Trust in and Adoption of Generative AI in University Education: Opportunities, Challenges, and Implications
Abstract
Generative AI has emerged as a transformative tool in the realm of higher education, offering a wealth of opportunities for personalized learning, automated feedback, and enhanced collaboration. However, its successful adoption within university environments is significantly dependent on the trust it earns from its users, particularly students. This study investigates the levels of trust and the adoption of Generative AI among students enrolled in both German and international study programs at Hochschule Bielefeld (HSBI) and its transnational partner, Hainan Bielefeld University of Applied Sciences (BiUH). Utilizing a comprehensive questionnaire, the research explores students' perceptions of the trustworthiness of Generative AI, their usage patterns, and their concerns regarding the ethical and academic implications of its use. Preliminary findings suggest that while students widely recognize the potential of Generative AI to improve learning outcomes and efficiency, the degree of trust in its reliability and fairness varies significantly. Key factors influencing this trust include the transparency of AI systems, the perceived accuracy of outputs, and concerns about bias and misuse. Students in international and cross-cultural programs face additional challenges, such as language barriers and cultural differences, which affect how AI is perceived and utilized. Ethical concerns, particularly regarding plagiarism and academic integrity, are prevalent across all groups, underscoring the need for clear institutional guidelines and policies. The findings highlight the importance of fostering AI literacy and providing support structures to build trust and encourage responsible use. Recommendations include the implementation of transparent AI tools, tailored training programs, and the development of ethical guidelines to ensure that Generative AI enhances education while upholding academic standards. This research provides actionable insights for universities aiming to integrate Generative AI into diverse educational contexts, ensuring that it serves as a beneficial tool that complements traditional educational methods while preparing students for a future where AI plays an increasingly central role.
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Generative AI tools allow students to automatically generate essays, reports, and coding solutions, increasing the risk of plagiarism and contract cheating.
“These tools allow students to automatically gen -erate essays, reports, and coding solutions, increasing the risk of plagiarism and contract cheating [ 55, 56, 79-81].”
From Redefining student assessment in AI-infused learning environments: a systematic review of challenges and strategies for academic integrity (2026) · cites this paper as [81]
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- Authors
- Zhang, Y., & Reusch, P.
- Affiliations
- Hainan Bielefeld University of Applied Sciences (CN)
- Hochschule Bielefeld (DE)
- Venue
- 2025 IEEE Global Engineering Education Conference (EDUCON)
- Publisher
- IEEE
- Published
- 2025-04-22
- Pages
- 1-10
- OpenAlex
- W4410987596
- Cited by
- 13
- References
- 10
- Citations by year
- 2026: 7 · 2025: 6
- FWCI
- 14.87
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- IEEE Global Engineering Education Conference (EDUCON) (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Keywords
- generative AI, student trust in AI, AI adoption in higher education, AI literacy, academic integrity, plagiarism concerns, AI ethics, international students, AI transparency, algorithmic bias, language barriers, responsible AI use, artificial intelligence in education
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