Authors: Alexis Andres, John Whitmer, Melanie Kurimchak
https://doi.org/10.35542/osf.io/vwn9c_v1
Abstract
New investments in AI infrastructure aim to realize the potential of emerging technologies in K12 teaching and learning. To ensure these investments translate into usable applications, this report synthesizes open science policies from 41 institutions, including 15 philanthropies, 22 federal agencies, and 4 international organizations, to establish actionable guidelines for making research outputs and digital public goods findable, understandable, and technically integrable into existing platforms. Analyzing 91 policy documents and 425 individual requirements, we identified 10 requirement categories, organized into three priority tiers: Essential (>50% of institutions), Important (30-50%), and Specialized (<30%). We also identified four common policy "combos" used to package requirements for specific purposes, ranging from basic technical infrastructure to ethical data sharing. This analysis highlights the convergence around core open science principles, while exposing challenges in policy maintenance and sustainability. The findings offer a practical framework for AI infrastructure sponsors and developers to maximize impact, promote equitable access, and prevent isolated, incompatible solutions that under-resourced institutions cannot leverage or adapt.
Suggested Citation: Andres, A., Whitmer, J., & Kurimchak, M. (2026, March 2). Enabling Uptake of AI Infrastructure in K12 EdTech Applications. Retrieved from osf.io/preprints/edarxiv/vwn9c_v1