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Beyond output metrics: reframing AI-assisted vocal pedagogy through human learning and educational value.
1Shenzhen Technology University, Shenzhen, China.
Frontiers in Psychology
|July 16, 2026
Summary
Artificial intelligence (AI) in vocal pedagogy offers performance metrics but requires human-centered evaluation. AI tools should support, not replace, teacher guidance for effective, equitable, and sustainable music learning.
Area of Science:
- Music Education
- Artificial Intelligence
- Performance Science
Background:
- Artificial intelligence (AI) tools are emerging in music education, offering objective measures of vocal performance like pitch and timing.
- However, the educational value of AI in vocal pedagogy is not guaranteed by mere data precision.
- A critical gap exists between measurable vocal outputs and the learner's internal experience and pedagogical interpretation.
Purpose of the Study:
- To propose a framework for evaluating AI-assisted vocal pedagogy based on meaningful human learning.
- To explore how AI-generated evidence can be integrated into effective, equitable, and sustainable vocal development.
- To shift the perspective on AI from an autonomous evaluator to a supportive tool in music education.
Main Methods:
- Conceptual analysis drawing from educational psychology, performance science, and metacognitive music learning research.
- Development of a framework linking AI technical adaptation, human learning processes, and educational outcomes.
- Examination of AI feedback through the lenses of learner interpretation, practice regulation, motivation, and trust.
Main Results:
- AI-generated evidence must be interpreted by learners to foster meaningful learning and practice regulation.
- Effectiveness, equity, and sustainability are crucial criteria for assessing AI's role in vocal pedagogy.
- AI's value is maximized when it supports human interpretation, reflection, and teacher-student dialogue.
Conclusions:
- AI should augment, not replace, the human element in vocal pedagogy.
- A human-centered approach is essential for integrating AI into music education effectively.
- AI tools can enhance vocal development by supporting pedagogical decision-making and fostering learner autonomy.
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