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With the continuous development of globalization, internationalization, and diversification trends, the localization of educational theories has increasingly attracted the attention of countries around the world, especially developing countries (C. Zhang, 2019). In China, the Orff music education system, as one of the most widely distributed music education systems in the world, has had a significant impact on music education and has gradually developed into a comprehensive and systematic educational direction in the field of music education in China. With its unique teaching methods and diversified teaching contents, which focus on cultivating students' musical expression, creativity, and cooperation ability, Orff music education is well recognized and respected by the Chinese education sector (Rui, 2021).
Despite its achievements in China, Orff music education is currently facing challenges, such as integrating Orff music education with Chinese cultural traditions and localizing educational theories. (Lai, 2022). As a country with a long history and rich culture, China has unique musical traditions and aesthetic concepts. Therefore, to localize Orff music education it needs to be combined with Chinese music culture to make it more in line with the needs and characteristics of Chinese students. This requires not only localizing and improving Orff music education, but also strengthening teacher training and developing teaching materials to adapt to the reality of Chinese music education (Huang & Yu, 2021).
On the other hand, with the rapid development of big data analytics technology, the education field has gradually begun to explore how to use big data analytics to improve the education model and teaching methods (Hong & Luo, 2021). Big data analytics can help educators better understand students' learning situations, interests, and learning styles so as to carry out personalized teaching design and guidance. In Orff music education, big data analytics can help educators better understand students' music literacy levels, music interests, and development potential, and they can provide them with targeted music teaching programs. By using big data analysis technology (Adjepong, 2021), Orff music education can better meet the needs of Chinese students' individualized development and improve the effectiveness and quality of music education.
However, there are some challenges and dilemmas in promoting the localization of Orff music education and the application of big data analytics technology in music education (Maronna, 2018). The balance between globalization and localization is a key issue, and how to inherit the core concepts and methods of Orff music education while integrating Chinese music culture and educational practices needs to be explored and solved by educators and researchers working together (Sun, 2021). In addition, the application of big data analytics technology also needs to consider issues such as data privacy and security to ensure the protection and legitimate use of student information.
To overcome these challenges, the following strategies can be adopted. First, practitioners can strengthen teacher training to improve teachers' understanding and knowledge of Chinese music culture, so that they can combine Orff music education with Chinese music traditions and flexibly apply them in their teaching practice. Secondly, they can develop localized teaching materials and teaching resources that meet the needs of Chinese students, integrate Chinese music elements into Orff music education, enrich the content of teaching materials, and stimulate students' interest and creativity (Y. Zhang & Yi, 2021). At the same time, with the help of big data analysis technology, they can collect students' learning data and feedback information, provide teachers with personalized teaching guidance, and promote students' comprehensive development. In addition, it is also necessary to strengthen exchanges and cooperation with other countries and regions in music education, learn from their successful experiences, and promote the localized development of Orff music education in China.
This paper aims to explore how to localize the Orff music education system based on the method of big data analysis to meet the music education needs of Chinese students and provide a personalized teaching mode. It also emphasizes the combination of big data technology and local culture in order to develop a music education system suitable for Chinese soil.