Research & educational impact

My research at Deakin University began with a question I cared about as a school leader. What happens when graduate teachers are trying to find their feet in the classroom while also wondering whether they will have a job the following year? For my Master of Education in Leadership and Learning, I explored the experiences of graduate teachers on fixed-term contracts in Victorian secondary schools and what those experiences could tell us about teacher attrition and retention. I received a High Distinction for the thesis.

I came away thinking more carefully about what schools ask of people at the beginning of their careers. A graduate teacher is learning how to teach, how to work within a school and how to ask for help when things get difficult. The research sharpened my thinking about what school leaders can influence, including how we welcome new colleagues, give them access to experienced mentors and make time for feedback. As Principal of THINK Global School, I draw on that thinking in professional review conversations. When a colleague described the difficulty of finding their way through our curriculum and advisory systems, we agreed to develop the map they had started for themselves into an onboarding resource for future staff. It gave us a practical way to act on something we had learned by listening.

I bring the same curiosity to emerging research on AI. The MIT Media Lab’s preliminary study of AI-assisted essay writing caught my attention because participants who used a language model reported less ownership of their essays and had more difficulty quoting their own work. A separate high school mathematics study by Bastani and colleagues found that access to generative AI improved performance during practice, but students using the unrestricted version performed worse when they later worked independently. A version designed to give teacher-developed hints largely mitigated that effect. The studies examined different tasks, and they prompt a question I find useful in both contexts. What can a student explain or do independently after using the tool?

That question connects with work I already do at THINK Global School. In the Journey Portfolio, I ask students to choose an experience, explain how it challenged their thinking and tell me what they might do differently as a result. If we were to trial AI-supported feedback on that kind of work, I would want to see the student’s first attempt, look at what they changed and hear them explain why. Their explanation would help me judge what they had learned from the feedback.

At PLC, I would be interested in exploring questions like this with girls and their teachers. An inquiry might begin by asking girls which feedback they acted on and what made it useful, then looking together at how their work developed. I would want teachers to have time to compare what they observed and for girls to hear what we learned from their contributions. That gives the Centre a way to connect research with decisions teachers make every day, and to see whether those decisions are improving students’ experience of learning.