AI 기반 성악 교육의 기술수용에 관한 연구: AI 피드백 신뢰, 자기조절 연습, 연습 지속성의 매개효과를 중심으로

The purpose of this study was to structurally examine the effects of technology acceptance factors related to AI-based vocal education on self-regulated practice strategies and practice persistence among Chinese university students majoring in vocal music. To this end, the Technology Acceptance Model (TAM) was adopted as the theoretical framework, and the causal relationships among perceived ease of use, perceived usefulness, trust in AI feedback, self-regulated practice strategies, and practice persistence were analyzed using structural equation modeling. The results indicated that perceived ease of use had significant positive effects on perceived usefulness and trust in AI feedback, while perceived usefulness also exerted a significant positive effect on trust in AI feedback. These findings suggest that when learners perceive AI-based vocal education as easy to use and useful for learning, they are more likely to trust the feedback provided by AI systems. Furthermore, trust in AI feedback had a significant positive effect on self-regulated practice strategies, indicating that greater trust in AI feedback promotes self-regulatory practice behaviors such as goal setting, self-monitoring, and error correction. In addition, self-regulated practice strategies had a significant positive effect on practice persistence, demonstrating that learners who actively employ self-regulated strategies are more likely to sustain long-term practice. Overall, these results highlight that AI-based vocal education plays an important role beyond mere technological adoption by facilitating learners’ self-regulated practice and practice persistence, and they provide empirical evidence to inform the design of AI-based educational systems and the development of effective teaching and learning strategies in the field of arts education.