Research

We study how people learn to use AI and what that means for education and research. Our work ranges from prompting techniques you can try to proposals for how universities should teach and assess.

AI-Locus of Control

When a person works with AI, who directs the outcome, the person or the tool? We study where people place that control, and how teaching moves it back to the person. We have watched people shift from accepting whatever the tool produced to steering it, and we are now following that change over time.

AI Prompting Techniques

How does a person get from a blank chat box to work they can stand behind? We build ways of prompting that begin with whether AI suits the task and end with whether the result reflects the person’s own knowledge. We have seen that the value lies in the judgements a person makes, even when the AI is wrong, and we now teach that to educators.

The Future of Education

If AI can produce an assignment, what should that assignment assess? We argue for teaching that rewards the process a student works through, with room to try something and learn when it fails. We have seen a subject succeed by dwelling on process, and we are turning that into assessment practice others can use.

AI in Research: Methods and Policy

How can researchers use AI in work that others can check? We set out what to record about the AI’s part in the work, so the researcher stays accountable for every decision. Our guidance is now part of Macquarie University’s ethics processes, and we are developing methods that keep the evidence beside every result.

Teaching with and about AI

How do people teach with a tool whose limits keep changing? We design teaching that gives people room to experiment, then asks them to explain how they judged what came back. We have found that a failed attempt still teaches when assessment asks what the person learned, and we build that into whole subjects.