人工智能素养、人工智能焦虑与大学音乐专业学生职业乐观：一项横断面研究

ORIGINAL RESEARCH article

Front. Psychol.

Sec. Educational Psychology

• Xihua University, Chengdu, China

Abstract

Objective: To examine the levels of artificial intelligence (AI) literacy, AI anxiety, and career optimism among university music students, their associations, and the independent associations of AI literacy and AI anxiety with career optimism after adjustment for relevant background factors. Methods: A cross-sectional survey was conducted from May to July 2026 among students from five undergraduate music institutions in eastern China using convenience sampling. A total of 453 valid questionnaires were included in the analysis. Participants completed the Artificial Intelligence Literacy Scale for Chinese College Students (AILS-CCS), the Chinese version of the Artificial Intelligence Anxiety Scale (AIAS), and the Career Optimism Subscale (COS). Data were analyzed using descriptive statistics, independent-samples t tests, one-way analysis of variance, Pearson correlation analysis, and hierarchical multiple linear regression. Results: Mean scores for AI literacy, AI anxiety, and career optimism were 52.97 ± 10.05, 83.85 ± 22.96, and 37.87 ± 8.02, respectively. Students with prior AI training and those reporting more frequent AI use showed higher AI literacy and career optimism and lower AI anxiety. AI literacy was positively associated with career optimism (r = 0.444, p < 0.001), whereas AI anxiety was negatively associated with career optimism (r = −0.461, p < 0.001). After adjustment for gender, year of study, music specialization, prior AI training, and frequency of AI use, AI literacy remained positively associated with career optimism (β = 0.314, p < 0.001), whereas AI anxiety remained negatively associated with career optimism (β = −0.326, p < 0.001). The final model explained 33.0% of the variance in career optimism. Conclusion: AI literacy and AI anxiety were independently associated with career optimism among university music students. These findings suggest that students' perceptions of AI-related competence and technological concerns are relevant to their career expectations. Music institutions may consider AI education that combines practical competence with critical understanding of AI's implications for artistic identity, professional value, and future career development. Future longitudinal research is needed to clarify the temporal relationships among AI literacy, AI anxiety, and career optimism.

Keywords

AI education, Artificial intelligence anxiety, Artificial Intelligence literacy, Career development, Career optimism, University music students

Received

08 August 2026

Accepted

30 September 2026

Copyright

© 2026 Du. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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