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Integrating generative AI into STEM education: Insights from science and mathematics teachers

Abdulla Al Darayseh, Nazan Mersin

2025International Electronic Journal of Mathematics Education14 citationsDOIOpen Access PDF

Abstract

This study investigates the perceptions of STEM teachers regarding the integration of generative artificial intelligence (AI) applications into classroom settings, using the extended Technology Acceptance Model (TAM) as the framework. The study examines self-efficacy, anxiety, perceived ease of use, expected benefits, attitudes, and behavioral intentions toward AI applications. Data was collected from 448 mathematics and science teachers across various Turkish provinces through an online survey. Results revealed a generally positive attitude toward AI, with male teachers exhibiting higher self-efficacy and perceived ease of use compared to female teachers. However, no significant differences were found across other TAM dimensions, such as stress, anxiety, and expected benefits, based on gender, age, or teaching experience. These findings suggest that while STEM teachers are generally open to AI adoption, targeted interventions are needed to address gender disparities and improve ease of use.

Topics & Concepts

Mathematics educationGenerative grammarScience educationMathematicsComputer scienceArtificial intelligenceOnline Learning and AnalyticsEducational Games and GamificationIntelligent Tutoring Systems and Adaptive Learning
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