualitative findings indicated that ChatGPT supported creative idea generation and instructional exploration. Participants also expressed raised concerns about musical accuracy and the reliability of AI-generated content. These results highlight the need for teacher education programs to cultivate critical pedagogical judgement alongside technical proficiency in AI-supported lesson design.

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