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Exploring the impact of AI-assisted practice applications on music learners' performance, self-efficacy, and
Jiayi Ou1, João Nogueira1, Chao Qin2
1CESEM/NOVA FCSH, Faculty of Social Sciences and Humanities, NOVA University of Lisbon, Lisbon, Portugal.
Introduction:
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.
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