Announcements & Commentary
From One Learner to Many: Why Scale Is a Prerequisite for Equity
By Maria Anguiano, Entrepreneur-in-Residence at College Futures Foundation
In this blog series, I’ve been exploring what it really means to build a postsecondary system around the lives and needs of today’s learners. The first two posts looked at how rigid structures block opportunity and how flexibility can help. This third post makes the case that in a digital world, scale isn’t a barrier to equity, it’s actually a condition for it.
Why Scale Has Failed In the Past and Why It Can Work Differently Now
For many educators and learners, the word scale can feel like a warning sign, and their concerns are valid. In an analog world, scaling education has often meant forcing more people into the same rigid design, leaving those whose lives don’t fit it struggling on the margins.
Traditional higher education reflects analog logic. Its structures, such as fixed curricula, rigid course sequences, advising structures, were designed with expertise and care, but not for personalization or adaptability. Even when dedicated to continuous improvement, in analog systems, this work is slow and uneven. Courses change once a year, if that. Feedback comes after it’s too late to help. A student’s struggle is treated as an individual challenge, not a signal to improve the system. This rigidity impacts students balancing work, caregiving responsibilities, or financial pressure the most. For them, waiting until the end of a semester to discover they’ve fallen behind isn’t just discouraging, it can be the difference between persisting and stopping out.
Scale, in a digital world, plays by different rules. Digital systems, when designed well, don’t force everyone into the same mold. They learn and improve with every interaction. Some of the most powerful platforms in daily life (e.g. Netflix, Amazon, Spotify) operate on this same principle. Netflix suggests a film based on your tastes. Amazon refines its recommendations with every click and return. Millions of micro-interactions teach the system how to serve people better. The more people who use it, the smarter it becomes. Education isn’t entertainment or shopping. But these platforms illustrate a principle that’s critical for education to adopt: digital personalized systems that improve with use.
This is one of the most overlooked benefits of scale. The more people who use a digital system, the more opportunities it has to learn, improving quality for everyone who comes after. This strategy is not about putting things “online”, but building systems that get better because they’re used by many. We have the opportunity to create digital learning platforms that have the ability to adapt, refine, and personalize, not in spite of scale, but because of it.
In an analog world, a printed map can only show the routes known when it was published. It’s useful, but it’s static and unable to adapt when construction reroutes traffic or when a new road opens.
A digital map works differently. It updates in real time, drawing on the experiences of millions of drivers. When someone reports an accident, the system reroutes you. When traffic slows, it suggests an alternative path. The more people who use it, the more accurate and helpful it becomes.
The same principle can apply in education. As an example, a new collaborative project led by UC Davis, working with four California Community Colleges and three CSU campuses, is building exactly this kind of adaptive, learning system for writing instruction. Funded by the California Education Learning Lab, the Peer and AI Review + Reflection (PAIRR) initiative pairs human feedback with generative AI feedback to give students more timely, specific, and actionable support on their writing.
Involving 114 instructors across UC, CSU, and CCC campuses and thousands of students, each interaction – every peer review, every AI-generated comment, every student reflection – feeds back into the system, helping it adapt and improve. The result is more personalized feedback and importantly, timelier and more accessible to students who might otherwise get little individualized attention in large courses. The larger the pool of students and instructors engaging with PAIRR, the stronger and more responsive the system becomes.
When designed with intention, digital learning systems can surface where students are succeeding, where they’re stuck, and what supports will help most. For those students that are balancing multiple priorities and can’t attend every office hour, this type of 24/7 personalized digital support is essential.
Economies of Scale
Too often, digital tools in education are built in isolation, customized for one professor, one program, or one campus. While local innovation is essential, this siloed approach keeps good ideas from spreading and makes them too expensive for any one institution to build and maintain.
That matters because when tools stay locked in one place, inequities multiply. Students at smaller or under-resourced campuses are left without the same supports available to their peers elsewhere. High-quality advising bots, adaptive courseware, or tutoring platforms risk becoming privileges of the best-funded institutions, rather than benefits for all learners.
When built for shareability, through modular design, open-source infrastructure, or clear interoperability, learning systems can scale across institutions without losing quality or context. At UC San Diego, for example, TritonGPT, a student co-designed, open-source virtual assistant, is helping thousands of learners navigate everything from financial aid to course planning. All 38,000 faculty and 44,000 students have access to this tool. It has an open design making it easy to adopt and customize and it’s already being used across institutions, including at San Diego State University and local community colleges.
These are expensive tools and courses to build. Viewed from the perspective of a single campus, they may seem unaffordable. But when designed for scale and shared across tens of thousands of learners, they become cost-efficient and high-impact.
That’s why efforts like the California Education Learning Lab are so important. The Lab pools R&D dollars to support cross-campus faculty teams, building shared courseware in high-demand fields like math and biology, and funding experiments that test how adaptive tools can close equity gaps. The equity impact is clear. Instead of every campus reinventing solutions with limited funding, coordinated investments can start to build shared infrastructure for California’s public education system, reaching students with high quality tools, regardless of which institutions they attend. Collaboration should not be limited to California efforts only, there are opportunities to use national tools, such as ASU’s REAL Chem course that is utilized by colleges around the country, including UC Riverside.
Let’s Build Intentionally
Digital scale has tremendous promise. However, in order to harness that promise, we need to rethink our framework for funding innovation in education. That means moving beyond one-off pilots and making bold, coordinated investments in statewide infrastructure, shared tools, interoperable systems, and digital supports that every learner can access, no matter where they begin. Scale is not the enemy of equity; it’s how we spread what works, stretch scarce dollars further, and make sure innovation doesn’t stop at a single campus gate.
Education is, and always will be, a profoundly human endeavor. The systems that support it, however, can be smarter, more adaptive, more responsive, and more equitable with every learner they serve.
