EXPLORING STUDENTS’ PERSPECTIVE ON ADOPTING GENERATIVE ARTIFICIAL INTELLIGENCE FOR LEARNING: AN EMPIRICAL STUDY

Date

2025-8-27

Author

Zaka, Minal

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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Generative artificial intelligence (GenAI) is reshaping higher education by offering personalized and efficient learning support. However, even with the research on the acceptance of GenAI ongoing, the students' perception of it is limited. This study makes an empirical contribution as it explores key influencers of the acceptance of GenAI applications amongst learners for their academics, and these were identified through a thorough systematic literature review. A quantitative approach was used, for which structured survey responses were gathered from 145 university students with prior experience using GenAI tools. Partial Least Squares Structural Equation Modeling (PLS-SEM) was applied to examine relationships in the proposed model. Findings reveal perceived usefulness, attitude, hedonic motivation, and social influence to have a considerable effect on where learners intend to use GenAI in the future. Whereas task-technology fit, perceived ease of use, and trust were effective with mediation from other variables. These insights help educators and policymakers better understand how to integrate generative AI into education effectively and responsibly.

Subject Keywords

Adoption, Students, Generative AI, Technology Acceptance Model

URI

https://hdl.handle.net/11511/115603

Collections

Graduate School of Informatics, Thesis