Beyond the Myths: What AI Really Means for Social and Emotional Learning and Student Engagement

Stanley O. Zebulon, MS, PMP, FCA, SSL Director, University of Illinois Springfield

Stanley O. Zebulon is a visionary professional who thrives on collaboration, data-driven strategy, and innovation. With deep expertise in finance, investment, cross-sectoral consulting, project leadership and process optimization, he focuses on empowering teams and fostering sustainable growth through a servant leadership approach. He shared his valuable thoughts for the 2026 edition of Education Technology Insights on how Artificial Intelligence (AI) can genuinely enhance social and emotional learning and student engagement, emphasizing that technology should serve as a tool to deepen human connection, not replace it.

In my years working at the intersection of finance, investment, consulting, technology, and education, I have seen few developments ignite as much debate as AI. Conversations about what I call AI-ism in higher education are now ubiquitous, from faculty meetings to policy roundtables and board retreats, yet they are often driven more by fear and misconception than by a clear understanding of AI’s true potential.

For some, AI is simply a shortcut for students to cheat. For others, it is an existential threat to faculty roles; for many administrators, it is a silver bullet that promises to solve retention, advising, and recruitment challenges overnight. Each of these views contains a kernel of truth, but they all miss the bigger picture.

The real story is not about AI replacing what humans do best. It is about AI reframing how we teach, support, and engage students, particularly in one of the most crucial dimensions of education today: social and emotional learning (SEL).

From Transactional Technology to Cognitive Partner

AI is often imagined as a mechanical substitute for human tasks like grading papers, generating content, or answering questions. Its most transformative role is as a cognitive partner. Intelligent tutoring systems, adaptive platforms, and generative tools can automate routine functions, freeing educators to focus on the deep, relational work that drives meaningful learning.

This shift from transactional tasks to transformational teaching is precisely where SEL becomes central. SEL is not about soft skills on the periphery of learning. It is about cultivating confidence, curiosity, empathy, resilience, and collaboration, capacities that determine how students approach complexity and persist through challenge. AI, when thoughtfully deployed, can amplify those capacities rather than diminish them.

Personalization as a Pathway to Belonging

One of the most persistent barriers to engagement in higher education is the “one-size-fits-all” approach. Students bring vastly different backgrounds, learning styles, and levels of preparedness into the classroom. Traditional instruction, even when enhanced with digital tools, struggles to adapt to that diversity.

AI changes this. Adaptive systems can now analyze how students interact with material in real time, adjusting pacing, difficulty, and modality to meet them where they are. This personalization is not just a technical improvement; it is a profound social-emotional one.

“When we harness both, we create classrooms where students do not just master content; they grow as thinkers, collaborators, and resilient problem-solvers.”

When students feel seen, when the learning environment acknowledges their struggles, celebrates their progress, and challenges them appropriately, they are far more likely to engage deeply and persist. This sense of belonging and psychological safety is the foundation on which SEL and academic success are built.

The Dynamic Learning Companion: SEL in Action

This philosophy has led to the development of AI-powered Dynamic Learning Companions (DLCs) that curate adaptive learning experiences to bridge the gap between course content and individual student journeys.

The Dynamic Learning Companion acts as a personalized, on-demand tutor that evolves with each learner. It breaks down complex concepts into accessible explanations, offers instant feedback through interactive Q&A, creates scenario-based exercises to apply theory in context, and even recommends study plans based on performance trends.

But the most powerful outcome isn’t the technology itself; it’s the emotional transformation it enables. Students engage with challenging material without fear of judgment. They receive feedback that builds confidence instead of discouragement. They develop resilience through iterative practice. Over time, they begin to approach learning not as a series of hurdles but as a journey of growth.

Empowering Educators, Not Replacing Them

Critics often argue that AI risks’ depersonalizing education, but my experience shows the opposite. When AI handles routine tasks and provides baseline support, faculty gain more time and space to do what only humans can do: mentor, coach, inspire, and connect. These are precisely the relationships that fuel SEL and, by extension, student engagement.

Moreover, AI can help institutions identify when and where deeper human interventions are needed. Predictive analytics can flag students at risk of disengagement, giving advisors and faculty an opportunity to reach out early with tailored support. Data-driven insights, when paired with human empathy, are far more powerful than alone.

The Future: The Ultimate Collaboration - Human and Machine

The greatest misconception of all is the belief that AI and humans are on opposing sides of education’s future. The truth is that the next era of learning will be defined by their collaboration. AI will illuminate hidden patterns, personalize the learning journey, and expand access to support. Humans will continue to provide mentorship, creativity, ethical judgment, and the emotional intelligence that no machine can replicate.

When we harness both, we create classrooms where students do not just master content; they grow as thinkers, collaborators, and resilient problem-solvers. That is the real promise of AI in higher education. It is not about replacing us. It is about empowering us to do the deep human work of helping students flourish.

AI

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Predictive Analytics