Sep 2026· Eurasia Journal of Mathematics, Science and Technology Education· Vol 22, pp. em2912· 1 citation· 55 references
TL;DR
Usefulness was strongest for men, trust for women, and explained variance was greater in years 3-4 than years 1-2, and risk weakened the usefulness-, trust-, and awareness-intention relationships.
Abstract
Artificial intelligence (AI) adoption among preservice mathematics teachers remains uneven. This study aimed to identify adoption predictors, test trust mediation, examine risk moderation, compare demographic subgroups, and evaluate a sequential awareness-ease-usefulness-trust-intention model. Survey data from 130 South African preservice mathematics teachers were analyzed using regression, mediation, moderation, subgroup analysis, and structural equation modelling. Trust (β = .38), usefulness (β = .26), and awareness (β = .19) positively predicted intention; risk predicted it negatively (β = -.16), while ease had no direct effect. Trust partially mediated all cognitive pathways (44.2%-58.5%), and risk weakened the usefulness-, trust-, and awareness-intention relationships. Usefulness was strongest for men, trust for women, and explained variance was greater in years 3-4 than years 1-2 (64.8% vs. 52.4%). The sequential model had acceptable fit and a significant full indirect effect (0.031, 95% confidence interval [0.009, 0.061]).
The results suggest that students’ willingness to engage with GenAI is shaped not only by favorable perceptions but also by confidence in the system’s reliability, integrity, and ethical use, suggesting the need to foster trust and cultivate positive attitudes through transparent policies, ethical guidelines, and targe...
Enrico C. Mendoza, Jose Roberto Del Rosario· International Review of Mana...· 0 citations
Generative AI has become a powerful tool in higher education, helping students and researchers work more efficiently. However, this rapid adoption raises important questions about how users view AI ethics and trust. This study investigates what actually drives AI adoption among students, researchers, and lecturers in I...
M. Naufal, A. Mailangkay· International Conferences on...· 0 citations
The results show that AI self-efficacy, perceived usefulness, and relative advantage have significant positive effects on lecturers’ intention to use AI, and institutional support plays a pivotal moderating role, strengthening the relationship between intention to use AI and actual adoption behaviour.
A.M. Al-Darabseh, S. F. Padlee, Siti Nur et al.· Journal of Intelligent Decis...· 0 citations
A moderated serial mediation model in which AI literacy is associated with continued ChatGPT use through an indirect pathway involving trust in AI and academic self-efficacy, with AI anxiety moderating the literacy-to-trust association was tested.
This study aimed to investigate the acceptance of biology students toward AIEd tools and the moderating effects of AI awareness and AI literacy on their behavioral intention via a descriptive-correlational design. A total of 162 biology students participated, with different fields of specialization. Moderation and simp...
Jerone Caribio, Eden David, L. Natividad· Multidisciplinary Reviews· 0 citations
The findings suggest that developmental benefits in students' collaboration with GenAI are better understood as theory consistent structural relationships shaped by contextual guidance, calibrated trust, and active regulation rather than as automatic consequences of frequent AI use.
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