Critical reflection is an essential skill within initial teacher education that supports authentic and meaningful connections for pre-service teachers (Polley, 2022). In a Bachelor of Education (Primary, Pasifika) programme, pre‑service teachers (PSTs) experienced challenges applying reflective models purposefully to inform professional judgement and pedagogical decision‑making. These challenges are compounded by increased access to generative artificial intelligence (GenAI), where insufficient AI literacy can lead to dependency and diminished critical judgement (Hsu, 2026).

This case study sits within a wider cross-sector AI initiative, and focuses on Jarvis, an AI reflective agent developed to scaffold pre-service teachers’ to articulate their own reflections through prompts and iterative questioning aligned with established educational frameworks. This work examines how engagement with Jarvis shapes pre‑service teachers’ critical thinking, quality of reflection, and professional learning conversations.

Focus groups with PSTs examined experiences of using Jarvis, with thematic analysis used to identify patterns in reflective practice and AI engagement. Findings indicated deeper reflective writing and stronger learning conversations where Jarvis supported student‑generated reflection rather than replacing it. This ongoing inquiry contributes to AI‑supported learning design by promoting AI literacy and critically reflective, future‑ready teachers.

Authors:
Kate Lewis, Manukau Institute of Technology, New Zealand
Kriya Patel, Manukau Institute of Technology, New Zealand

About the Presenter(s)
Kate Lewis, Senior Lecturer Primary Pasifika at Manuaku Institute of Technology. Self-determined learning; collaborative learning; digital technologies; innovative learning environments; initial teacher education.

See this presentation on the full schedule – On Demand Schedule

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