FretMate: ChatGPT-Powered Adaptive Guitar Learning Assistant
Authors
Learning to play the guitar poses significant challenges for beginners, who often choose to practice alone to avoid the embarrassment of making mistakes in front of others. This isolation leads to a lack of timely feedback and encouragement, resulting in frustration and decreased motivation. Traditional learning methods fail to provide personalized and immediate support. To address these issues, we propose a GPT-powered guitar learning assistant, FretMate, that provides immediate error correction, personalized learning paths, and emotional support. The design was informed by formative interviews with six guitar instructors and six learners. We evaluated our assistant against the traditional self-guided practice in a controlled two-week study with 16 participants. Results showed that participants using FretMate improved in skill acquisition, engagement, and motivation compared to the control group. We discuss the po- tential of integrating conversational AI into instrument learning to provide personalized instruction and emotional engagement.
Research Questions / Practical Problems
Question signals indexed for this paper.
Research Questions
3- How can AI provide improvisational feedback and emotional support to improve learning experience and efficiency for self-taught guitar learners?Category: Music, Arts, and Performance TrainingSimilar questionsarrow_forward
- Can combining audio analysis and gesture recognition effectively identify and correct technical errors in guitar learning?Category: Music, Arts, and Performance TrainingSimilar questionsarrow_forward
- Can personalized learning paths and emotional support significantly improve music learners' practice persistence and motivation?Category: Music, Arts, and Performance TrainingSimilar questionsarrow_forward
Practical Problems
1- Beginner guitar learners easily lose interest due to a lack of feedback and emotional support.Category: Music, Arts, and Performance TrainingSimilar questionsarrow_forward
No related papers with ≥60% similarity
Based on Jaccard similarity of research subtopics & professions (≥60%)