The Causal Model for Music Teaching of Universities in Shanxi Province
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บทคัดย่อ
The objective of this research is to study the causal model of music teaching in colleges and universities in Shanxi Province. A total of 520 students were selected from five universities in Shanxi Province from a population of 3,834 students. The data collection tools consisted of six questionnaires: The Music Education Effect Questionnaire, the Curriculum Design Questionnaire, the Teacher Professional Ability Questionnaire, the Student Learning Motivation Questionnaire, the Extracurricular Practice Participation Questionnaire, and the Educational Resource Input Questionnaire. The reliability values of the questionnaires were 0.925, 0.898, 0.903, 0.876, 0.881, and 0.869, respectively. Path analysis was employed for data analysis.
The results indicate that all variables are significantly positively correlated with the effect of music education. The hypothesized causal factor model is consistent with the empirical data (χ² = 9.642, df = 5, χ²/df = 1.928, GFI = 0.996, AGFI = 0.983, RMSEA = 0.031, SRMR = 0.009). Teacher professional ability has the greatest total influence on music education effect (0.715), followed by curriculum design (0.582), student learning motivation (0.326), educational resource input (0.294), and extracurricular practice participation. Student learning motivation has the greatest direct influence (0.463), followed by curriculum design (0.287), teacher professional ability (0.215), and educational resource input (0.172). Teacher professional ability has the greatest indirect influence (0.500), followed by extracurricular practice participation (0.268), curriculum design (0.295), and educational resource input (0.122). These five variables collectively explain 72.3% of the variance in music education outcomes.
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Barros, S., Marinho, H., & Pereira, A. (2024). Music Performance Anxiety in Portuguese Higher Education: Contextual Factors, Perceptions, and Strategies. Musicae Scientiae, 28(2), 287–307.
Biggs, J., & Tang, C. (2011). Teaching for Quality Learning at University. (4th ed.). Maidenhead, England: Open University Press.
Brown, A. (2018). Assessing Music Education: A Holistic Approach. Journal of Music Education, 35(2), 45–62.
Chen, J. (2018). Challenges and Prospects of Music Education in Chinese Colleges and Universities. Journal of Music Education, 45(2), 78–92.
Deci, E. L., & Ryan, R. M. (2000). The “What” and “Why” of Goal Pursuits: Human Needs and the Self-Determination of Behavior. Psychological Inquiry, 11(4), 227–268.
Frenzel, A. C., Pekrun, R., Goetz, T., Daniels, L. M., Durksen, T. L., Becker-Kurz, B., & Klassen, R. M. (2016). Measuring Teachers’ Enjoyment, Anger, and Anxiety: The Teacher Emotions Scales (TES). Contemporary Educational Psychology, 46, 148–163.
Hattie, J. (2009). Visible Learning: A Synthesis of Over 800 Meta-Analyses Relating to Achievement. London, England: Routledge.
Kong, Q., Zhang, J., & Wang, Y. (2022). Technology-Enhanced Music Education: Pedagogical Transformation and Learning Outcomes in Higher Education. International Journal of Music Education, 40(3), 456–472.
Liu, S. (2022). Music Education in the Colleges and Universities of China: Current Problems and Response Strategies. Malaysian Journal of Chinese Studies, 11(2), 25–42.
Wang, Y. (2025). Challenges in Music Education in Chinese Colleges and Universities. Journal of the Knowledge Economy, 16(2), 7934–7958.
Xu, P., & De Vera, J. A. (2023). The Impact of Technology on Music Education. International Journal of Science and Engineering Applications, 12(11), 44–47.