How AI Shapes Aesthetic Learning? Text Mining of MOOC Learner Comments

Against the backdrop of AI-powered transformation in aesthetic education, this study focuses on 15 aesthetic courses on “China University MOOC” platform. Based on learners' comments, it employs LDA topic modeling and sentiment analysis to explore learners' experience structures and emotional characteristics. The study identifies four core dimensions: learning gains, aesthetic practice, AI support, and artistic immersion. Among these, AI support occupies the largest proportion, while learning gains is relatively less prominent, indicating that evaluations of aesthetic education courses are shifting from outcome-oriented to process-oriented aesthetic experiences. Sentiment analysis results show that overall evaluations are primarily positive, accompanied by a relatively high proportion of neutral emotions, with significant differences in emotional structures across different themes. From the learners’ perspective, the study reveals the experience characteristics and evaluation logic of AI-supported aesthetic MOOCs, offering practical insights into how AI shapes aesthetic learning in the digital education context.