Knowledge Resource
Research Summary: Factors associated with Chinese vocational college students’ intention to use generative artificial intelligence for learning: an extended UTAUT mode
- Original authors
- Attribution requires verification
- Original source
- Frontiers in Education
- Summary & Analysis prepared by
- Aziz Shuaib Ausi
- Resource type
- Research Summary / Knowledge Resource
- Resource published on AZIZ OS
- 2 October 2026
- Reading time
- 1 min
- Publication type
- Knowledge Resource
- Availability
- Open access
About this Summary & Analysis
AZIZ OS provides independently prepared summaries and analytical interpretations of externally published research and knowledge sources. The underlying works remain attributable to their original authors and rights holders. This resource is intended to improve accessibility and understanding and does not replace the original publication.
Research from 'Frontiers in Education (International)' explored the factors influencing Chinese vocational college students' intention to use generative artificial intelligence (GenAI) for learning. The study utilized an extended Unified Theory of behavioral Intention and Use of Technology (UTAUT) model, which incorporated anxiety (ANX), and employed a two-stage analytical approach combining structural equation modeling (SEM) and ordered Probit (OProbit) regression to analyze these factors and their impact on behavioral intention.
Why it matters
Understanding the drivers and barriers, such as anxiety, to technology adoption among vocational students provides critical insights for digital transformation strategies in educational and workforce development. This research highlights the need for targeted interventions to foster effective GenAI integration in learning environments, which can impact future workforce readiness and national competitiveness.
Key insights
- The study focused on Chinese vocational college students' intention to use GenAI for learning.
- An extended Unified Theory of behavioral Intention and Use of Technology (UTAUT) model was developed, integrating 'anxiety' (ANX) as an additional factor.
- A two-stage analytical approach, combining structural equation modeling (SEM) and ordered Probit (OProbit) regression, was used to examine factor relationships and changes in behavioral intention.
Source
Frontiers in Education — https://www.frontiersin.org/articles/10.3389/feduc.2026.1896901
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Verification
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- Verification ID
- ASA-EXE-2026-01035
- Version
- v1.0 · r0
- Issued
- 2 October 2026
- Resource prepared by
- Aziz Shuaib Ausi
- Resource status
- Research Summary / Knowledge Resource
- Underlying work
- Factors associated with Chinese vocational college students’ intention to use generative artificial intelligence for learning: an extended UTAUT mode
- Original authors
- Attribution requires verification
- Original source
- Frontiers in Education
- Provenance status
- Attribution requires verification
- Rights
- Underlying publication rights remain with the respective copyright holder(s). Refer to the original source for authoritative publication and licensing information.
This verification confirms the AZIZ OS resource record and its documented provenance. It does not establish authorship of the underlying external work.