Perceptions of artificial intelligence in university student affairs management: a quantitative study at Panzhihua University, China

A study conducted at Panzhihua University in China investigated perceptions of generative artificial intelligence (specifically DeepSeek) among various university stakeholders for student administrative work. The research aimed to address a gap in understanding local university stakeholders' views on domestic generative AI amidst its rapid adoption in Chinese higher education.

Why it matters

Understanding stakeholder perceptions of AI in administrative functions is crucial for effective technology integration and change management in educational institutions. This informs strategic planning regarding resource allocation, training, and policy development for AI implementation, directly impacting operational efficiency and service delivery.

Key insights

• AI adoption is experiencing rapid growth within Chinese higher education institutions.
• There is a recognized research gap concerning local university stakeholders' perceptions of domestic generative AI (DeepSeek) in student administrative management.
• The study employed a cross-sectional quantitative survey involving 386 participants, including undergraduates, postgraduates, faculty, and administrative staff at Panzhihua University.
• The methodology involved testing five research hypotheses based on the Technology Acceptance Model (TAM) and Unified Theory of Acceptance and Use of Technology (UTAUT) frameworks, with data analysis performed using R.
• The reported results indicate that the overall awareness rate of DeepSeek among participants reached a certain level, though the specific rate is not provided in the summary.
• Bonferroni correction was applied during data analysis to manage Type I errors in multiple comparisons.
• Composite scores were used exclusively for descriptive analysis due to identified low internal consistency across measurement items.

Source

Frontiers in Education — https://www.frontiersin.org/articles/10.3389/feduc.2026.1920133