Open Education Doesn’t Need More Clutter. It Needs Clearer Pathways.

What the National Needs Assessment reveals about OER, open educational resources, and the next layer of affordable learning support.

Open education has never lacked values.

The field knows how to talk about access, affordability, equity, student agency, shared knowledge, and the public good. Those values matter. They’re why many of us found our way into this work in the first place.

But the Open Education Association’s National Needs Assessment points to a different kind of challenge. Many people aren’t asking whether open education matters. They’re asking how to find the right OER, how to access usable tools, how to respond to political and technological change, how to secure funding, and how to turn belief into practice (Allen, 2025).  

In other words, open education doesn’t simply need more enthusiasm. It needs clearer pathways.

And honestly? That feels right. The field is full of smart people, generous resources, open textbooks, guides, repositories, webinars, toolkits, and examples. We have OpenStax, OER Commons, LibreTexts, Lumen Learning, Pressbooks projects, state networks, library guides, communities of practice, and enough Google Drive folders to make even the most committed open education person stare quietly into the middle distance.

The problem isn’t emptiness.

The problem is navigation.

OER is being searched for, but search is not the same as support

Keyword research tells its own little story. In the U.S. market, “OER” gets far more search traffic than the full phrase “open educational resources.” That tracks with how people often enter the work. They don’t always begin with theory. They begin with a need.

They search “OER.” They search “open educational resources.” They search “OER Commons” or “OpenStax anatomy and physiology” or “open education resources” because they’re trying to solve a course problem, a student affordability problem, a textbook problem, a curriculum problem, or a “please do not make me rebuild this entire class from scratch” problem.

The long-tail search patterns around major OER sites show the same thing. Homepages matter, but much of the traffic comes from specific discipline and topic pages: anatomy, physics, chemistry, biology, calculus, U.S. history. Faculty and students often search for the content first, not the platform.

That’s a tiny SEO clue with a big program design lesson tucked inside.

People do not usually enter open education through our most elegant definitions. They enter through a course, a discipline, a resource gap, a student need, a teaching problem, or a moment of frustration.

So when OER programs and affordable learning initiatives offer only broad-awareness messaging, we miss the actual entry point. “What are open educational resources?” is still an important question, but many people also need the next layer:

• Where do I find OER for my course?

• How do I know if an open textbook is any good?

• What counts as open, and what’s just free?

• Can I adapt it?

• What about ancillary materials?

• How much time is this going to take?

• Who can help me think through the options?

That’s where the work gets real.

The national needs assessment points to practical gaps

The Open Education National Needs Assessment Survey was conducted in spring 2025 with input from 1,327 community members across all 50 states. The survey focused on U.S. higher education and used an Outcome-Driven Innovation approach, which looks at the activities people are trying to accomplish and how satisfied they are with the current support for those activities (Allen, 2025).  

That framing is useful because it doesn’t begin with “What should we promote?”

It begins with “What are people trying to do?”

The nine activities studied included finding OER, accessing tools and resources, staying up to date, responding to political or technological change, accessing professional development, securing funding, adapting or publishing OER, networking, and receiving recognition for open education work (Allen, 2025).  

The highest-rated needs were very practical. Finding OER was rated important by 80% of respondents, and accessing tools and resources by 71%. Satisfaction was lowest for funding, at 32%, and responding to political and technological change, at 20% (Allen, 2025).  

Those numbers tell us something important.

Open education programs are not just asking for more awareness. They need support for doing the work. They need help finding resources, responding to change, securing funding, and accessing curated tools that make the work easier to start and sustain.

The clearest opportunity areas in the assessment were finding OER, responding to change, accessing tools and resources, and securing funding. The report also suggests that the greatest need may not be a single brand-new solution, but rather better amplification and use of the solutions that already exist (Allen, 2025).  

That’s the spicy little center of this whole thing. We may not need to keep making more stuff.

We may need to make the good stuff easier to find, understand, trust, adapt, and use.

The issue is not just awareness. It is enterability.

I keep coming back to the word enterability.

