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A framework for generative AI policy and guidelines in K-12 education

  • Helen Crompton
  • , Diane Burke
  • , Aras Bozkurt
  • , Christine Nickel
  • , Fengchun Miao
  • , Mark Pegrum
  • , John Curry
  • , David Parsons
  • , Adam Edmett
  • , Lee Ann Lindsey
  • , Manuel B. Garcia
  • , Agnes Chigona
  • , Curtis J. Bonk
  • , Francisco Bellas
  • , Mourad Benali
  • , Pat Yongpradit
  • , Agnieszka Palalas
  • , Andreia de Bem Machado
  • , Hasan Tinmaz
  • , Jinhee Kim
  • Johanna Velander, Junhong Xiao, Lenandlar Singh, Mohan Yang, Mohd Ali Bin Samsudin, Sean Yu
  • Old Dominion University
  • Anadolu University
  • United Nations Educational, Scientific and Cultural Organization
  • University of Western Australia
  • Idaho State University
  • academyEX
  • British Council
  • Northern Arizona University
  • Far Eastern University
  • Cape Peninsula University of Technology
  • Indiana University Bloomington
  • University of A Coruna
  • Regional Centre for the Educational and Training Professions - Oujda
  • Code.org
  • Universidade Federal de Santa Catarina
  • Woosong University
  • Linnaeus University
  • Shantou University
  • University of Guyana
  • Texas A&M University
  • Universiti Sains Malaysia
  • Independent Researcher

Research output: Contribution to journalJournal Articlepeer-review

1 Citation (Scopus)

Abstract

The rapid emergence of generative artificial intelligence (GenAI) has introduced both opportunities and challenges for education systems worldwide. Educational stakeholders are grappling with fundamental questions of how to guide students on whether and when, and in what ways, they should use GenAI. In this study, a framework was developed to guide K–12 policies and guidelines on the use of GenAI. Using the Delphi technique and collective writing, expert perspectives were gathered from participants across 20 countries and six continents. The analysis identified eight key topic areas for K–12 GenAI policy and guideline development: (1) data privacy and security, (2) ethical and responsible use, (3) equitable access, (4) academic integrity, (5) human oversight, (6) GenAI literacy, (7) curriculum integration, and (8) governance and review. A complementary six-part framework was also constructed to support policy relevance and currency through multi-stakeholder governance, continuous review, ongoing training, awareness of external developments, outcome monitoring, and transparent communication. Together, these frameworks advance the scholarly and practical understanding of how GenAI policies can be designed and maintained in schools.

Original languageEnglish
JournalJournal of Research on Technology in Education
DOIs
Publication statusAccepted/In press - 2026

Keywords

  • artificial intelligence
  • framework
  • Generative AI (GenAI)
  • guidelines
  • K-12
  • policies
  • Social Ecological Technology Integration (SETI)

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