Human-Centered AI Governance in K–12 Education: A Qualitative Content Analysis of Policy Gaps in Massachusetts School Districts

Authors

• Simone Elias, Abilene Christian UniversityFollow
• Noran Moffett, Fayetteville State UniversityFollow
• Jeremy Womack, Abilene Christian University
• Richard Brutti, Brandeis University

Abstract

Artificial intelligence (AI) and generative AI tools have rapidly permeated K–12 education, outpacing governance structures and raising urgent concerns about equity, student data privacy, and academic integrity (Eutsler et al., 2026; OECD, 2023). Although a growing body of scholarship proposes multi-level AI governance models for education, empirical evidence on implementing these frameworks at the district policy level remains limited. This article contributes to the field by first synthesizing and adapting a K–12 AI governance framework based on peer-reviewed and policy literature, structured around macro-meso-micro levels and six pillars: ethical and equity-centered use, data governance and privacy, teaching and academic integrity, organizational structures and stakeholder participation, professional learning and AI literacy, and continuous evaluation and adaptive policy (OECD, 2023; Pinho et al., 2025; Region 8 Comprehensive Center, 2024).

Second, the framework is applied through a qualitative content analysis of publicly posted AI-related policies from 10 Massachusetts public school districts, assessing alignment with the Massachusetts Department of Elementary and Secondary Education (DESE) guidance released in August 2025 and identifying governance strengths and gaps. The findings show that district policies focus primarily on academic integrity while consistently under-specifying equity, organizational structures, professional learning, and adaptive policy review, despite comprehensive macro-level guidance. The analysis employs a human-centered governance perspective, conceptualizing AI as an augmentation rather than a replacement for educators. The article concludes by introducing an AI Governance Dashboard, operationalized through the Human-Centered AI Policy Insight Engine (Elias, 2026), as a reflective tool to assist district administrators in evaluating AI governance guidance and identifying areas for improvement, with all outputs intended to inform, not replace, professional judgment and district leadership deliberation.

Recommended Citation

Elias, Simone; Moffett, Noran; Womack, Jeremy; and Brutti, Richard (2026) "Human-Centered AI Governance in K–12 Education: A Qualitative Content Analysis of Policy Gaps in Massachusetts School Districts," Journal of Research Initiatives: Vol. 9: Iss. 3, Article 12.
Available at: https://digitalcommons.uncfsu.edu/jri/vol9/iss3/12