Artificial Intelligence in Science and Technology Education: Potential, Ethics, and Educator Competency for the 21st Century
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Abstract
This article examines the role and potential of Artificial Intelligence (AI) in enhancing the quality of science and technology education, pursuing four primary objectives: analyzing the mechanisms through which AI enables personalized learning experiences, evaluating the effectiveness of Learning Analytics systems in monitoring student progress, exploring the ethical challenges arising from the application of technology in educational contexts, and formulating policy recommendations for institutional administrators and relevant policymakers. The study draws on systematic review of studies conducted over the past decade, complemented by case study analysis from leading educational institutions at both the international level and within the Thai context. The findings indicate that AI demonstrates moderate-to-high positive effect sizes on learning outcomes, particularly in supporting individualized learning and delivering real-time feedback. Nevertheless, such success is significantly associated with teachers' digital competency, which converging research consistently identifies as an indispensable factor in driving digital transformation in the classroom. Furthermore, while AI holds considerable potential for reducing educational inequality, these technologies in practice remain concentrated in resource-rich institutions, and give rise to substantial concerns regarding student data privacy and algorithmic bias that require systematic and sustained policy intervention.
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