ArticleScientific reports2025
Determinants of student adoption of artificial intelligence applications in higher education.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
- Student perceptions of artificial intelligence in higher education: a structural analysis at an Italian university.Frontiers in psychology · 2026Article
- Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The integration of artificial intelligence (AI) into educational settings has the potential to transform learning experiences; however, its adoption among students remains impacted by various factors. The current study assesses the determinant factors that shape students' willingness to adopt AI applications. A quantitative approach was applied, and data were collected from 211 undergraduate students at the University of Ha'il. The data were analysed via structural equation modelling (SEM) with the AMOS software. The results revealed that readiness, interactivity, and ethical awareness significantly affect students' adoption of AI applications, while trust and performance did not have a significant effect. These findings suggest that fostering AI adoption among students requires a holistic approach that addresses students' technical preparedness and considers trust-building and ethical educational usage. The implications of this study are significant for educational institutions such as universities, as well as for policy makers, educators and developers aiming at integrating the AI applications effectively into students' learning and curriculum. University administrators could benefit by developing the necessary infrastructure and training, while educators could leverage these insights in designing AI-supported learning environments. Students would benefit from these improved academic experiences that are tailored to their needs. This research contributes to the growing discourse on AI in education and offers a holistic conceptual framework to maximize its potential.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.