Redefining integrity in the context of generative artificial intelligence (GenAI) in higher education: What are students saying?

Presentation


Slade, Christine, Matthews, Kelly, Chung, Jennifer, Liang, Yifei and Oberg, Glenys. 2025. "Redefining integrity in the context of generative artificial intelligence (GenAI) in higher education: What are students saying?" 47th Higher Education Research and Development Society of Australasia Annual Conference(HERDSA 2025). Perth, Australia 07 - 10 Jul 2025
Paper/Presentation Title

Redefining integrity in the context of generative artificial intelligence (GenAI) in higher education: What are students saying?

Presentation TypePresentation
AuthorsSlade, Christine, Matthews, Kelly, Chung, Jennifer, Liang, Yifei and Oberg, Glenys
Year2025
Web Address (URL) of Conference Proceedingshttps://conference.herdsa.org.au/2025/program/
Conference/Event47th Higher Education Research and Development Society of Australasia Annual Conference(HERDSA 2025)
Event Details
47th Higher Education Research and Development Society of Australasia Annual Conference(HERDSA 2025)
Parent
Higher Education Research and Development Society of Australasia Annual Conference
Delivery
In person
Event Date
07 to end of 10 Jul 2025
Event Location
Perth, Australia
Event Venue
Perth Convention and Exhibiton Center
Event Web Address (URL)
Abstract

Focus of the Showcase: This presentation showcases the outcomes of a recent large-scale multi-university research project about students’ relationship with GenAI. It highlights how GenAI is reshaping integrity discussions and emphasises the necessity of including student views.
Background/context: A growing number of surveys have explored students’ views on AI’s use and usefulness, academic integrity, and trust (e.g., Chan & Hu, 2023; Kelly, Sullivan & Strampel, 2023; Polyportis, 2024; Ravšelj et al., 2025). Student perspectives are crucial in these discussions (Liu et al., 2024).
Description: The project, a collaboration between four major Australian universities, explored how the complexity and diversity of students’ values, beliefs, backgrounds, and learning context shapes their use of GenAI. This presentation focuses on responses related to personal, academic and professional integrity. Method: We created and utlised a cross-sectional online survey with descriptive analysis as part of the larger mixed method research project.
Evidence: The survey of 8021 students (August to October 2024) revealed that most used AI for brainstorming, creation, Q&A and analysis. Only 27% trusted its output, 71% believed it increased cheating, and 91% worried about breaking university rules. Forty percent admitted to using AI in assessments when not allowed. Just 32% felt their university provided enough guidance on using AI, and only 23% felt prepared to use it professionally (Chung et al., 2024).
Contribution: This research broadens the integrity discussions, highlighting the challenges institutions face in maintaining integrity with advanced technologies. The survey shows that while students use GenAI for academic tasks, many are concerned about cheating and feel unprepared to use it professionally. It also emphasises the need for institutions to adapt their policies and practices. By doing so, they can better support students in navigating the ethical use of these technologies. Engagement: There will be time for questions from the audience and discussion.

Contains Sensitive ContentDoes not contain sensitive content
ANZSRC Field of Research 2020390303. Higher education
460299. Artificial intelligence not elsewhere classified
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Byline AffiliationsUniversity of Queensland
Deakin University
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