Next-Gen Hallam Maths Teachers: Leading the way in the GenAI Era

Abstract

As generative artificial intelligence (GenAI) tools become increasingly visible in educational settings, it is important to understand how trainee teachers experience and interpret GenAI use in real classrooms, alongside their own developing practice. Our presentation reports on findings from our SoTL project on perspectives and usage of GenAI in maths teaching.

The study adopts a mixed-methods design, drawing on survey data and qualitative insights from semi-structured interviews and focus groups with pre-service primary and secondary teachers. The survey captures patterns of GenAI use and general attitudes, while interviews and focus groups explore trainees’ experiences on placement, including their own use of GenAI and how mentors, host teachers and colleagues are using Gen AI in their practice.

Findings indicate that trainees encounter a range of practices in schools, from enthusiastic adoption of GenAI for lesson planning and resource creation to more cautious or limited use. Many trainees report using GenAI to support planning, generate examples, and adapt materials, often influenced by school context and mentor guidance. While GenAI is seen as enhancing efficiency and confidence, trainees also express concerns about accuracy, ethical use, and the risk of over-reliance.

We discuss the implications for teacher education, emphasising the need to prepare trainees to critically evaluate and responsibly integrate GenAI, particularly as they navigate differing practices and expectations across placement settings.