Innovation and Application of Artificial Intelligence in Basic Art Courses in Vocational College

Abstract

In the context of the deep integration of digitalization and artificial intelligence technology into higher education, basic art courses in universities are facing an urgent need for innovative teaching models. This study focuses on 30 first-year art students from Quanzhou Light Industry Vocational College. Adopting a quasi experimental research design, combined with pre-test and post test comparisons, questionnaire surveys, interviews, and action research methods, the aim is to explore the application effect of artificial intelligence assisted teaching in basic art courses in universities. The study conducted empirical analysis around the three core dimensions of students' academic performance, practical operation ability, and learning satisfaction. The results showed that AI assisted teaching can significantly improve students' academic performance in art basic courses, with an average score increase of 7.13 points, especially in the dimension of creative uniqueness; Students' practical skills such as dynamic capture and proportional structure have significantly improved; Students' overall satisfaction with AI assisted learning reached 4.25 points (on a 5-point scale), recognizing its value in skill enhancement and creative efficiency optimization. At the same time, research has found that AI tools have high operational complexity and some students have a tendency towards technology dependence. Based on this, this study proposes suggestions such as establishing a "technology+ humanities" collaborative evaluation mechanism and avoiding technology dependence. This study validates the effectiveness of combining artificial intelligence with basic art courses in universities, providing practical reference and theoretical support for the digital transformation of vocational art education.