Enterability asks whether people can actually enter a program, practice, or field. Not whether they’re technically allowed in. Not whether the information exists somewhere. Not whether there’s a 47-page guide hiding three clicks deep on a website last updated during a former organizational era.

Enterability asks:

• Can people find the door?

• Can they understand the invitation?

• Do they know what to do first?

• Can they see where the path leads?

• Do they feel capable enough to begin?

Open education has an enterability problem.

A faculty member may care about textbook affordability and still not know where to find high-quality OER in their discipline. A librarian may want to support open educational resources but lack a program structure, data workflow, or campus strategy. A teaching and learning center may value open pedagogy but not know how to connect it to professional development, assessment, or institutional priorities. An administrator may appreciate student savings but not understand the faculty labor behind adoption, adaptation, accessibility, and maintenance.

When we treat those gaps as motivation problems, we miss the design issue. People don't always fail to enter because they don’t care. Sometimes the door is hard to find. Sometimes the instructions are hidden. Sometimes the path was built for people who already know the code.

Faculty support has to respect real conditions

The Gonzaga University Faculty OER Needs Assessment offers a useful local example of why OER support has to be designed around actual faculty needs, not assumptions. Foley Library created the assessment because it had data on how course material costs affected students but lacked data on faculty behaviors, preferences, awareness, attitudes, needs, and barriers related to OER (Pekala, 2022).  

That distinction is doing a lot of work.

Student affordability data can tell us why OER matters. Faculty needs assessment can tell us what kind of support the work requires.

At Gonzaga, faculty were not simply choosing course materials based on cost. The top factors faculty prioritized were quality, subject coverage, and currency. Cost mattered, but it wasn’t the leading factor for most respondents (Pekala, 2022).  

That should shape how OER programs talk about the work.

If the message is only “free is better,” many faculty will hesitate. And honestly, they should.

Faculty are responsible for learning quality, disciplinary fit, academic freedom, course outcomes, accreditation needs, student experience, and their own limited time. OER can support those things, but only when the conversation respects them.

The Gonzaga report also shows how much confusion remains around what counts as OER. Some faculty reported familiarity with OER while also showing less familiarity with Creative Commons licensing, and some resources identified as OER appeared to be free but not openly licensed (Pekala, 2022).  

That’s not a tiny technicality. It is one of the core design challenges for open education support.

“Free,” “library-provided,” “affordable,” “online,” and “openly licensed” are not interchangeable. If we want people to use OER well, we can’t assume everyone already understands the difference.

OER programs need discipline-sensitive support

The Gonzaga findings also point toward the need for more specific support. Among faculty who had never used OER, the top reasons were lack of awareness, satisfaction with current materials, and not knowing where to find quality OER in their discipline. Faculty who had used OER reported high satisfaction overall, but barriers remained around fit, quality, ancillary materials, and long-term access (Pekala, 2022).  

This is where generic OER awareness starts to run out of road.

Faculty don’t only need an OER 101 workshop. They may need:

• a discipline-specific search consultation

• a curated shortlist of open textbooks or open educational resources

• help comparing OER with current commercial materials

• examples from peers in their field

• guidance on Creative Commons licensing

• a realistic estimate of time and labor

• support for adaptation, accessibility, and implementation

• a low-stakes way to explore before committing to adoption

Gonzaga faculty recommended informational workshops, opportunities to learn from faculty peers already using OER, and department- or school-level conversations. Tenure-track and early-career faculty showed particular interest in financial incentives for adapting or creating OER (Pekala, 2022).  

Faculty comments also revealed a healthy caution. Some respondents worried about being forced to use OER. Others questioned whether the initiative respected academic freedom or accounted for the labor of finding, creating, and curating materials (Pekala, 2022).  

That concern deserves more than a polite nod.

Open education advocacy that ignores faculty labor eventually recreates the same extraction it claims to resist. If we want OER adoption, open pedagogy, and affordable learning work to last, we need support models that recognize time, expertise, context, and choice.

Programs need local evidence, not copy-paste models

No two OER programs are exactly alike. A community college, a research university, a small private institution, a statewide system, a library-led initiative, and a teaching-center-led initiative may share values, but they do not share the same conditions.

