Ou, JiayiNogueira, JoaoQin, Chao2026-03-192026-03-192025-10-131664-1078PURE: 157969533PURE UUID: 23b17671-9b93-4aee-a089-d23e8dc3c5aeWOS: 001600502200001PubMed: 41159183http://hdl.handle.net/10362/201641UIDB/00693/2020 UIDP/00693/2020Introduction: Despite significant advancements in artificial intelligence (AI) applications across various disciplines, research on AI’s psychological impacts in music learning contexts remains limited. This study explores the effects of AI-assisted practice apps on violin students’ self-efficacy, performance outcomes and Self-Regulated Learning (SRL).Methods: A four-month quasi-experimental study was conducted with 40 violin majors from a conservatory in South China. All participants received identical classroom instruction and maintained equivalent daily practice time, but the experimental group (n = 20) used AI-assisted practice app while the control group (n = 20) practiced using regular practice methods.Results: Mixed-effects modelling revealed differentiated impacts on self-efficacy dimensions: while the control group experienced natural decline in Music Learning Self-Efficacy (MLSE) as task difficulty increased, AI intervention enabled the experimental group to maintain stable learning confidence. More notably, the experimental group achieved significant improvements in Music Performance Self-Efficacy (MPSE) with large effect sizes, indicating that AI-assisted practice app possesses distinct advantages in enhancing performance confidence. In terms of performance outcomes, the experimental group demonstrated significant improvement while the control group showed a declining trend. Thematic analysis revealed that AI-assisted practice apps support self-regulated learning (SRL) across three critical phases: providing goal-setting and strategic planning support during the forethought phase, facilitates self-monitoring and self-control during the performance phase, and enabling objective evaluation and strategic adjustment during the self-reflection phase.Discussion: This study enriches understanding of self-efficacy theory in AI technology-enhanced learning environments and demonstrates AI technology’s educational value in instrumental music learning.151193019engAI-assisted appMusicians' performanceMusicians' self-efficacyQuasi-experimental studySelf-regulated learningjournal article10.3389/fpsyg.2025.1675762https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=nova_api&SrcAuth=WosAPI&KeyUT=WOS:001600502200001&DestLinkType=FullRecord&DestApp=WOS_CPLhttps://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2025.1675762/full