Remixing Special Education Practices with Artificial Intelligence: UDL, EBP, and HLPs
DOI:
https://doi.org/10.33043/3dq2d32dKeywords:
artificial intelligence, universal design for learning, Preservice teacher preparation, high leverage practices, evidence based practicesAbstract
This article presents engaging and practical methods of helping educators to “remix” the evidence-based and high-leverage practices they are already familiar with to include the new capabilities of artificial intelligence (AI). Transformational modern technologies can be powerful and disruptive, possessing the potential to impact multiple areas of society, including education. One of the best ways for educators to implement AI in their teaching is using it to help support and extend their current practices (Mishra et al., 2023). Similar to how a new remix on the radio can make an old favorite song fresh again, educators can use AI to uphold and enhance their existing instructional strategies and skills. However, adapting to the new paradigm of AI in education may be challenging for teacher preparation programs in special education. The authors of this article apply some of the strategies from “Leveraging Emerging Technology to Design an Inclusive Future with Universal Design for Learning” (McMahon & Walker, 2019) to effectively implement AI in education. Rather than needing to start fresh or relearn how to teach while incorporating AI, teachers can view this article as a foundation for how to apply AI tools to support current practice. The recommendations are based on Universal Design for Learning (UDL) and strategies for adapting AI tools to support high-leverage practices and established evidence-based practices. The authors aim to inspire special educators to start using AI to help “remix” and innovate the implementation of their existing instructional strategies.
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Copyright (c) 2024 Don Mcmahon, Jonah Firestone
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