Determining the Behavioral Intention Scales in Lifelong Music Learning Using PLS-SEM Approach

• Main Authors: Wenjun Zheng, Lay, Yoon Fah
• Format: Article
• Language: English; English
• Published: Ani Publishing Ltd 2023
• Subjects: LB1025-1050.75 Teaching (Principles and practice); MT18 Music in colleges and universities
• Online Access: https://eprints.ums.edu.my/id/eprint/39183/1/ABSTRACT.pdf; https://eprints.ums.edu.my/id/eprint/39183/2/FULL%20TEXT.pdf; https://eprints.ums.edu.my/id/eprint/39183/

it is important to understand students' behavioral intention in lifelong music learning and antecedents that influence intent as it is the basis for promoting students' participation in lifelong music learning. This pilot study aimed to test the validity and reliability of adapted scales, which was prepared for measuring the interrelationship between past behavior, high-demanding parenting styles, attitude, subject norm, perceived behavior control, and behavioral intention in lifelong music learning, as well as in the Chinese context. Method: Participants (n=97) were asked to complete the scale and validate the scale multidimensionally using a second-generation measure, the Partial Least Square-Structural Equation Modelling (PLS-SEM) methodology. The reliability requirements were ascertained using outer loading, composite reliability, and Cronbach's Alpha. The convergent validity of the instrument was evaluated via the use of the average variance extracted, and the discriminant validity was verified through the use of cross-loading, the Fornell-Larcker criteria, and the Heterotrait-Monotrait criterion. Findings: After removing six indications, the research outcomes showed that all instruments were valid and reliable and may be utilized in future research. Implications for Research and Practice: The scale of this study can be used to obtain first-hand data on the source of lifelong music learning intention and behavior intention in lifelong music learning among Chinese university students. In future, through further data analysis, it can also be used to assess the importance of each path in the hypothetical model, contributing to the development of theories and models.