Determinants of Generative Artificial Intelligence (GenAI) Adoption among University Students and Its Impact on Academic Performance: The Mediating Role of Trust in Technology

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Bibliographic Details
Title: Determinants of Generative Artificial Intelligence (GenAI) Adoption among University Students and Its Impact on Academic Performance: The Mediating Role of Trust in Technology
Language: English
Authors: Saqar Moisan F. Alotaibi (ORCID 0009-0002-7787-2715)
Source: Interactive Learning Environments. 2025 33(6):4159-4188.
Availability: Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
Peer Reviewed: Y
Page Count: 30
Publication Date: 2025
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Artificial Intelligence, Technology Uses in Education, College Students, Academic Achievement, Technology Integration, Trust (Psychology), Knowledge Level, Digital Literacy, Student Attitudes, Foreign Countries
Geographic Terms: Saudi Arabia
DOI: 10.1080/10494820.2025.2492785
ISSN: 1049-4820
1744-5191
Abstract: Generative Artificial Intelligence has garnered significant attention for its potential to enhance personalised learning, data analysis, and academic research in higher education. However, adoption among university students remains limited due to barriers such as limited technical knowledge, negative perceptions, and a lack of trust in technology. This study investigates the key determinants of GenAI adoption and its impact on academic performance (AP), focusing on the mediating role of trust in technology (TT). Using Smart PLS-SEM, data were collected via questionnaires from 364 undergraduate and postgraduate students in Information Science, Library Science, Learning Resources, and Knowledge Management across five public universities in Saudi Arabia. The findings show that technical knowledge (TK) positively affects both TT and AP, confirming that students with higher technical knowledge tend to trust GenAI more and perform better academically. Personal experience (PE) and personal perceptions (PP) also have positive effects on TT and AP, with PP having the strongest influence on TT. TT plays a significant mediating role between TK, PE, PP, and AP. Direct effects on AP remain strong, highlighting the importance of both technical proficiency and personal experience. This study highlights the need for further research into additional factors that could enhance GenAI integration in higher education and maximize its broader impact.
Abstractor: As Provided
Entry Date: 2026
Accession Number: EJ1501716
Database: ERIC
Description
Abstract:Generative Artificial Intelligence has garnered significant attention for its potential to enhance personalised learning, data analysis, and academic research in higher education. However, adoption among university students remains limited due to barriers such as limited technical knowledge, negative perceptions, and a lack of trust in technology. This study investigates the key determinants of GenAI adoption and its impact on academic performance (AP), focusing on the mediating role of trust in technology (TT). Using Smart PLS-SEM, data were collected via questionnaires from 364 undergraduate and postgraduate students in Information Science, Library Science, Learning Resources, and Knowledge Management across five public universities in Saudi Arabia. The findings show that technical knowledge (TK) positively affects both TT and AP, confirming that students with higher technical knowledge tend to trust GenAI more and perform better academically. Personal experience (PE) and personal perceptions (PP) also have positive effects on TT and AP, with PP having the strongest influence on TT. TT plays a significant mediating role between TK, PE, PP, and AP. Direct effects on AP remain strong, highlighting the importance of both technical proficiency and personal experience. This study highlights the need for further research into additional factors that could enhance GenAI integration in higher education and maximize its broader impact.
ISSN:1049-4820
1744-5191
DOI:10.1080/10494820.2025.2492785