--- title: "Cultivating Belonging through AI and Identity: Moving from Surviving Systems to Reshaping Them | Digication Blog" description: "Inside College Unbound and Digication's AAC&U CLASS 2026 session on cultivating belonging through AI and identity: designing AI-guided reflection that scales relationships rather than replacing them." source: https://www.digication.com/blog/cultivating-belonging-ai-identity --- [Back to all posts](/blog) AI # Cultivating Belonging through AI and Identity: Moving from Surviving Systems to Reshaping Them Digication|April 26, 2026|8 min read What does it actually mean to belong in higher education? Not to be admitted, not to pass, not to comply with institutional expectations, but to genuinely belong? That question sits at the center of a conversation Abby Crew and Jeff Yan brought to the AAC&U Conference on Learning and Student Success (CLASS) 2026 this past April. Their session, "Cultivating Belonging through AI and Identity," drew on years of partnership between College Unbound and Digication to explore what happens when you design technology around belonging rather than efficiency. The answer, it turns out, changes everything. ## Who We're Actually Talking About Before getting to the technology, it helps to understand the students. College Unbound serves a population that looks almost nothing like the traditional college student. Seventy-six percent of CU students identify as BIPOC. Seventy-one percent identify as women. Seventy-nine percent are Pell eligible, compared to 34% nationally. The average student age is 38. These are parents and caregivers balancing family responsibilities with coursework. They are first-generation students navigating systems that were not designed with them in mind. They are people returning to finish degrees they started years ago, working full-time, building new pathways. They are, as the CU framework puts it, not deficits to be remediated but people carrying wisdom that institutions have historically failed to recognize. For these students, belonging is not a soft concept. It is often the difference between staying enrolled and dropping out. ## The Challenge of Scale Here is the tension that every faculty member in higher education knows: the most powerful learning happens in relationships. Deep, reflective conversations between a student and an advisor, a faculty member who sees the whole person, a community that honors lived experience as legitimate knowledge. But those conversations do not scale. A faculty member can have that depth of engagement with a handful of students. They cannot have it with everyone, at every transition point, across a semester. The question College Unbound asked when they began working with Digication was not "What can AI do?" It was something more honest: "What do we value, and can AI serve that?" The answer they arrived at was AI-guided reflection, designed not as a replacement for human connection but as a way to make space for it at scale. ## How AI-Guided Reflection Actually Works Digication's approach positions AI as a coach, not an evaluator. When a student sits down to reflect, they are not filling out a form or answering a checklist. The AI guides them through structured questions connected to CU's Big 10 Competency Framework, mirroring their own language back to them, helping them see patterns in their growth that they might not have named for themselves. The Big 10 framework is worth understanding on its own terms. Rather than measuring student success through GPA alone, it tracks ten competencies: accountability, critical thinking, advocacy and agency, equity and justice, collaboration, well-being, communication, lifelong learning, creativity, and resilience. Together, these form what CU calls a student's "learning fingerprint," a holistic map of where they are strong and where they are growing. The AI does not grade students on these competencies. It helps them see their own patterns. And faculty see the results in an analytics dashboard that gives them something they have rarely had before: a real-time signal into student growth that goes well beyond grades and attendance. Faculty can see depth levels (is this student engaging superficially or deeply?), emerging competencies (which Big 10 areas are showing up organically?), growth patterns over time, and early intervention signals for students who may be struggling before it shows up in their grades. For students whose average journey at CU is approximately 2.2 years, a missed signal in semester one cannot be recovered if there is no semester six. ## What This Looks Like for a Real Student Consider the case of Stacy Archibald, who gave her consent to be named and her reflection shared publicly. Stacy represents a student archetype that institutions serve constantly but rarely design for: someone with deep wisdom and life experience who is paralyzed by the academic blank page. She did not lack insight. She lacked a bridge between her lived knowledge and the institutional framework that would recognize it. When Stacy began a guided reflection session, her opening was simple: "I have no idea where to start." The AI entered not as an author but as a listener. Through guided questions, it helped her translate her natural language into the Big 10 framework in real time. When it asked how her caregiving experience related to Resilience, something clicked. "Oh, that's what that is!" By the end of the session, she was asking, "Can I come back to this? I have more to say." That shift, from "I have no idea where to start" to "I have more to say," is what belonging looks like in practice. Technology did not create that transformation. Technology made the space for it. ## The Prompt Is the Pedagogy One of the most important insights from this work is deceptively simple: most AI tools fail students not because the technology is broken but because the questions the technology asks are wrong. Your AI tool is only as good as the question it asks. At CU, the design question is always: What do we want the student to discover about themselves? That framing changes everything about how prompts are built, what competencies they connect to, and how the AI positions itself in the conversation. When you start from that question rather than from efficiency metrics, you end up with something that feels genuinely different to the student using it. ## A Classroom Conversation Worth Having In a recent capstone class at College Unbound, students used generative AI to translate their Big 10 portfolios into what they called "traditional higher ed speak," the kind of language that grants, graduate programs, and employers recognize. What emerged was not just a writing exercise. It became a deeply uncomfortable and necessary conversation about power, identity, and whose voice gets heard in academic spaces. Students confronted the tension between being understood by institutional gatekeepers and preserving the authenticity of their own voices. Audre Lorde's provocation, "The master's tools will never dismantle the master's house," became a touchstone for the room. One student, Renaldo Hudson, formerly on death row and now a prison reform advocate, brought a perspective that challenged every assumption in the room about what counts as knowledge. This is why design decisions about AI prompts are not neutral. How we design the questions, what we ask students to reflect on, and whose framework we use are all pedagogical decisions with real consequences for belonging. ## What We Do Not Know Yet One of the most refreshing aspects of this work is that its architects are willing to say clearly what they are still figuring out. The data is early and promising, but preliminary. Questions about consent and data ethics, specifically who owns a student's reflection and how it is stored, are being treated not as compliance issues but as questions of student agency. There are also honest questions about AI mimicry versus genuine reflection. How do you ensure students are using AI as a mirror rather than a ghostwriter? Equity in access matters too: not all students have reliable devices or private spaces, and a tool that requires consistent technology access must grapple honestly with who gets left out. And faculty adoption is never automatic. The best tool in the world fails if it adds burden without clear benefit. Their guiding principle through all of it: student agency over AI efficiency. ## An Invitation If any of this resonates with challenges you are working through at your institution, the conversation is worth continuing. The full session details, slides, and LinkedIn links for Abby Crew and Jeff Yan are on our [AAC&U CLASS 2026 event page](/events/aacu-class-2026). From there you can also learn more about College Unbound's model and Digication's AI-guided reflection tools. The question they left hanging at the end of their session is one worth sitting with: Technology didn't create the belonging. Technology made the space for it. What are you making space for? 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