Crafting Effective Curricula for Chinese Students with Use of Artificial Intelligence for Art Education

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Guangyu Wu
Yupeng Liu

Abstract

This study examined how artificial intelligence (AI) could be effectively integrated into art education curricula for Chinese students across primary, secondary, and tertiary levels. Drawing data from 3,715 students across six institutions in four major Chinese cities, the research assessed the impact of AI tools on student engagement, creative expression, and visual literacy. Exploratory data analysis revealed that students who reported higher motivation, ease of use, and usefulness of AI feedback tended to perform better in visual literacy assessments. Visual Literacy Score was significantly correlated with Motivation Level (r = 0.58), Ease of Use (r = 0.54), and
AI Feedback Usefulness (r = 0.51), highlighting these as key predictors of success. Multiple linear regression analysis confirmed that AI Familiarity, Ease of Use, and Motivation Level were statistically significant predictors, with the model explaining 43% of the variance in Visual Literacy Score. Machine learning models further validated these findings. Among Random Forest, Gradient Boosting, and XGBoost regressors, the XGBoost model achieved the highest accuracy (RMSE = 12.3, MAE = 8.7). SHAP analysis revealed AI Familiarity and Feedback Usefulness as dominant contributors to predictive power, with interaction plots showing that students reporting fewer technical challenges alongside high ease of use scored highest in literacy. The results revealed that curricular frameworks integrating user-friendly AI tools, sustained exposure, and motivational supports were most effective. Tertiary students and students from Guangzhou and Shanghai consistently had higher levels of performance in relation to their peers, indicating that regional exclusiveness and development disparity exist in relation to readying for AI. This research provided relevant suggestions for development of a culturally responsive and technology adaptable AI curriculum for Chinese art education.

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How to Cite
Guangyu Wu, & Yupeng Liu. (2025). Crafting Effective Curricula for Chinese Students with Use of Artificial Intelligence for Art Education . CINEFORUM, 65(3), 202–217. Retrieved from https://revistadecineforum.com/index.php/cf/article/view/450
Section
Journal Article