AI ADOPTION IN UNIVERSITY SETTINGS: A TECHNOLOGY READINESS AND UTAUT-BASED MODELS OF MEDIATING MECHANISMS

This study is an extension of literature concerning the effectiveness of learning using AI technologies, focusing on the factors affecting behavioral intention of students towards such use in the context of Jordan higher educational institutions. The sample, consisting of 282 university students from Jordanian university was selected through convenience sampling, after which, data was gathered from them. Data was analyzed using Partial Least Squares-Structural Equation Modeling to test the formulated hypotheses. Based on the obtained results, efforts, social influence, perceived risk, and technology readiness had significant effects on behavioral intention of students towards AI technology but this significance was not found for performance expectancy and facilitated conditions. Moreover, the findings indicated that attitudes had a significant mediating effect on perceived risk, social influence, and behavioral intention but efforts, performance expectancy, facilitating conditions, technology readiness had no such mediating effect. The study has several practical and theoretical implications, the top of which is the extension of theoretical models of UTAUT and other technology readiness models and the enhancement of AI practices among the learning process of students.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-12-12
DOI
https://doi.org/10.5281/zenodo.17914937
Primary Topic
Organizational and Employee Performance
Type
article
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article

AI ADOPTION IN UNIVERSITY SETTINGS: A TECHNOLOGY READINESS AND UTAUT-BASED MODELS OF MEDIATING MECHANISMS

Zenodo (CERN European Organization for Nuclear Research)
Organizational and Employee Performance
article

AI ADOPTION IN UNIVERSITY SETTINGS: A TECHNOLOGY READINESS AND UTAUT-BASED MODELS OF MEDIATING MECHANISMS

article en

Abstract

This study is an extension of literature concerning the effectiveness of learning using AI technologies, focusing on the factors affecting behavioral intention of students towards such use in the context of Jordan higher educational institutions. The sample, consisting of 282 university students from Jordanian university was selected through convenience sampling, after which, data was gathered from them. Data was analyzed using Partial Least Squares-Structural Equation Modeling to test the formulated hypotheses. Based on the obtained results, efforts, social influence, perceived risk, and technology readiness had significant effects on behavioral intention of students towards AI technology but this significance was not found for performance expectancy and facilitated conditions. Moreover, the findings indicated that attitudes had a significant mediating effect on perceived risk, social influence, and behavioral intention but efforts, performance expectancy, facilitating conditions, technology readiness had no such mediating effect. The study has several practical and theoretical implications, the top of which is the extension of theoretical models of UTAUT and other technology readiness models and the enhancement of AI practices among the learning process of students.

Zenodo (CERN European Organization for Nuclear Research)
Al-Hussein Bin Talal University (JO), Ahlia University (BH), Zarqa University (JO), University of Business and Technology (SA), Imam Abdulrahman Bin Faisal University (SA)
Quality Education
Openalex Percentile: Top 20%
Organizational and Employee Performance
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