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Vol.12, No.2, May 2023. ISSN: 2217-8309 eISSN: 2217-8333
TEM Journal
TECHNOLOGY, EDUCATION, MANAGEMENT, INFORMATICS Association for Information Communication Technology Education and Science |
The Development and Validation of a Metacognitive Questionnaire for Music Learning
Wen Li, Pravina Manoharan, Xuerong Cui, Fen Liu
© 2023 Pravina Manoharan, published by UIKTEN. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. (CC BY-NC-ND 4.0)
Citation Information: TEM Journal. Volume 12, Issue 2, Pages 1090-1099, ISSN 2217-8309, DOI: 10.18421/TEM122-55, May 2023.
Received: 25 January 2023. Revised: 11 April 2023.
Abstract:
Although music learners’ metacognition could regulate and improve their practice and performance, respectively, metacognitive measurement tools for music domains remain scarce. Hence, this study aimed to develop and validate a Metacognitive Questionnaire for Music Learning (MQML). Through item analysis, exploratory factor analysis (EFA), and confirmatory factor analysis (CFA), two rounds of research were conducted on 513 valid questionnaires to analyze the item discrimination, reliability, and validity of the questionnaire. This study developed a questionnaire consisting of two subscales, eight factors, and 35 items. The MQML was explored and validated with a Cronbach’s alpha value of 0.960 for the overall scale, subscale Cronbach’s alpha values were 0.914 and 0.947. An eight-factor metacognitive structural model was validated for the first time in the music field. Essentially, MQML could provide empirical data for music students’ metacognition strategies and expand the current body of literature on music cognition.
Keywords – eight-factor, metacognitive questionnaire, metacognitive strategies, music metacognition, self-practice. |
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