Science Educators’ Attitudes and Perspectives on Artificial Intelligence (SEAP-AI) Scale

Abstract

This study examines science teachers’ attitudes and perspectives on Artificial Intelligence (AI) integration into teaching practices. Existing research has largely framed teacher engagement with AI through simplistic binaries of acceptance or resistance, limiting our understanding of how educators perceive both the opportunities and risks of AI. To address this gap, we surveyed 853 K-12 science teachers from Missouri and Texas, applying an alternative, six-dimensional framework grounded in empowerment and protectionism across teacher and student domains. We adapted and validated a 24-item instrument originally designed for literacy educators to the science education context. Confirmatory factor analysis of the 552 participants who completed at least 85% of the survey confirmed strong structural validity and reliability (CFI = 0.928; RMSEA = 0.078) across six factors. Our findings revealed that demographic factors such as teacher age, years of experience, and school location (rural or urban) were not significantly associated with AI-related attitudes. However, professional development (PD) and grade level taught were significant predictors. Teachers with no AI-related PD reported significantly lower empowerment levels compared to those with even minimal PD exposure. Additionally, P-2 science teachers consistently scored lower than their peers in grades 3–12 across multiple factors of empowerment and protectionism. This research contributes a validated instrument for assessing science teachers’ perspectives on AI and underscores the need for equity-focused, developmentally appropriate PD. Supporting teachers’ AI literacy is essential to prevent the reproduction of existing biases and inequalities as AI becomes more integrated into science education.

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