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Identification of bottlenecks and solutions for secondary school music teachers’ career development in Jiangxi Province based on data mining

Shunwei Liu

Abstract


In the enchanting realm of music, where talent and passion intertwine, music teachers play a vital role in nurturing young minds and shaping the future of music. However, in Jiangxi Province, these dedicated educators face numerous challenges that hinder their career growth. To uncover the bottlenecks and offer viable solutions, data mining provides a powerful tool for analysis. Through the lens of data mining, this article delves into the unique challenges faced by music teachers in Jiangxi Province. By examining factors such as limited resources, inadequate support systems, and outdated teaching methods, we aim to identify the underlying issues that impede their professional development. Moreover, we explore practical strategies and innovative approaches that can be implemented to overcome these barriers. Join us on this melodious journey as we combine data-driven insights with our expertise to illuminate the path towards a thriving career for music teachers in Jiangxi Province. With a focus on sustainability, inclusivity, and fostering a nurturing environment, we believe that by empowering educators, we can cultivate a harmonious future for music education in the region.


Keywords


identification; bottlenecks; solutions; secondary school; music teachers; career development; Jiangxi province; data mining

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References


1. Eccles JS. Who am I and what am I going to do with my life? Personal and collective identities as motivators of action. Educational Psychologist. 2009, 44(2), 78-89.

2. Inan F. Factors affecting technology integration in K-12 classrooms: A path model. Educational Technology Research and Development. 2010, 58(2), 137-154.

3. Stronge JH, Ward TJ, Grant LW. What makes good teachers good? A cross-case analysis of the connection between teacher effectiveness and student achievement. Journal of Teacher Education. 2011, 62(4), 339-355.

4. Smith J, Perez R. The Convergence of Music Teaching and Artificial Intelligence. Music Education Journal. 2020, 64(4), 5-14.

5. Johnson M. Technological Advances in Music Education: A Century Review. Journal of Music and Technology. 2018, 12(2), 45-58.

6. Wang X, Chen Y, Liu Z. Modern Approaches to Music Teaching: An Empirical Study. Journal of Educational Research. 2019, 15(3), 210-225.

7. Lee A, Rodriguez B. Emotional Computing in Artistic Disciplines: An Overview. International Journal of Artificial Intelligence in Education. 2021, 33(1), 100-115.

8. Martin JP. The Rise of Intelligent Teaching: Harnessing AI in Music Education. Journal of Music and Technology. 2022, 21(1), 45-59.

9. Liu H, Chen Y. Wisdom Teaching in the Digital Age: A New Paradigm. Journal of Modern Education. 2017, 14(3), 22-38.

10. Smith R, Rodriguez P. Autonomous Learning in Music: The Role of Technology. Music Education Quarterly. 2019, 10(2), 51-66.

11. Griffin A. Nurturing Next-Gen Music Talents: Tech-Savviness and Beyond. International Journal of Music and Technology. 2020, 16(1), 43-55.

12. Brown L, Harris J. Reimagining Music Pedagogy: Traditional Approaches in Contemporary Contexts. Journal of Music Teaching and Learning. 2021, 19(4), 5-20.

13. Wiener N. Cybernetics or Control and Communication in the Animal and the Machine. MIT Press; 1961.

14. Turner L, Richardson G. The Interdisciplinary Essence of Modern Music Education. Journal of Contemporary Education. 2021, 18(2), 101-113.

15. Edwards RL, Thompson S. Embracing Change in Education: The Role of AI and Cybernetics. International Journal of Educational Innovations. 2023, 14(4), 32-47.

16. Kumar A, Johnson M. Technological advancements and their impact on contemporary teaching methodologies. International Review of Research in Educational Innovations. 2021, 13(2), 56-70.

17. Romero C, Ventura S. Educational data mining: A review of the state of the art. IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews). 2020, 40(6), 601-618.

18. Conway C, Christensen S. Professional Development and the Beginning Music Teacher. Contributions to Music Education. 2006, 33(1), 9–25. http://www.jstor.org/stable/24127197

19. Kakada P, Deshpande Y, Bisen S. Technology support, social support, academic support, service support, and student satisfaction. Journal of Information Technology Education: Research. 2019, 18, 549-570. https://doi.org/10.28945/4461

20. Sahito Z, Vaisanen P. Factors Affecting Job Satisfaction of Teacher Educators: Empirical Evidence from the Universities of Sindh Province of Pakistan. Journal of Teacher Education and Educators. 2017, 6(1), 5-30.




DOI: https://doi.org/10.32629/jai.v7i5.1407

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Copyright (c) 2024 Shunwei Liu

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