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December 8, 2025Australian Journal of Applied LinguisticsOpen Access

Empowering pre-service teachers with generative artificial intelligence and microlearning: pathways to self-directed growth

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Authors

LKLucas KohnkeEducation University of Hong Kong

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Overview

Exploratory research identifies pathways to self-directed growth in pre-service teachers, highlighting microlearning and self-regulated learning as key strategies.

Key Points

  • Professional development improves through microlearning strategies and self-regulated learning.
  • Key themes include navigating generative artificial intelligence and enhancing teacher identity through innovation.
  • Analysis based on semi-structured interviews with 14 pre-service teachers, revealing the importance of accessibility and feedback.
  • Implications suggest the need for institutional support and integration of AI literacy in teacher education.

Cite This Study

Lucas Kohnke (2025) studied this question.

synapsesocial.com/papers/693624a44fa91c937236c2b7https://doi.org/10.29140/ajal.v8n4.102889
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Principles of GenAI-assisted microlearning: perspectives of pre-service language teachers2025 · 3 citations
  2. 2Investigating Pre-Service Language Teachers’ Experiences with Generative AI in Language Education2026
  3. 3AI as a collaborator: pre-service teachers’ perspectives on preparing multimodal language lessons2026 · 2 citations
  4. 4Teacher educators using GenAI-infused instruction to develop preservice teachers’ professional thinking: a collaborative self-study2026
  5. 5Exploring the Influence of Generative AI on Self-Regulated Learning: A Mixed-Methods Study in the EFL Context2025 · 3 citations