Influence of higher education students’ perceived behaviour on their artificial intelligence acceptance: an empirical investigation using technology acceptance model

Purpose This study aimed to investigate higher education students’ perceived behaviour towards artificial intelligence (AI) acceptance in their learning. Design/methodology/approach Theory of technology acceptance model (TAM) and its critical constructs were used to develop research model and hypotheses. The research model was validated using structural equation modelling (SEM) based on 405 useable survey responses. Findings The findings report that the critical constructs of TAM theory are helpful to explain higher education students’ perceived behaviour towards their AI acceptance in learning. The findings also confirm the reliability and strength of TAM theory to assess higher education students’ behavioural intention to accept AI. Practical implications The findings will help authorities of higher education to understand the students’ behavioural intention to accept AI. The study will assist authorities, policymakers, designers, developers and decision-makers of higher education to facilitate the effective integration of AI in higher education. Originality/value The study contributes to enhance new knowledge in literature regarding AI acceptance in higher education. It fills the knowledge gap by confirming the influence of higher education students’ perceived behaviour on their AI acceptance. Additionally, it uses SEM approach, which is very new in quantitative analysis, to test and establish the research model.

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Publication Details

Journal
Journal of Applied Research in Higher Education
Published
2025-02-21
DOI
https://doi.org/10.1108/jarhe-11-2023-0535
Citations
7
Primary Topic
Technology Adoption and User Behaviour
Type
article
Field-Weighted Citation Impact
29.18
Controls
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article

Influence of higher education students’ perceived behaviour on their artificial intelligence acceptance: an empirical investigation using technology acceptance model

Bablu Karan, Chitra Chakma
7 citations
Journal of Applied Research in Higher Education
Technology Adoption and User Behaviour
29.18
article

Influence of higher education students’ perceived behaviour on their artificial intelligence acceptance: an empirical investigation using technology acceptance model

Bablu Karan, Chitra Chakma
article en
7 citations

Abstract

Purpose This study aimed to investigate higher education students’ perceived behaviour towards artificial intelligence (AI) acceptance in their learning. Design/methodology/approach Theory of technology acceptance model (TAM) and its critical constructs were used to develop research model and hypotheses. The research model was validated using structural equation modelling (SEM) based on 405 useable survey responses. Findings The findings report that the critical constructs of TAM theory are helpful to explain higher education students’ perceived behaviour towards their AI acceptance in learning. The findings also confirm the reliability and strength of TAM theory to assess higher education students’ behavioural intention to accept AI. Practical implications The findings will help authorities of higher education to understand the students’ behavioural intention to accept AI. The study will assist authorities, policymakers, designers, developers and decision-makers of higher education to facilitate the effective integration of AI in higher education. Originality/value The study contributes to enhance new knowledge in literature regarding AI acceptance in higher education. It fills the knowledge gap by confirming the influence of higher education students’ perceived behaviour on their AI acceptance. Additionally, it uses SEM approach, which is very new in quantitative analysis, to test and establish the research model.

Journal of Applied Research in Higher EducationVol. 18(3)
Central University of Karnataka (IN), Institute for Women's Policy Research (US)
Openalex Percentile: Top 1%
Technology Adoption and User Behaviour
29.18
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Influence of higher education students’ perceived behaviour on their artificial intelligence acceptance: an empirical investigation using technology acceptance model — Bablu Karan, Chitra Chakma · Journal of Applied Research in Higher Education (2025) | TGRS Research Map | TGRS