Overview

Generative AI is disrupting practices and policies at educational institutions, specifically those around learning materials and their delivery. For those in the DOERS community, this is particularly critical because different choices in the adoption and use of AI technologies can either enable or conflict with the goals of systematic adoption of high quality open resources and practices. AI optimists see the opportunities for new technologies to boost the capacity of open education projects and resources and to expand to reach more students, while AI pessimists see commercial capture and hype that threatens the goals of the open community.

Educational systems and institutions are under intense pressure to design and adopt policies that both require the use of AI technologies that are seen to be crucial to workforce competitiveness and to punish the use of AI technologies that allow students to disrupt expectations about student work and evaluation, against a backdrop of rapidly changing technology and conflicting evaluations of technological value. Open educational practices can provide key tools for this evaluation – open pedagogical approaches to defuse academic integrity concerns, open educational resources that allow platform neutrality, and the use of AI tools to build around existing OER, while pushing back against the anti-open impacts of increased platformization and commercialization.

In this context, crafting a singular “perfect” policy is impossible. But members of the DOERS network can and should evaluate these policies against their existing goals in their open education work. In this report, we document four core principles that can guide that evaluation, documented through workshops and focus groups with members of the DOERS community.

Those principles are:

1. Prioritize student outcomes – for these individual students here and now. Even if it makes grading harder and even if you haven’t figured out what it means for academia writ large.
2. Engage critically with generative AI – understand what it can and can’t do right now – not projections of what might happen in the future. It won’t always be useful, it won’t always be harmful, but students will have to be able to evaluate the usefulness of the tools that currently exist.
3. Tool choice has to follow pedagogical choice – and those choices must be communicated to students. Unexpected or unsanctioned uses may be a signal about bad/disposable pedagogy, not bad actors. Open pedagogy requires clearly defined pedagogical goals
4. Universal design principles help all users.

Why this report?

As generative artificial intelligence tools gain public attention at a rapid pace, they are also changing practices and policies within educational institutions. These changes are polarizing educators and administrators with widely differing views of the risks and benefits of these technologies.  This is particularly sharp for those working in open education where technological optimism and public interest mission both heighten professional perspectives on these changes.  It’s important to student-centered values of open education and to work together to develop a framework for evaluating the policy decisions that DOERS members face to make coherent decisions during a time of high volatility.

What is this report trying to do?

This report focuses on how to approach the evaluation, adoption, and implementation of generative AI policies that are coherent with the DOERS mission. This report is not intended to be a model policy for AI to be adopted by states and institutions, but rather a way for states and institutions to evaluate policy choices with the DOERS principles in mind – to think about how the choices about AI policies can complement open education policy and align with the principles of innovative, student-focused, collaborative work.

How was this report developed?

This report presents findings from a series of twelve focus groups held in the spring and summer of 2025 with members of the DOERS community including instructors, librarians, and administrators. These structured conversations focused on direct experiences and concerns with generative AI in open education communities with an emphasis on five topics: creation, adaptation & delivery of OER; concerns of social & economic impact; supporting diverse learners; attribution and student practice; and institutional policies. These workshops took place online and were open to members of the DOERS network and related communities of practice.

This report presents a set of four core principles supported by a list of findings that reflect the need and experiences presented in conversation. We hope this report will frame discussions across the open education community and provide helpful context for individual institutions as they adopt policies that reflect DOERS mission “to realize the promise of high-quality, accessible, and sustainable OER implementations to achieve student success at scale.”