AI Technology for Education Management in Guangdong University of Finance
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The objectives of this research were (1) To investigate the current level of AI technology proficiency among faculty at Guangdong University of Finance across five core dimensions (2) To analyze internal and external influencing factors that shape teachers' AI technical competency (3) To formulate targeted promotion pathways for improving faculty's AI competence in teaching management. This study employs a mixed-methods design research. The sample were 248 valid full-time teachers and teaching administrators from seven disciplines. The instruments were a questionnaire and semi-structured interview outlines. The statistical software using frequency, percentage, mean, standard deviation, Pearson correlation, and multiple linear regression. The results revealed that 1) The overall AI proficiency of surveyed faculty was at a moderate level, ranked from high to low as AI practical application, AI cognition and attitude, AI tool selection and application, AI content design and production, and AI teaching evaluation and reflection. 2) School environment and national policies exerted significant positive effects on multiple dimensions of teachers' AI proficiency; disciplinary concept and peer demonstration also acted as key positive influencing factors, while individual subjective awareness had no statistically significant impact. 3) Two sets of improvement paths were summarized: external optimization measures and personal self-improvement paths. The research results can provide practical references for finance-oriented universities to improve faculty AI competency through scientific management.
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