ArticleFrontiers in psychology2026
Deliberate practice in the age of artificial intelligence: how AI-assisted practice supports self-regulated learning and expert performance development in conservatory musicians.
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.
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Abstract
Introduction: Deliberate practice is central to expert performance development, yet the conditions under which practice produces sustained gains remain contested. AI-assisted music practice applications provide adaptive feedback, intelligent scheduling, automated error detection, and performance analytics, potentially supporting deliberate practice. This study examined whether engagement with AI-assisted practice applications is longitudinally associated with expert performance development among conservatory musicians through self-regulated learning (SRL). Methods: A three-wave longitudinal study was conducted over a 16-week academic semester with a target sample of 600 conservatory musicians. Of these, 512 completed all three waves (85.3%). Temporal associations among AI-assisted practice engagement, SRL, and instructor-rated musical performance were examined. Results: Significant longitudinal associations supported the proposed pathway. Greater engagement with AI-assisted practice applications was associated with subsequent SRL, which was in turn associated with later instructor-rated musical performance. These findings are consistent with a mediating role of SRL in the association between AI-assisted practice engagement and expert performance development. Discussion: AI-assisted practice applications may support expert performance development by fostering self-regulatory processes conducive to deliberate practice. However, because the study was observational rather than randomized and involved heterogeneous AI applications rather than a standardized intervention, the findings should be interpreted as longitudinal associations rather than causal effects. AI-assisted practice applications are therefore best conceptualized as pedagogical supports that facilitate conditions for deliberate practice rather than as deliberate practice itself.
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