That means open education programs need local evidence before they design local interventions.

The Council of Australasian University Librarians’ OER Advocacy Toolkit recommends evaluating an OER program by returning to the original purpose of the program and asking whether the program met that purpose and how that can be evidenced. Suggested evidence includes workshops conducted, attendance, open textbook adoptions, adoption patterns by discipline or year level, and the number of students engaging with open textbooks (Council of Australasian University Librarians [CAUL], 2025).  

That sounds simple, but it changes the work. It means programs should define success before they try to report success.

One program may be trying to increase first-year textbook affordability. Another may be trying to build faculty publishing capacity. Another may be supporting open pedagogy, student co-creation, departmental adoption, course marking, or a statewide affordable learning strategy. Another may be trying to build institutional memory after years of informal, person-dependent work.

Those programs need different evidence because they are trying to do different things.

The IES Program Evaluation Toolkit offers a useful structure here. It presents program evaluation as a step-by-step process that can include logic models, evaluation questions, data sources, data collection instruments, analysis, and dissemination (Stewart et al., 2021).  

For OER and affordable learning programs, this kind of structure can move assessment away

from “What numbers can we gather at the end of the year?” and toward better questions:

• What problem is this program designed to address?

• Who is the program meant to support?

• What activities are we using to create change?

• What evidence would show progress?

• What can we responsibly claim from the data we have?

• What do we still not know?

That last question is not a weakness. It is program maturity.

The IES toolkit also emphasizes that evaluation design should consider threats to validity regardless of whether the evaluation asks process or outcome questions (Stewart et al., 2021).  

That’s a useful reminder for OER programs. Student savings estimates are important. Adoption counts are important. Student reach is important. But when we make claims about retention, success, equity, or learning outcomes, we need to be careful about what our evidence can and cannot show.

Credibility is part of sustainability.

Data should function as a listening system

The OER Starter Kit for Program Managers describes data as the “peripheral nervous system” of an OER program because it helps a program assess successes, failures, emergent ideas, and urgent issues. Data can also guide strategic decision-making, support storytelling, and reveal needs for targeted programming and funding (Gallant, 2022).  

I love that framing because it moves data out of the compliance closet.

Data is not only something we collect because someone above us asked for a report. At its best, data helps a program listen.

It helps us notice where people are getting stuck. It helps us see which disciplines are participating and which are not. It helps us understand whether faculty need OER search support, funding, workshops, peer examples, licensing help, accessibility support, or time. It helps us tell a fuller story than “we saved students money,” even though student savings absolutely matter.

The OER Starter Kit also recommends starting data planning with stakeholder questions rather than jumping straight into collection. Executive administrators, faculty, instructional designers, students, student government, and campus stores may all need different information from an OER program (Gallant, 2022).  

That is a care-centered design principle hiding inside a data chapter.

Don’t collect everything.

Don’t collect randomly.

Don’t build a spreadsheet and call it assessment.

Ask who needs to know what, why they need to know it, and how the information will be used to improve the work.

The OER Starter Kit also makes a strong case for qualitative data. Qualitative data can explain the meaning behind quantitative findings, surface emotions and opinions, and identify emerging trends that fixed survey questions may miss (Gallant, 2022).  

That is especially important in open education.

A savings estimate will not tell you that a faculty member needed three conversations before they felt confident enough to change a course. An adoption count will not tell you that students felt more prepared because they had access to materials on day one. A dashboard will not tell you that a department is interested but worried about quality, accreditation, labor, or academic freedom. A grant report will not automatically capture the messy middle where most implementation actually happens.

Programs need numbers. They also need stories. They need evidence of reach and evidence of experience. They need assessment practices that can hold both.

What OER and affordable learning programs need now

Reading these sources together, I see a clear pattern.

OER and affordable learning programs do not simply need more awareness campaigns. They need infrastructure that helps people move from values to practice.

That infrastructure includes:

• Clear entry points. People need to know where to begin, what support exists, and what step makes sense for their context.

