Beyond Memorization: How AI Serves as a Cognitive Partner in Learning

By Bren Triplett, Director of Information Technology Programs at Colorado Christian University

This spring, I stood in front of a room of my CCU colleagues at our Leadership in Action conference and opened with the question I'd been sitting with for years.

What if learning is built on a cognitive ability that not everyone has?

I wasn't asking it rhetorically. I was asking it because I live the answer every day. I have aphantasia. I can't form a picture in my mind, not of a face, not of a room, not of a word on a page I read an hour ago. For most of my life, I didn't know that had a name. I just knew that when a professor said "picture this," I did what I'd always done: I listened harder, took better notes, and worked around the blank space where a mental image was supposed to be.

Traditional higher education runs on a recall model. Read something, hold it in your mind, retrieve it later on an exam or in an essay. That model assumes every student can generate internal imagery, retain it, and pull it back on command. My experience says that assumption isn't universal, and once I started looking, I found I'm far from alone.

Why Traditional Learning Leaves Some Students Behind

Here's how I explained it to my colleagues at Leadership in Action — Aphantasia is the inability to mentally bring up any pictures in your mind at all. I literally don't have a mind's eye.

The word itself comes from the movie Fantasia: aphantasia means without the vivid, Disney-style imagery most people can conjure on demand. What surprised the room wasn't the definition. It was learning that aphantasia sits on a spectrum. Some people who can't picture anything still get a workaround: a smell that triggers a memory, a sound that pulls up a moment. I'm in the rarer end of that group, the ones who don't get any of those backup channels either. No pictures, no substitute cues. Just a different way in.

I don't say that looking for sympathy. If anything, it's made me an original thinker, because I was never able to lean on the shortcut everyone assumes exists.

Aphantasia is one data point in a much larger picture. Research published in the journal Consciousness and Cognition assessed aphantasia prevalence in 5,010 U.S. adults and found a self-reported rate of 8.9 percent, with broader estimates from other studies typically closer to 4 percent.

In a lecture hall of thirty students, that's likely at least one person sitting there while an instructor says "visualize this" and gets nothing back. They're not distracted. They're doing their best inside a system that wasn't built with them in mind.

Zoom out further, and the picture gets bigger. Current estimates suggest that anywhere from 10 to 30 percent of college students may be neurodivergent, a range that includes students with ADHD, dyslexia, autism, and other differences in how information gets processed, stored, and recalled.

According to the U.S. Department of Education's National Center for Education Statistics, nearly 20 percent of undergraduate students report having a disability, and the real figure is likely higher, since most students who could use support never disclose it. When I say this out loud, I'm always careful to underline that these are conservative, source-backed numbers. The lived reality, in my experience talking to other neurodivergent faculty and students, feels bigger still.

None of this is a deficiency story. It's a design story. Recall-based instruction was built around one kind of mind. When your mind works differently, you don't fail because you're incapable. You struggle because the delivery model and your cognition don't match.

What Extended Cognition Means for How We Learn

The framework I used at the conference to make sense of my own experience is called extended cognition, the idea, rooted in the work of philosophers Andy Clark and David Chalmers, that thinking doesn't have to stay locked inside the skull. It can happen in partnership with tools, systems, and other people. When you write something down not just to record it but to work it out, the writing is doing cognitive work. The notebook isn't separate from the thinking. It's part of it.

That's the frame I brought to my presentation, and it's what I told the room next, "This work is grounded in lived cognitive difference, not just a theory. This is how I live my life."

When I went looking for research that tied AI directly to cognitive neurodiversity in higher education, I mostly found gaps. Plenty of research exists on aphantasia. Plenty exists on AI tools in isolation. Almost none of it connects the two. That's the piece I think is missing, and it's the piece I want to help build, both through my own writing and, frankly, by talking to the software vendors building these tools about what an intentionally designed model could look like.

Once you see learning through the lens of extended cognition, AI stops looking like a shortcut and starts looking like scaffolding. A student mapping a concept out loud with an AI tool isn't avoiding hard thinking. They're extending their working memory to do something their brain finds harder without support.

For neurodivergent learners specifically, this describes something many of them have already been doing for years with sticky notes, text-to-speech software, and visual organizers. Those were never workarounds. They were cognitive partners doing shared work. AI usage in college students is simply the newest, and most responsive, version of that same partnership.

How AI Serves as a Cognitive Partner and Equalizer

I don't have to speculate about whether this works. My brother teaches fourth grade, and everything I was proposing that day, he'd already tried.

He assigned a three-day, five-paragraph essay with AI-assisted, real-time feedback built in. Ninety percent of his students pushed back immediately: they didn't want to write, didn't see the point. One student in particular had said flatly that he'd never learn to write and saw no value in it. Within three days, working with instant feedback instead of waiting weeks for a grade, that same student turned around and asked my brother something none of us expected, "Can we keep going? This is so fun and so engaging. I want to learn to continue to write better."

