The use of Artificial Intelligence in higher vocational colleges in Sichuan, China: a mixed-methods study of adoption, utilization, and policy implications

This study investigated the status of Artificial Intelligence (AI) adoption and utilization in higher vocational colleges in Sichuan Province, China, and examined the challenges and policy implications of institutional AI integration. Using a mixed-methods, descriptive-comparative design, we combined a survey of 1,085 respondents (administrators, teachers, and students) with interviews and on-site observations to profile prevalent AI tools, frequency and purposes of use, and the extent of AI integration in teaching, language learning, and research, while also comparing stakeholder perceptions and identifying barriers to effective adoption. Results indicate a moderate level of AI adoption in Sichuan’s vocational colleges: approximately 70–75% of faculty and administrators reported adopting AI tools, while student uptake was lower, with nearly one-quarter unsure whether they had used AI. Utilization was strongest for routine tasks and language learning (notably AI-supported translation and tutoring), whereas AI use for research-related activities remained comparatively limited. Domestic platforms such as Baidu ERNIE Bot and Alibaba’s Qwen were the dominant tools, consistent with China’s technology ecosystem and access constraints, whereas foreign models such as ChatGPT were used minimally. Formal AI capacity-building was scarce—fewer than 10% reported receiving structured training—yet individuals with prior training or institutional support showed higher usage. Statistical analyses further found no significant differences in overall AI utilization levels among students, teachers, and administrators, suggesting a broadly cohesive pattern of adoption across roles. Key challenges included limited training opportunities, inadequate infrastructure and access, uncertainty or resistance toward AI use, and concerns about data privacy and academic integrity. Based on these findings, we propose a comprehensive academic policy framework to guide the ethical and effective integration of AI across teaching, learning, research, and administration, emphasizing AI literacy programs, infrastructure enhancement, clear usage guidelines, and sustained implementation support, aligned with China’s educational modernization agenda.

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Publication Details

Journal
Frontiers in Education
Published
2026-03-02
DOI
https://doi.org/10.3389/feduc.2026.1796803
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

The use of Artificial Intelligence in higher vocational colleges in Sichuan, China: a mixed-methods study of adoption, utilization, and policy implications

Francis Gutierrez Balazon, Liu Yang
Frontiers in Education
Artificial Intelligence in Healthcare and Education
article

The use of Artificial Intelligence in higher vocational colleges in Sichuan, China: a mixed-methods study of adoption, utilization, and policy implications

Francis Gutierrez Balazon, Liu Yang
article en

Abstract

This study investigated the status of Artificial Intelligence (AI) adoption and utilization in higher vocational colleges in Sichuan Province, China, and examined the challenges and policy implications of institutional AI integration. Using a mixed-methods, descriptive-comparative design, we combined a survey of 1,085 respondents (administrators, teachers, and students) with interviews and on-site observations to profile prevalent AI tools, frequency and purposes of use, and the extent of AI integration in teaching, language learning, and research, while also comparing stakeholder perceptions and identifying barriers to effective adoption. Results indicate a moderate level of AI adoption in Sichuan’s vocational colleges: approximately 70–75% of faculty and administrators reported adopting AI tools, while student uptake was lower, with nearly one-quarter unsure whether they had used AI. Utilization was strongest for routine tasks and language learning (notably AI-supported translation and tutoring), whereas AI use for research-related activities remained comparatively limited. Domestic platforms such as Baidu ERNIE Bot and Alibaba’s Qwen were the dominant tools, consistent with China’s technology ecosystem and access constraints, whereas foreign models such as ChatGPT were used minimally. Formal AI capacity-building was scarce—fewer than 10% reported receiving structured training—yet individuals with prior training or institutional support showed higher usage. Statistical analyses further found no significant differences in overall AI utilization levels among students, teachers, and administrators, suggesting a broadly cohesive pattern of adoption across roles. Key challenges included limited training opportunities, inadequate infrastructure and access, uncertainty or resistance toward AI use, and concerns about data privacy and academic integrity. Based on these findings, we propose a comprehensive academic policy framework to guide the ethical and effective integration of AI across teaching, learning, research, and administration, emphasizing AI literacy programs, infrastructure enhancement, clear usage guidelines, and sustained implementation support, aligned with China’s educational modernization agenda.

Frontiers in EducationVol. 11
Batangas State University (PH), Hubei Urban Construction Vocational and Technological College (CN)
Quality Education
Openalex Percentile: Top 40%
Artificial Intelligence in Healthcare and Education
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