Through tensions to identity-based motivations: Exploring teacher professional identity in Artificial Intelligence-enhanced teacher training
This mixed-methods case study explores teacher professional identity (TPI) tensions and motivations for Artificial Intelligence (AI) integration in teaching within a Chinese university-level AI-enhanced teacher training programme. Surveys were completed by 216 attendees, followed by in-depth qualitative analysis of 15 selected teachers. The study reveals TPI groupness-individuality, humanity-technology, and continuity-openness tensions. Three conceptual models are introduced: Human Intelligence and AI as Navigator, Collaborator, and Inventor. It underscores the critical role of tailored AI-enhanced teacher training in harmonising educators’ diverse identities and motivations with technological advancements, signalling a strategic approach for effective AI integration in global teacher education. • Explores teacher professional identity (TPI) tensions in Artificial Intelligence (AI)-enhanced training. • Examines TPI tension-based motivations to engage with AI. • Introduces models: Human Intelligence and AI as Navigator, Collaborator, Innovator. • Promotes worldwide navigation of TPI with AI. • Provides practical and global implications tailored to three models.
Authors
- Yang-Zheng Lan (ORCID: https://orcid.org/0000-0002-5813-3792)
Institutions
- Qingdao University of Science and Technology (CN)
- University of Cambridge (GB)
Publication Details
- Journal
- Teaching and Teacher Education
- Published
- 2024-08-22
- DOI
- https://doi.org/10.1016/j.tate.2024.104736
- Citations
- 51
- Primary Topic
- Online Learning and Analytics
- Type
- article
- Field-Weighted Citation Impact
- 21.00