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Voices from the Global South: Myanmar educators' ethical considerations in using generative AI in teaching, learning and assessment

IMPACT SIGNAL83/100
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Information from the abstract

Purpose The rapid integration of artificial intelligence (AI) in education presents many opportunities but also raises critical ethical and cultural challenges. This study aims to explore the current application of AI in education in Myanmar and investigates the conflicts between global AI ethical principles and local cultural values. Design/methodology/approach Employing a mixed-methods research design, the study utilizes quantitative survey analysis alongside qualitative participatory workshops to provide both breadth and depth to the understanding of educators' perspectives. Findings The quantitative findings indicate that while most ethical considerations and practical AI implementation patterns remain consistent across different groups, educators' concern for maintaining human autonomy in AI-assisted education grows significantly with their level of professional experience. Furthermore, the qualitative insights highlight a clear gap between internationally developed (often Global North-centered) AI ethics frameworks and the realities of Myanmar's education context. In particular, socioeconomic challenges and local cultural expectations shape how educators understand and respond to AI. Overall, the study argues that AI ethics in education need to be more locally grounded and responsive to national contexts, rather than relying solely on universal frameworks. Originality/value This paper fulfils an identified need to study how ethical AI integration can be enabled in under-resourced and underrepresented educational contexts. By centering the voices of Myanmar educators and documenting their unique perspectives, the study advances knowledge on AI ethics in education and provides practical, context-sensitive guidance for educators, policymakers and researchers.

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Why this record is monitored

This record has an Impact Signal of 83/100 based on recency, source, collaboration, and bibliographic signals. It prioritizes monitoring and is not a judgment of research quality.

Related topics: Ethics and Social Impacts of AI · Explainable Artificial Intelligence (XAI) · Artificial Intelligence in Healthcare and Education

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Thai researcher and institutional participation

Wai Yan Htut · King Mongkut's University of Technology Thonburi

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Data limitations

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