(1 May 2025) Two and half years after ChatGPT’s commercial release, the higher education community is still coming to terms with how generative AI technology is impacting teaching, learning, and research. Universities, publishers, and other stakeholders in and around higher education have been obliged to react quickly, creating task forces, new guidelines and policies, and other support resources to help the community navigate this period of change. However, there still remains much to learn when it comes to the ways in which generative AI is transforming postsecondary teaching, learning, and research. Colleges and universities are facing challenges in coordinating cross-institutional AI literacy initiatives, providing access to generative AI tools, and managing instructors’ student academic integrity concerns. As we move from a period of experimentation to integration, scholarly inquiry into generative AI’s impacts on education and research is essential to establish best practices moving forward.
In response to generative AI’s introduction into the higher education sphere, we launched the “Making AI Generative for Higher Education” cohort project in fall 2023 with 19 colleges and universities across the US and Canada. This project has allowed us to collect and share information on how generative AI is perceived and used across these campuses, as well as discuss strategies for supporting instructors, researchers, and students. As a core component of the project, each institution conducted interviews with instructors and researchers to learn more about their adoption and support needs in regard to generative AI.
Today, we are announcing the publication of a new report detailing the findings of these interviews. The interviews offer insight on how instructors and researchers are using generative artificial intelligence in their work, as well as the challenges they currently face related to the technology. The study also reveals which support resources instructors and researchers are relying on and which resources they feel are still lacking. We are grateful to the participating institutions (listed below) and their teams for making this research possible.
Key Findings
- Instructors and researchers have widely varied degrees of familiarity with AI, but even those at the lower end of the scale recognize the importance of improving their AI literacy levels.
- Instructors are taking it upon themselves to integrate basic AI skills into student activities but are still determining how generative AI can help them meet course learning objectives and how/if to reimagine those learning objectives.
- Instructors desire further top-down guidance related to student academic integrity and the formal integration of AI literacy into student general education.
- Most researchers have already experimented with AI, but far fewer have settled on productive ways of integrating the tools for the longer term.
- Researchers seek further clarity around ethical standards and best practices to ensure research quality and integrity can be maintained.
- Instructors and researchers see a gap in discipline-specific support resources at their institutions and are concerned about having secure, affordable access to generative AI tools. They also demonstrate a need for more education on the generative AI product landscape for higher education.
Find out more here.