• Curated tools and resources. Programs need fewer overwhelming link lists and more contextualized pathways, guides, examples, and how-to supports.

• Discipline-sensitive support. Faculty need help finding and evaluating OER that fit their courses, fields, learning goals, and students.

• Respect for faculty labor. OER work takes time. Exploration, adoption, adaptation, creation, accessibility review, licensing, and implementation are real work.

• Funding and sustainability strategies. Programs need support securing funds, making the case for investment, and connecting affordable learning to institutional priorities.

• Change-response capacity. AI, policy shifts, funding cuts, political pressure, platform changes, and institutional restructuring all affect open education work. Programs need strategy, not panic.

• Mixed-methods assessment. Savings, sections, enrollments, and adoptions matter. So do interviews, reflections, case studies, student experiences, and faculty learning.

• Ethical data practices. Programs should collect data with purpose, consent, privacy, equity, and usefulness in mind.

• Documentation and knowledge transfer. If the program only lives in one person’s inbox, memory, or heroic over-functioning, it is fragile.

This is the work I think of as the hinge.

The hinge is not always the most visible part of open education. It is not the keynote, the finished open textbook, or the final impact report.

It is the structure that helps someone enter.

The intake form. The Canvas module. The search template. The landscape brief. The grant pathway. The peer conversation. The decision guide. The workshop follow-up. The shared tracker. The careful explanation of what counts as OER and why licensing matters. The moment when someone who felt overwhelmed realizes there is a next step they can actually take.

That hinge work is not extra. It is what makes participation possible.

From open values to open practice

The National Needs Assessment shows a field with real strengths. Many people know where to turn for support, and many existing networks are serving important needs. But the same assessment also shows gaps in coordination, recognition, funding, response to change, and access to usable tools and resources. Only 14% of respondents rated the field as well coordinated nationally, and only 15% rated it as well recognized nationally (Allen, 2025).  

That tells us the next phase of open education work is not only about persuasion.

It is about infrastructure.

It is about designing OER programs that are easier to enter, easier to sustain, and easier to explain. It is about making support visible before people are overwhelmed. It is about honoring faculty expertise while reducing unnecessary labor. It is about gathering evidence without overclaiming. It is about treating data as listening, documentation as care, and program design as an access issue.

This is also the layer of work I am building toward through The Open Practice Academy: helping open education, OER, and affordable learning programs move from values to usable, sustainable practice.

Because open education does not need to become louder to matter.

It needs to become more enterable.

It needs doors people can find, pathways people can trust, and structures that help the work hold.

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References

Allen, N. (2025, August 4). National needs assessment survey results. Open Education Association. https://www.opened.org/posts/2025/national-needs-assessment-survey-results

Council of Australasian University Librarians. (2025). Open educational resources advocacy toolkit: Evaluating your OER program. https://caul.libguides.com/oer-advocacy-toolkit/evaluate-your-advocacy/evaluate-your-OER-program

Gallant, J. (2022). Data collection and strategies for OER programs. In A. K. Elder, S. Buck, J. Gallant, M. Seiferle-Valencia, & A. Ashok (Eds.), The OER starter kit for program managers. Rebus Community. https://press.rebus.community/oerstarterkitpm/chapter/chapter-21-data-collection-and-strategies-for-oer-programs/

Pekala, S. (2022). Faculty open educational resources (OER) needs assessment. Foley Library Scholarship, Gonzaga University. https://repository.gonzaga.edu/foleyschol/1

Stewart, J., Joyce, J., Haines, M., Yanoski, D., Gagnon, D., Rhoads, C., & Germeroth, C. (2021). Program evaluation toolkit. Institute of Education Sciences, Regional Educational Laboratory Central. https://ies.ed.gov/use-work/resource-library/resource/tooltoolkit/program-evaluation-toolkit

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AI Use Disclosure

This post was developed with AI-supported assistance for brainstorming, organization, drafting, revision, editing, and/or source-note synthesis. I use AI as a thinking and accessibility tool, not as a replacement for human judgment, lived experience, professional expertise, or ethical responsibility.

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