AI Literacy in STEM Education: Teachers’ Ethical, Pedagogical, and Epistemic Challenges
Abstract
This study aims to explore the ethical, pedagogical, and epistemic challenges of STEM teachers in integrating AI literacy into STEM education. An exploratory qualitative double case study design was used. Three STEM teachers were chosen deliberately based on their teaching experience and familiarity with digital or AI-powered learning practices. Data was collected through semi-structured interviews, classroom observations, and analysis of AI-related instructional documents and teaching artifacts. Data were analyzed using thematic analysis, followed by in-case and cross-case analysis to identify recurring and distinct patterns among the three teacher cases. The findings reveal three main themes. First, teachers express ethical concerns related to academic integrity, students' reliance on AI-generated answers, data privacy, and the potential for reproduction bias. Second, pedagogical challenges arise in designing meaningful, AI-powered STEM assignments, aligning the use of GenAI with learning objectives, and developing appropriate assessment strategies. Third, epistemic challenges are seen in students' tendency to overtrust AI outputs, limited ability to verify scientific accuracy, and difficulty distinguishing explanations from evidence. Despite these challenges, teachers view AI literacy as essential to promoting critical, reflective, and responsible STEM learning. This study contributes to the growing study of AI literacy by highlighting teachers' experiences and offering practical insights for designing ethical, pedagogy-grounded, and epistemically minded STEM learning environments.
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DOI: https://doi.org/10.24952/ejpm.v3i1.21075
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