Determinants of Generative Artificial Intelligence (GenAI) adoption among university students and its impact on academic performance
The mediating role of trust in technology
Bibliographic Data
| ID | 21632501 |
|---|---|
| Authors | Saqar Moisan F Alotaibi (0009-0002-7787-2715, Taibah University, corresponding author) |
| Year | 2025 |
| Volume | 33 |
| Issue | 6 |
| Pages | 4159-4188 |
| Publication date | 2025-07-03 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Interactive Learning Environments (JOURNAL) |
| Journal identifiers | ISSN: 1049-4820 • E-ISSN: 1744-5191 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/10494820.2025.2492785 |
| OpenAlex | W4409648303 |
| Language | EN |
| Citations received | 7 |
| References cited | 76 |
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
Academic achievement · Educational technology · Generative grammar · Knowledge management · Mathematics education · AI in Service Interactions · Computer Science · Organizational and Employee Performance · Psychology · Technology Adoption and User Behaviour · Artificial Intelligence
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| Unique citing works | 7 |
|---|---|
| Citations per year | 7 |
| Citation span | 2025 - 2026 (2) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 7 |