Artificial Intelligence in Higher Education: Trick or Treat? 

If you have been at any higher education events lately, AI has been the top item on conference agendas. Reactions throughout the academy have ranged from, “the sky is falling“ to “AI is the solution to everything.” So, as a leader at your institution or organization, how should you be thinking about the potential of AI as one of the items in your “bag of tricks” to achieve better institutional outcomes and efficiencies at your organization?

It’s helpful to consider this question in context: our postsecondary education experience is not delivering on its promise. Completion continues to be a persistent challenge with only 62% of those who start completing their degree in 6 years, and only 44%  of Black students and 50% of Latinx and Native Students completing on this timeline. In this moment, we have an opportunity and imperative to consider how AI can be part of future models as we improve as a field.

AI offers a new set of “tricks” or tools to apply to our teaching and learning infrastructure and approach

So, what tricks do now widely-available Generative AI tools offer us as we seek to improve the ways that institutions and the technology vendors who serve them better support students? Fundamentally, as illustrated in the chart below, AI gives us the ability to generate words and images and powerful tools for predicting the most likely outcome. These tools enable innovation in teaching and learning, greater efficiency across academic and administrative tasks, and the ability to more quickly predict and to take action to improve student and institutional outcomes.

But today, instructors are not using those ingredients at the rates they think students will need to use them

Building on the Time for Class (T4C) report released in Spring 2023, Tyton (in partnership with funding partner Turnitin), conducted a pulse survey this fall, reaching over 1,000 higher education faculty and 1,600 current postsecondary students. We see that adoption of generative AI tools has been steadily increasing since the spring, but faculty and students are not adopting equally. Notably, we now see half – 49% – of students tell us they are using Generative AI tools regularly. Only 22% of faculty note they are using them regularly, pointing to an enormous experience gap between these two user groups.

Regardless of their own use and familiarity, most faculty believe that students must learn how to work with AI tools for professional success and see learning about AI as an institutional responsibility.

Overall, half of faculty believe students will need to know how to use AI for professional success, with GenAI users even more likely to believe this than to non-users. Similarly, half of faculty note that they see it as the institution’s responsibility to teach students about GenAI. Yet only 1/3 of faculty report that they are teaching students how to use generative AI. This points to a significant need for AI literacy and support across institutions, and support for faculty, staff, and learners to understand the uses and implications of these tools inside and outside of the classroom.

Students and faculty do not see eye to eye on the use of AI in the classroom

Across the field, we have seen institutions and faculty scrambling to provide guidance and policies for responsible and acceptable use of AI as part of the training of students, staff, and faculty. A look at the juxtaposition of how students report using generative AI tools to support their understanding and completion of coursework points to this disconnect.  Whereas students and faculty agree on the use of AI tools for brainstorming, outlining and editing, there is a disconnect between students who are using generative AI to draft portions of assignments and faculty who view this as unacceptable use.