Artificial intelligence (AI) already influences the practice of education, and the pedagogical impacts of AI on the vocal training are not theorized sufficiently. The paper proposes a theory that describes the idea of AI-improved change in the sphere of vocal education in the Chinese higher education. The paper conceptualizes AI as more than a technological tool based on the embodied and experiential learning, self-regulated learning and purposeful practice, and human-AI collaborative creativity. The three changes in training the voice which were identified during the analysis are the change of teacher-cantered training to feedback-based and data-driven learning, the change of experience-based training to reflective and self-regulated training, and the change of individual practice to a human-artificial intelligence learning. The feedback systems that have been improved with the help of AI enable to track the performance constantly and encourage the isolated development of the skills, in the meantime, the adaptive learning environment strengthens the feeling of metacognition and habits of regular practicing. In the meantime, AI-based creative spaces are used to strengthen the interpretive exploration and impose the artistic agency. The study is contextualized on the higher education system in the Chinese system in which the focus has been on the imperative to execute pedagogically, teacher digital competence, equitable access and cultural responsiveness. Offering the theoretically grounded perspective, the paper will contribute to the enhancement of the existing discourse on the topic of technology-enhanced music education and will offer the contextually relevant ways of merging innovation and artistic integrity in the sphere of vocal training.

Tingyu Yan, Hong Yu. Artificial Intelligence and the Transformation of Vocal Pedagogy: A Conceptual Framework for Chinese Higher Education. Frontiers in Educational Research (2026), Vol. 9, Issue 3: 119-128. https://doi.org/10.25236/FER.2026.090318.

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