Application Status and Optimization Strategies of Generative AI in Cultural Graduation Projects: From the Perspective of University Teachers——A Case Study of Preschool Education Teachers at a University of Technology

Shunhe Wang(Guangdong University of Business and Technolog)

Abstract

This study aims to explore the application status, influencing factors and practical dilemmas of generative AI in cultural graduation projects at universities. A questionnaire survey was conducted among 36 supervising teachers, and empirical analysis was performed using descriptive statistics, Pearson correlation analysis and one-way analysis of variance (ANOVA). The results indicate that teachers generally hold a positive attitude toward generative AI. Nevertheless, universities fall behind in providing supporting training, standardized usage regulations and dedicated AI platforms. Teachers’ familiarity with generative AI, institutional training intensity and the completeness of relevant regulations are significant positive predictors of teachers’ application willingness and practical outcomes. Teachers’ working years, experience in supervising graduation projects and participation in training lead to significant differences in AI usage behaviors, while professional backgrounds show no remarkable impact. The main challenges include students’ excessive reliance on AI, insufficient academic rigor of AI-generated content, and the lack of sound software and hardware support systems. Accordingly, this paper proposes targeted strategies including hierarchical training, institutional improvement, dedicated platform construction and full-process supervision. The findings provide practical references for the digital reform of graduation projects in higher education.

Keywords

personalized formula; Pet nutrition supplement; Effect evaluation; Gene detection; AI algorithm; Standardization system

References

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Yang, N. C. (2023). Design-Based Research from the Perspective of Learning Science. Beijing: Educational Science Publishing House.

DOI: http://dx.doi.org/10.12345/jetm.v10i2.39508