That's not an AI replacing a teacher. That's a kid who'd already decided writing wasn't for him, getting pulled back in because the feedback loop closed in minutes instead of weeks. The same class built a math-facts game in real time, in a maze format, and got so invested that kids started asking to skip recess to keep playing it. After those two lessons, a school-wide evaluation showed his students reading and working math facts at a fifth- or sixth-grade level. When he told colleagues how he'd done it, most of them weren't interested. That reaction is its own data point about how far the field still has to move.

I brought up my brother's classroom as an illustration, but I'm testing the same principle at the university level, and I'm not the only one. Another CCU faculty member at Leadership in Action described giving unusually detailed AI-assisted feedback on projects in a graduate project-management course. Her students finished their core deliverable by week four instead of week five, freeing up the final week for refinement instead of a scramble. That's the same mechanism showing up in an adult, online, graduate context: faster, more specific feedback closes the gap between doing the work and understanding it.

This is what AI usage in college students actually looks like when it's working well, and it's more varied than the headlines suggest. Students use generative AI to restate a dense concept in simpler language, to pressure-test their understanding before committing an idea to paper, or to generate a second explanation when the first one didn't land. A student with ADHD might use AI to break a large assignment into smaller, sequenced steps. A dyslexic student might lean on it to check sentence flow so the idea on the page matches the idea in their head. A student with aphantasia, like me, might use it to build text-based frameworks and structured language in place of the mental imagery I simply don't have access to. None of that is outsourcing the thinking. It's constructing understanding in real time instead of waiting to retrieve it later, which is exactly the shift many neurodivergent minds already work best with.

Using AI With Integrity, Not as a Shortcut

I want to be direct about where I draw the line, because the honest worry most faculty carry about AI isn't really about cheating. It's about passivity, the fear that students will stop thinking and start outsourcing entirely. That's a legitimate concern, and it deserves a real answer, not a dismissal.

The frame that holds up is augmentation, not replacement. You use AI to extend what you're already capable of, not to skip the part where you actually have to learn something. When a student asks AI to explain a concept they're stuck on, that's augmentation. When a student asks AI to produce a response to an idea they never engaged with in the first place, that's replacement. The line isn't drawn by the technology. It's drawn by the student's intention and their willingness to do the thinking themselves.

"The beginning of wisdom is this: Get wisdom, and whatever you get, get insight." - Proverbs 4:7 (NIV)

Colorado Christian University holds that technology has to serve human flourishing under a biblical worldview. An AI model can organize information and offer structure, but it has no moral compass and no spiritual discernment of its own. It can't evaluate truth or exercise empathy. My job as an educator isn't to hand students a tool and step back. It's to teach them to use these tools with wisdom, integrity, and their own critical judgment intact.

Which brings me back to the line I closed my presentation with, because it's the one I still believe most, “This is not a tool shift. It's a redefinition of learning."

What This Means for Today's College Students

We hear some version of these same three questions regarding AI from students, from parents, and from other faculty.

Is using AI to study cheating?

Using AI as a study tool is not cheating. Asking it to explain a concept, quiz your understanding, or give feedback on an early draft sits in the same category as visiting a tutoring center or working through a problem with a study group. What crosses the line is submitting AI-generated content as your own original work when an assignment calls for yours. Check your institution's policy on generative AI, because most are more nuanced than a blanket ban.

Can AI help students who learn differently?

Yes, in concrete ways. AI tools can restate complex concepts in multiple formats, help students break large tasks into smaller sequenced steps, flag structural issues in writing, and offer support that adjusts to where a student actually is instead of where a fixed curriculum assumes they should be. For neurodivergent learners who often go without individualized academic support, that's a meaningful shift toward equitable access.

Does AI replace critical thinking?

Only if you let it. Critical thinking grows when you bring real questions into an AI conversation, push back on what comes back, and connect it to what you already know. Using AI to generate starting material and then analyzing and extending it builds deeper thinking. Using it to skip the thinking entirely hollows the process out. The difference lives entirely in how a student engages, not in whether they use the tool at all.

Make the Most of Every Mind

The story of AI in college learning is still being written, and from where I sit, as a faculty member whose own brain doesn't work the way most curricula assume, something real is happening. The benefits of AI use for diverse learners are arriving at exactly the moment higher education needs them.

For a student juggling a graduate degree with a full-time job and a family, AI can function as a study partner that doesn't clock out at 10 p.m. It helps students construct understanding in real time, cut down on cognitive friction, and put their energy where it matters most: actually learning. Used with intention and integrity, that's not a shortcut. It's wisdom in action, and it's exactly the kind of flexible approach CCU Online is built around for adult students who learn on their own schedule and in their own way.

That's the redefinition I brought to Leadership in Action, and it's the one I'm still working out, one classroom at a time.