AI-Based Feedback Systems in Piano Education: Effects on Technical Accuracy and Learner Autonomy
DOI:
https://doi.org/10.5216/mh.v26.85176Palavras-chave:
artificial intelligence, feedback systems, music pedagogy, musical performance quality, piano practice analysisResumo
This study aims to empirically evaluate whether the use of an AI-based feedback system, in combination with traditional instruction, can improve technical accuracy and promote learner autonomy among piano students, compared to a control group receiving only conventional training. The sample consisted of 240 first-year piano majors. Learner autonomy was assessed using the Autonomous Educational Learning Scale, while technical accuracy in piano performance was evaluated through multimodal analysis employing Onsets & Frames and MediaPipe software. The findings confirmed the positive impact of the AI-based feedback system (PFS-AI, Onsets & Frames, MediaPipe) on both learner autonomy and technical proficiency. A mixed-design ANOVA revealed significant main effects of time and group, as well as their interaction. The study offers practical and scholarly insights by empirically validating the effectiveness of AI-driven feedback systems, suggesting their potential to reduce instructional burden and enhance the quality of piano education.








