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AI-Driven Approaches to Inclusive Science Teaching in a Liberal Arts Context
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2025
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Abstract
This chapter explores AI-Driven Approaches to Inclusive Science Teaching in Liberal Arts Contexts, emphasizing how generative artificial intelligence (AI) can enhance inclusivity through Universal Design for Learning (UDL) principles. Drawing on CAST's framework for AI and UDL, we examine how generative AI tools support personalized learning pathways, improve access, and reduce barriers in science education for diverse learners. Recent findings (Francis, Jones, & Smith, 2025) highlight the importance of balancing AI innovation with academic integrity, while Haroud and Saqri (2025) underscore the varying digital literacies and attitudes of students and faculty toward AI integration. Building on Schreffler et al.'s (2019) review of UDL in STEM for students with disabilities, this chapter illustrates how AI can align with inclusive pedagogies to better serve liberal arts students often underrepresented in science disciplines. We propose practical, ethical, and pedagogical strategies for higher education faculty to implement AI inclusively in science classrooms.
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