Treffer: Mapping and clustering analysis on UIC in animation education: A bibliometric analysis.

This study aims to analyze the trends, core themes, and challenges in University-Industry Cooperation (UIC) in animation education, particularly in the context of vocational education in China, through a bibliometric analysis. Using data from articles published between 1999 and 2021, this study applies bibliometric methods, including citation analysis, bibliographic coupling, and keyword co-occurrence analysis, to examine the evolution of research on UIC in animation education. The study utilizes Scopus as the primary database and employs VOSviewer and RStudio software for data visualization and analysis. The bibliometric analysis reveals a significant increase in publications on UIC in animation education, especially after 2015. It identifies key research areas, such as the integration of industry and education, school-enterprise cooperation, and the role of vocational colleges in bridging the gap between education and industry. The study also highlights challenges in aligning educational practices with industry needs, insufficient enterprise participation, and the need for more integrated models of cooperation. The findings indicate that while research on UIC in animation education has grown substantially, there are still significant gaps, particularly in creating deeper, long-term industry partnerships. The study suggests that more innovative models, such as co-designed curricula and shared innovation centers, are needed to enhance the effectiveness of UIC in this field. This study provides valuable insights for policymakers, educators, and industry stakeholders, emphasizing the importance of improving UIC models to meet the evolving needs of the animation industry. The findings suggest exploring deeper collaboration models and strengthening government support for industry-education integration. [ABSTRACT FROM AUTHOR]

Copyright of International Journal of Innovative Research & Scientific Studies is the property of International Journal of Innovative Research & Scientific Studies and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)