Trust in and Adoption of Generative AI in University Education: Opportunities, Challenges, and Implications

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.

Authors

Institutions

Publication Details

Published
2025-04-22
DOI
https://doi.org/10.1109/educon62633.2025.11016490
Citations
6
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
3.93
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Trust in and Adoption of Generative AI in University Education: Opportunities, Challenges, and Implications

Pascal Reusch, Yue Zhang
6 citations
Artificial Intelligence in Healthcare and Education
3.93
article

Trust in and Adoption of Generative AI in University Education: Opportunities, Challenges, and Implications

Pascal Reusch, Yue Zhang
article en
6 citations

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.

Hochschule Bielefeld (DE)
Openalex Percentile: Top 6%
Artificial Intelligence in Healthcare and Education
3.93
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.