Develop and adopt AI feedback systems that integrate visual and auditory feedback and automatically adapt students' practice plans¶

Strategy · All strategies
Evidence · no claims cited

Description¶

Based on the findings, the article recommends that future systems go beyond text-based analysis: "Gelecek çalışmalarda, görsel ve işitsel geri bildirim unsurlarını entegre eden ve öğrencinin çalışma planını otomatik olarak uyarlayabilen sistemlerin geliştirilmesi önerilmektedir." It further recommends that students regularly use AI-supported applications offering intonation and posture analysis, do out-of-class self-evaluation via mobile and free platforms, and treat feedback as a planning and motivation tool as well as a technical-development aid.

Design Implications¶

Context¶

Requirements¶

• Cooperation with software developers; ethical regulations; mobile-compatible systems combining intonation and posture analysis with visualization and sound features

Constraints¶

• The recommendation arises from a four-week, single-institution study limited to entonation measurement with two specific AI models

Target Learners¶

• violin and instrument students in higher education
• music teachers integrating AI into lessons

Target Learning Goals¶

• intonation and posture improvement
• out-of-class self-assessment and practice planning

Related Strategies¶

• Deliver AI-generated visual explanations adaptively based on learner engagement profiles rather than uniformly
• Multisensory Phonics Instruction
• Integrate AI-driven scaffolding with teacher-led offloading and refine feedback granularity to prevent over-scaffolding

Examples¶

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Key Sources¶

• Yakup Aksoy. (2026). Yapay zekâ, yapay zekâ söyle bana: Keman eğitiminde yapay zekâ destekli geri bildirimin entonasyona etkisine yönelik bir model çalışması. Online Journal of Music Sciences, 11(2). https://doi.org/10.31811/ojomus.1897062