AI Integration in STEM and Special Education: Teacher Perceptions, Ethical Challenges, and Pathways to Equity

Artificial intelligence (AI) is transforming Science, Technology, Engineering, and Mathe- 7matics (STEM) education by enhancing data-driven decision-making, supporting personalized 8learning, and addressing data literacy gaps. This paper explores the integration of AI in STEM edu- 9cation, focusing on teacher perceptions, ethical challenges, and equity considerations. Through an 10analysis of current and emerging applications, the study identifies AI’s potential to improve learn- 11ing outcomes, reduce teacher workload, and foster data-informed instruction. However, challenges 12such as algorithmic bias, data privacy concerns, and the impact on teacher autonomy are critical to 13address. The paper offers actionable recommendations, including the implementation of explaina- 14ble AI (XAI) systems, equitable resource distribution, and comprehensive professional develop- 15ment, to support ethical and inclusive AI adoption in STEM education. These insights aim to guide 16educators, policymakers, and researchers in leveraging AI to create equitable and impactful learning 17environments.