%0 Journal Article
%T Generative AI-Enabled Environmental Education and Green Entrepreneurial Intention
%A Thuyen Thanh Thị Tran
%A Hai Hong Phan
%A Thuc Ngoc Nguyen
%J World Journal of Environmental Biosciences
%@ 2277-8047
%D 2026
%V 15
%N 2
%R 10.51847/ckXj3lzNz5
%P 91-101
%X Environmental education increasingly requires digital learning approaches that help students understand environmental problems and develop sustainability-oriented responses. This study examines how generative AI adoption (GAA) contributes to this educational process by supporting green skills, green opportunity recognition, and green entrepreneurial intention (GEI) among university students in Vietnam. Drawing on human capital theory, opportunity recognition theory, and person–environment fit theory, the study proposes a model in which green skills (GS) and green opportunity recognition (GOR) serve as mediators, while sustainable entrepreneurship education (SEE) acts as a moderator. Data were collected from 599 university students with experience using generative AI tools and analyzed using partial least squares structural equation modeling (PLS-SEM). The findings show that GAA is positively associated with GS and GOR. GS is positively associated with GOR and GEI, while GOR is positively associated with GEI. The mediation results confirm that GS and GOR explain how GAA is linked to GEI. In addition, SEE strengthens the GS–GOR and GOR–GEI relationships. These findings contribute to environmental education and sustainability research by identifying a capability-to-action pathway through which AI-supported learning, green competencies, and environmental opportunity recognition jointly shape GEI. Practically, universities should embed GenAI within sustainability-oriented education to strengthen environmental problem-solving, responsible resource use, and the development of feasible green initiatives. 
%U https://environmentaljournals.org/article/generative-ai-enabled-environmental-education-and-green-entrepreneurial-intention-hmfgyfvmfafjj4p