Abstract:

Generative Artificial Intelligence is rapidly reshaping education systems worldwide, raising critical questions for Initial Teacher Education (ITE). Within our Primary Postgraduate Certificate in Education (PGCE) programme in England, early debates about whether to ‘permit’ the use of AI quickly became redundant as our pre-service teachers were already using generative AI extensively in both academic and personal contexts. Recognising this reality, we shifted from gatekeeping towards structured and research-informed integration, positioning AI as a stimulus for professional learning rather than a threat to academic integrity.

We report first-year findings from a longitudinal, multi-stakeholder case study. This is amongst the first to examine generative AI integration across university–school partnerships rather than within university coursework alone. It explores how generative AI influenced lesson planning, school placement experiences and emerging teacher identity. Participants included pre-service teachers, university tutors, school mentors and school leaders within a large urban partnership.

The research adopted a collaborative, close-to-practice inquiry design that fostered two-way knowledge exchange between university and school settings. Data were collected through surveys, semi-structured interviews and focus groups, enabling triangulation across stakeholder perspectives. Iterative thematic analysis identified patterns of AI use, ethical reasoning, professional judgement, innovation and emerging tensions. This methodological approach strengthened research quality while ensuring validity in classroom contexts.

Findings challenged initial assumptions that pre-service teachers would rely on AI to simply produce ready-made lessons without scrutiny. Instead, findings showed that most pre-service teachers used AI strategically to support workload-intensive tasks such as adapting tasks, scaffolds, modelled texts and resource creation. Most participants demonstrated critical evaluation of outputs and further adapted them for pupil age, needs, curriculum requirements and school contexts. School partners identified both opportunities, including increased efficiency, creativity and adaptation, and risks related to output accuracy, AI bias and potential over-reliance. These findings highlight the importance of explicit AI literacy and clear ethical and professional guidance within ITE.

The innovation of this work lies in reframing generative AI from a compliance issue to a site of professional formation within ITE. Rather than being an external disruption, the programme now embeds critical AI literacy, ethical reflection and collaborative evaluation into pre-service learning. Impact is evident in strengthened professional agency, enhanced dialogue across partnerships and the initial report of recommendations for AI use for all stakeholders.

Although situated in England, the research focus, including AI adoption, professional identity and ethical integration, is shared internationally. The paper offers transferable principles for teacher education systems and policy development, including embedding critical AI literacy within curricula, modelling reflective AI use and sustaining inquiry-based dialogue around emerging technologies. Research-informed strategies and adaptable frameworks to support responsible generative AI integration within diverse educational contexts will be shared.

Keywords:

Pre-service teachers, initial teacher education, Use of AI, research around technology, AI in education and teacher identity.