Online learning has solved many problems of access. It has made it possible for working adults, military-connected students, parents, caregivers, rural learners, and place-bound professionals to pursue education without stepping away from the rest of their lives.
But access is not the same as attachment.
As AI becomes embedded in online learning, institutions face a familiar temptation: to treat the next technology as the solution to problems that are partly technological, but mostly relational. AI can generate feedback, support tutoring, personalize practice, assist with advising, improve course design, and identify patterns in student engagement. Used well, AI can make online learning more responsive and humane. But it will not, by itself, make students feel known, trusted, or connected to a larger educational community.
That is what is meant by belonging as infrastructure. Belonging should not depend on a charismatic instructor, a strong cohort, or a lucky advising relationship. It should be intentionally built into the systems, roles, rhythms, and handoffs that shape the online learner experience from inquiry through graduation and beyond.
Beyond Interaction
For years, online educators have talked about interaction: student-to-content, student-to-instructor, and student-to-student. Those categories remain useful, but they are no longer enough. A student can post in a discussion board, watch a video, and receive feedback while still feeling disconnected from the institution and from the purpose of their education. Belonging asks: does the learner experience the course, program, and institution as a community they are part of?
This matters because online students often operate at the edge of institutional visibility. They may not walk across campus, sit outside a faculty office, attend student events, or casually meet classmates after class. Their relationship with the institution is mediated through course shells, emails, portals, advising appointments, and digital platforms. When those systems are fragmented, online learning can feel transactional rather than coherent.
The scale of this issue is not small. NC-SARA’s most recent annual data report analyzes exclusively distance education enrollment from more than 2,400 participating institutions. Recent research in Online Learning on post-traditional online students also emphasizes that belonging is central to online learner experience, especially for students whose lives and responsibilities do not fit traditional residential assumptions. Online belonging is not a soft add-on. It is part of quality, persistence, and student success.
Where AI Can Help
AI can support this work, but only if institutions use it to strengthen human connection rather than replace it. AI-enabled analytics might help faculty or advisors notice when a student has stopped logging in, missed a key assignment, or is repeatedly asking for help with the same concept. A virtual assistant might help a student locate tutoring, prepare questions for an advisor, or translate program requirements into a usable next step. Generative AI might help instructors draft formative feedback, freeing time for targeted outreach.
Each example depends on human-centered design. The alert should lead to a real person reaching out. The chatbot should help students find people, not avoid them. The feedback should invite dialogue, not reduce teaching to automated response. The goal is not more automation for its own sake. The goal is more timely care, clearer pathways, and stronger connection.
That also requires attention to trust and ethics. Students should know when they are interacting with AI, how their data are used, what decisions remain human, and where they can go for help. The U.S. Department of Education has emphasized keeping humans in the loop, and UNESCO has highlighted privacy, transparency, and ethical governance as central considerations for generative AI in education. Without trust, AI will not deepen belonging. It may weaken it.
Four Practical Design Commitments
First, design visible presence. Online students should know who is teaching, advising, supporting, and listening. That can include a welcome video, predictable weekly instructor communication, clear response times, advisor check-ins, and opportunities to hear from alumni or professionals in the field.
Second, design for purpose. Courses should help students connect assignments to identity, career goals, ethical questions, community needs, and future opportunities. A discussion prompt that asks students to apply a concept to their workplace, family, military experience, or community can do more for belonging than a generic prompt that merely verifies reading.
Third, design pathways. Online learners should see how individual courses connect to credentials, careers, graduate study, civic contribution, and lifelong learning. Programs can use milestone maps, career-linked assignments, alumni panels, employer-informed projects, and advising touchpoints to help students understand where they are going.
Fourth, design participation. Students should not only consume content. They should contribute to a learning community through discussion, collaboration, peer review, mentoring, reflection, and shared problem-solving. Even small structures matter: peer partners, student-generated examples, low-stakes introductions, collaborative resource lists, or end-of-course advice for future students.
The Leadership Challenge
The leadership challenge is to stop treating online learning as a collection of courses and start treating it as a learning ecosystem. Faculty, designers, advisors, career services, alumni, employers, and community partners all shape whether online students feel connected or alone.
AI will change online education. It already is. But the most important question is not simply how students will use AI or how faculty will detect it. The deeper question is what kind of relationships institutions are building in an AI-enabled world.
If online learning is treated as content delivery, AI will make content delivery faster. If it is treated as administration, AI will make administration more automated. But if online learning is treated as an ecosystem of learning, support, purpose, and connection, AI can help make belonging more durable.
Institutional leaders should make that choice intentionally. Audit the online learner journey. Find the points where students disappear, wait, repeat themselves, or feel unknown. Then redesign those points so AI supports timely human connection rather than substituting for it.
Online learning opened the door for millions of students. The next challenge is making sure they do not walk through that door alone.
Dr. Joe D. Lyons is an Associate Professor and senior academic leader at Saint Louis University, where he serves as Faculty Senate President, Director of Security and Strategic Intelligence, Director of the Midwest Intelligence Community Center of Academic Excellence, and Co-Director of the SLU Cyber Center. His work focuses on higher education strategy, adult and online learning, AI in education, workforce development, shared governance, and interdisciplinary academic systems.
