European Journal of Education· 2026Q1
L2 Teachers' Work Engagement in AI‐Enhanced Teaching Environments: Harnessing a Phenomenological Approach to Uncover Its Personal and Contextual Determinants
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- 2026year
Short summary
Work engagement in L2 teachers using AI tools is shaped by personal traits (adaptability, AI literacy, self-efficacy, resilience, emotional regulation) and contextual factors (leadership, professional development, colleague support, learner engagement).
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Key points
- Work engagement in L2 teachers using AI is influenced by personal traits: adaptability, AI literacy, self-efficacy, resilience, and emotional regulation.
- Contextual conditions also shape engagement, including leadership behaviors, professional development, colleague support, and learner engagement.
- A descriptive phenomenological approach was used with 49 English language teachers in Chinese educational contexts.
- Thematic analysis of open-ended questionnaire data identified these personal and contextual determinants.
AI-generated from the title and abstract; the full text is not read.
Abstract
ABSTRACT Adopting a descriptive phenomenological approach, this study sought to unravel the determinants of L2 teachers' work engagement within artificial intelligence (AI)‐assisted instructional contexts. To this end, 49 English language teachers were purposefully selected from Chinese educational contexts to complete an open‐ended questionnaire online. Data were thematically analysed using MAXQDA (v. 2024), revealing that teachers' work engagement has been shaped by specific personal traits— adaptability , AI literacy , self‐efficacy , resilience and emotional regulation —and contextual conditions, including leadership behaviours , professional development opportunities , colleague support and learner engagement . These findings highlight how these individual and environmental factors together have influenced teachers' ability to remain engaged while navigating AI‐mediated teaching demands. By uncovering these personal and contextual determinants, the study offers practical insights for educational leaders and policymakers seeking to support L2 teachers in effectively integrating AI tools into instruction.
The authors' abstract, as published at the source. European Journal of Education, 2026 · DOI ↗
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Field: Computer Science Applications
Computer Science ApplicationsComputer Science