Navigating generative artificial intelligence educational expertise: a duoethnographic exploration using an AI chatbot interviewer

This duoethnographic study explored the lived experiences of the authors, two university-based teacher educators in Hong Kong, as they navigate their positioning as generative artificial intelligence (GenAI) educational experts. Employing dialogic reflections elicited by a customised GenAI chatbot interviewer, the study investigated the complexities caused by the developments of GenAI in teacher education amidst professional uncertainty, institutional tensions and evolving pedagogical practices. Data collected through reflective dialogues, annotated transcripts and related artefacts were analysed using reflexive thematic analysis, identifying six key themes: (1) catalyst moments and professional awakenings, (2) negotiating expertise amid uncertainty, (3) dialogic approaches and collegiality, (4) redefining assessment and pedagogical practice, (5) tensions with institutional policy and (6) vulnerability, lifelong learning and role modelling. The results highlight the impact of GenAI on teacher education, the challenges of managing ambiguity while being positioned as experts and the critical role of collegial networks and dialogic practices in nurturing shared understanding. The findings contribute to discourses on GenAI’s implications for teacher education, offering insights into the professional learning journeys of teacher educators and advocating for a collective, reflective approach to navigating technological disruptions. This will help teacher educators embrace uncertainty during times of change.

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Publication Details

Journal
Teachers and Teaching
Published
2026-07-17
DOI
https://doi.org/10.1080/13540602.2026.2703816
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
0.00
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article

Navigating generative artificial intelligence educational expertise: a duoethnographic exploration using an AI chatbot interviewer

Benjamin Luke Moorhouse, Lucas Kohnke
Teachers and Teaching
AI in Service Interactions
article

Navigating generative artificial intelligence educational expertise: a duoethnographic exploration using an AI chatbot interviewer

Benjamin Luke Moorhouse, Lucas Kohnke
article en

Abstract

This duoethnographic study explored the lived experiences of the authors, two university-based teacher educators in Hong Kong, as they navigate their positioning as generative artificial intelligence (GenAI) educational experts. Employing dialogic reflections elicited by a customised GenAI chatbot interviewer, the study investigated the complexities caused by the developments of GenAI in teacher education amidst professional uncertainty, institutional tensions and evolving pedagogical practices. Data collected through reflective dialogues, annotated transcripts and related artefacts were analysed using reflexive thematic analysis, identifying six key themes: (1) catalyst moments and professional awakenings, (2) negotiating expertise amid uncertainty, (3) dialogic approaches and collegiality, (4) redefining assessment and pedagogical practice, (5) tensions with institutional policy and (6) vulnerability, lifelong learning and role modelling. The results highlight the impact of GenAI on teacher education, the challenges of managing ambiguity while being positioned as experts and the critical role of collegial networks and dialogic practices in nurturing shared understanding. The findings contribute to discourses on GenAI’s implications for teacher education, offering insights into the professional learning journeys of teacher educators and advocating for a collective, reflective approach to navigating technological disruptions. This will help teacher educators embrace uncertainty during times of change.

Teachers and Teaching
City University of Hong Kong (HK), Education University of Hong Kong (HK)
Reduced inequalities
Openalex Percentile: Top 6%
AI in Service Interactions
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Navigating generative artificial intelligence educational expertise: a duoethnographic exploration using an AI chatbot interviewer — Benjamin Luke Moorhouse, Lucas Kohnke · Teachers and Teaching (2026) | TGRS Research Map | TGRS