The Invisible Framework: Unpacking the Policy Realities and Use of Generative AI and Adaptive Learning Platforms in Large K-12 Public School Districts in the United States

Abstract

The rapid advancement of artificial intelligence (AI) technologies has significantly impacted various sectors, including education. This study contributes to the field of educational technology and policy by examining the current landscape of Generative AI and Adaptive Learning Platform (ALP) use, regulation, and implications in U.S. K-12 public education. Through a comprehensive analysis of seven nationally representative school districts, the research explores the acceptable use policies, AI technology adoption, and the evolving roles of students and teachers in the context of AI integration. The findings reveal a lack of comprehensive and consistent frameworks for governing AI technologies in educational settings, with most districts relying on implicit or indirect regulation. The study highlights the widespread adoption of both Generative AI and ALPs across the sampled districts, focusing on tools that support personalized learning, adaptive instruction, and teacher productivity. However, the lack of explicit guidance on the use of these technologies and the potential for inconsistent implementation raise concerns about the impact on educational equity and student outcomes. The comparative analysis of AI policies and practices underscores the need for clear, comprehensive, and accessible policies that explicitly address the unique considerations and challenges associated with AI technologies in education. The study emphasizes the importance of promoting consistency and collaboration in AI policy development, prioritizing teacher training and support, addressing equity and access concerns, fostering stakeholder engagement and transparency, and encouraging ongoing research and evaluation. The implications of this study are significant for educators, policymakers, and technology developers seeking to harness the benefits of AI while mitigating its risks and ensuring equitable access and outcomes for all students. The findings and recommendations presented in this research serve as a foundation for informed decision-making and the development of best practices for the responsible and effective integration of AI technologies in K-12 public education.