ArticleFrontiers in psychology2026
Instrumental music teachers' perceptions and acceptance of Al integration in teaching: a mixed-methods study based on the UTAUT2 model.
Article in Frontiers in psychology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: The application of Artificial Intelligence (AI) is fast becoming widespread in educational environments, especially within the field of music education. However, instrumental music teachers, who are highly dependent on their physical instructions and aesthetic judgement, have never undergone an analysis of how they perceive and embrace AI technologies. This study is based on an expanded version of Acceptance and Use of Technology (UTAUT2), which includes two additional variables that relate to the context: Perceived Threat to Teaching Artistry (PTTA) and Perceived Irreplaceability of Embodied Teaching (PIET). Methods: The method employed by this study was an explanatory sequential mixed methods approach, wherein the first phase involved the use of Partial Least Squares Structural Equation Modeling (PLS-SEM) on survey data gathered from 352 in-service instrumental music teachers in China. In the qualitative phase, reflexive thematic analysis was conducted on semi-structured interviews with 17 instrumental music teachers. Results: Results show that performance expectancy, habit, hedonic motivation, effort expectancy, and social influence significantly and positively predict behavioral intention, while facilitating conditions and price value show no significant effect. Both PTTA and PIET significantly and negatively affect behavioral intention, with PIET's negative effect being more pronounced among experienced teachers and string/wind instrument teachers. The qualitative phase yielded four core themes, revealing a conditional acceptance pattern: teachers acknowledge AI's supplementary value in basic skill training but firmly maintain their irreplaceable role in aesthetic judgment, individualized expressive guidance, and embodied interaction. Discussion: This study extends UTAUT2's applicability to the instrumental music teaching context, where artistry and embodiment are central, providing empirical evidence for designing and promoting AI teaching tools.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.