{"title":"Assessment of the Relationship Between Music Students' Self-Efficacy, Academic Performance and Their Artificial Intelligence Readiness","authors":"Xinzheng Wang, Peiwen Li","doi":"10.1111/ejed.12761","DOIUrl":null,"url":null,"abstract":"<div>\n \n <p>In recent years, the intersection of self-efficacy and technological readiness has become increasingly relevant in educational research, particularly within specialised fields like music education. Understanding how these factors interplay can offer valuable insights into enhancing educational practices and fostering academic achievement among music students. This study investigates the relationship between music students' self-efficacy, academic performance and artificial intelligence (AI) readiness within the context of Chinese Music education. Adopting a random sampling method, the researchers distributed questionnaires to 1082 Chinese music students to assess their self-efficacy, academic performance and AI readiness. Utilising SPSS (version 27) and AMOS (version 24) for data analysis, the researchers explored the statistical relationships among these variables. The findings indicate that a significant 63% of variations in students' academic performance can be explained by the combined influence of self-efficacy and AI readiness. This highlights a strong relationship between these factors and students' overall success in their professional pursuits. Specifically, students' self-efficacy uniquely predicts 52% of changes in academic performance, emphasising the importance of self-belief in academic achievement, whereas their AI readiness uniquely predicts 60% of changes in academic performance, showcasing the critical role of technological fluency in driving academic success. These results provide valuable insights into the interconnected dynamics of self-efficacy, academic performance and AI readiness among Chinese music students. The study underscores the significance of confidence, technological proficiency and their impact on students' educational trajectories, offering implications for enhancing educational practices and fostering student success in the context of music education.</p>\n </div>","PeriodicalId":47585,"journal":{"name":"European Journal of Education","volume":"59 4","pages":""},"PeriodicalIF":2.8000,"publicationDate":"2024-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"European Journal of Education","FirstCategoryId":"95","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/ejed.12761","RegionNum":3,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"EDUCATION & EDUCATIONAL RESEARCH","Score":null,"Total":0}
引用次数: 0
Abstract
In recent years, the intersection of self-efficacy and technological readiness has become increasingly relevant in educational research, particularly within specialised fields like music education. Understanding how these factors interplay can offer valuable insights into enhancing educational practices and fostering academic achievement among music students. This study investigates the relationship between music students' self-efficacy, academic performance and artificial intelligence (AI) readiness within the context of Chinese Music education. Adopting a random sampling method, the researchers distributed questionnaires to 1082 Chinese music students to assess their self-efficacy, academic performance and AI readiness. Utilising SPSS (version 27) and AMOS (version 24) for data analysis, the researchers explored the statistical relationships among these variables. The findings indicate that a significant 63% of variations in students' academic performance can be explained by the combined influence of self-efficacy and AI readiness. This highlights a strong relationship between these factors and students' overall success in their professional pursuits. Specifically, students' self-efficacy uniquely predicts 52% of changes in academic performance, emphasising the importance of self-belief in academic achievement, whereas their AI readiness uniquely predicts 60% of changes in academic performance, showcasing the critical role of technological fluency in driving academic success. These results provide valuable insights into the interconnected dynamics of self-efficacy, academic performance and AI readiness among Chinese music students. The study underscores the significance of confidence, technological proficiency and their impact on students' educational trajectories, offering implications for enhancing educational practices and fostering student success in the context of music education.
期刊介绍:
The prime aims of the European Journal of Education are: - To examine, compare and assess education policies, trends, reforms and programmes of European countries in an international perspective - To disseminate policy debates and research results to a wide audience of academics, researchers, practitioners and students of education sciences - To contribute to the policy debate at the national and European level by providing European administrators and policy-makers in international organisations, national and local governments with comparative and up-to-date material centred on specific themes of common interest.