Harmonising Minds: How <scp>AI</scp> ‐Powered Learning Tools Shape Music Education Students' Cognitive Load, Well‐Being and Academic Success

Abstract

ABSTRACT This study examines the role of AI‐powered learning tools in influencing cognitive load, well‐being and academic success among music education students, with a focus on technology acceptance as a key factor. Data were collected through a random sampling of 454 Chinese music students (192 males, 262 females) aged 18–24, with varying levels of proficiency in AI tools. The study employed the Technology Acceptance Model (TAM) Questionnaire, Warwick‐Edinburgh Mental Well‐Being Scale (WEMWBS), a self‐reported academic performance questionnaire, and the Cognitive Load Scale (CLS). Data analysis was conducted using SPSS (version 27) and structural equation modelling (SEM) to explore complex interactions among variables. Findings reveal a positive correlation between technology acceptance and reduced cognitive load, increased well‐being and improved academic success. Higher perceived ease of use and usefulness of technology, as per TAM, contribute to lower cognitive load, greater focus and enhanced task efficiency, thereby supporting well‐being and academic performance. These results highlight the importance of technology acceptance in managing cognitive load and optimising educational outcomes within robotics‐integrated music education environments.