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AI Competence of Teachers in a Developing Nation: A Case Study of Hanoi, Vietnam

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  • Tuan Anh Nguyen

    (Hanoi Metropolitan University, Vietnam)

Abstract

This study developed a 40-component artificial intelligence (AI) competency framework to assess kindergarten–12th grade teacher proficiency. Using this framework, the AI competency of 206 Hanoi primary teachers was quantitatively surveyed in July 2025 and again in November 2025. Survey 1 showed overall AI competency was average (scores 40–134/200). While teachers possessed a solid conceptual grasp, significant deficits existed in practical application (tool usage, strategic integration, ethical responsibility, and professional development). Noteworthy weaknesses were in the areas of personalizing student learning and optimizing AI prompts. Analysis identified key challenges: the absence of a standardized national framework, lack of targeted training, and limited self-study capabilities. Crucially, Survey 2 confirmed the framework's practical utility in guiding and motivating teachers toward skill improvement. Based on these results, comprehensive solutions are proposed for management and teachers to accelerate digital transformation and enhance educational quality in Vietnam and similar developing nations.

Suggested Citation

  • Tuan Anh Nguyen, 2025. "AI Competence of Teachers in a Developing Nation: A Case Study of Hanoi, Vietnam," International Journal of Knowledge and Systems Science (IJKSS), IGI Global Scientific Publishing, vol. 16(1), pages 1-37, January.
    • Handle: RePEc:igg:jkss00:v:16:y:2025:i:1:p:1-37
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