Through tensions to identity-based motivations: exploring teacher professional identity in artificial intelligence-enhanced teacher training
Open accessAbstract
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.
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As GenAI rapidly reshapes teaching tasks, instructional decision-making, and professional boundaries, teachers' identities undergo adaptation and reconstruction.
“As GenAI rapidly reshapes teaching tasks, instructional decision-making, and professional boundaries, teachers’ identities undergo adaptation and reconstruction (Lan, 2024).”
From AI teaching innovation behavior among college teachers: a structural equation modeling analysis based on the AI-TPACK framework, teaching self-efficacy, professional identity, and AI literacy (2026) · cites this paper as Lan, 2024
Section 3.2.3 (p. 10) describes teachers’ professional identities evolving as they integrate AI, including ChatGPT. The paper supports identity adaptation, but its discussion is chiefly about AI-enhanced teacher training; it does not establish that GenAI is rapidly reshaping instructional decision-making or professional boundaries as the sentence claims. (LLM, conf=0.84)
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“As GenAI rapidly reshapes teaching tasks, instructional decision-making, and professional boundaries, teachers’ identities undergo adaptation and reconstruction (Lan, 2024).”
- Authors
- Lan, Y.
- ORCID
- Lan, Yanzhen
- Venue
- Teaching and Teacher Education
- Publisher
- Elsevier BV
- Published
- 2024-12
- Volume
- 151
- Pages
- 104736
- ISSN
- 0742-051X (ISSN-L)
- OpenAlex
- W4401732938
- Cited by
- 124
- References
- 63
- Citations by year
- 2026: 83 · 2025: 36 · 2024: 5
- FWCI
- 46.51
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Teaching and Teacher Education (publishedVersion, cc-by-nc)
- Apollo (University of Cambridge) (submittedVersion, cc-by-nc)
- Apollo (University of Cambridge) (submittedVersion, cc-by)
- Apollo (cc-by)
- Topics
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Social Sciences › Education › Teacher Education and Leadership Studies
- Physical Sciences › Computer Science › Information Systems › Digital Education and Society
- Keywords
- teacher identity, artificial intelligence in teacher education, identity tensions, teacher motivation, Chinese university teachers
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