One of the best parts of teaching is getting to know students as individuals. Good teaching depends on noticing where each student is stuck and offering feedback that helps them move forward. In real classrooms, though, that ideal is hard to sustain. When one instructor is responsible for dozens of students (or more), time and attention run thin.
This is among the reasons why AI has started to attract so much interest as an instructional aid. Many people talk about it as a tool for efficiency, and that is part of the story. Still, the deeper opportunity is not simply to do work faster but also make more room for the human side of teaching.
I find it helpful to think about pedagogical personalization as a triangle made up of students, instructors, and AI. AI can support student reflection, lighten instructor workload, and help students and instructors connect in meaningful ways. When those three relationships work together, teaching can become more personal, sustainable, and humane.
The Mirror Between Student and AI
It is easy to see why instructors worry that AI could make students passive learners. When it is used only to generate quick answers, that risk becomes reality. But when oriented toward prompting reflection, AI can help students see their own learning more clearly.
Instructors can strengthen this process with small design choices. After using an AI writing tutor on a draft, for example, students might answer three short questions:
- What pattern did the AI notice?
- Do you agree with that feedback?
- What will you try next?
This type of reflection encourages students to think about feedback instead of simply accepting it.
Or consider a student working through physics problems and feeling discouraged after several mistakes. They may start to think they are simply bad at physics. An AI tool, however, might detect a more specific pattern: Their conceptual setup is strong, but they repeatedly make small unit-conversion errors. That kind of feedback can shift what Carol Dweck, in her book Mindset: The New Psychology of Success, calls a fixed mindset into a growth one, where failure becomes a concrete habit to improve.
This reflection matters because students often struggle to diagnose the flaws in their own learning, and research has found that metacognitive activities can improve how students understand their learning process. AI can make hidden patterns easier to notice by showing students where they are confused, where their confidence is justified, and where they should pay extra attention.
The GPS for the Instructor
AI can also help instructors take care of repetitive work that consumes time without adding much human value. The 80/20 rule suggests that a small share of effort often produces most of what is noticed or valued. Yet instructors spend significant time sorting student responses, scanning for patterns, and summarizing themes. These tasks are useful, but they can pull attention away from the more relational and judgment-based parts of teaching.
An interesting way to think about AI is as a GPS for the instructor. A GPS does not drive the car. It reads the road ahead and suggests possible routes. The driver still decides where to go and which turn to take. AI can play a similar role in teaching.
Visit our resource library to read Notre Dame’s Guidance on the Use of Artificial Intelligence for Assessment. Please note instructors should use only tools approved by the University for handling student work.
For example, an instructor may collect weekly reflection journals from a large class. Reading each entry carefully is valuable, especially when students express confusion or uncertainty. Still, it can take hours to identify who is struggling, which concepts are unclear, and what themes are emerging. AI can assist with organizing those responses, highlighting common concerns, and flagging students who may need extra support.
With that clearer starting point, the instructor can decide how to respond. The next class might clarify a common misunderstanding, or a discouraged student might receive a quick check-in. These choices still depend on the instructor’s judgment, knowledge of the students, and understanding of the course context. In this sense, AI works best as a quiet GPS: It helps instructors see possible routes while they remain in control.
The Bridge Between Students and Instructors
During a busy semester, instructors are routinely buried under grading, emails, planning, and administration. Even when they care deeply about students, they may have little space left for thoughtful interaction. In these moments, AI can quietly strengthen the relationship between students and instructors.
An instructor who no longer spends the evening sorting through journals may have time to speak with a struggling student before class. A discussion can be shaped around the questions students are actually wrestling with, and quieter students become easier to notice.
In practice, personalization often shows up in small but meaningful moments such as a timely conversation, a thoughtful word of encouragement, or a bit of flexibility during a difficult week. What students often remember most is the sense that someone noticed what they were going through and responded with care.
Personalization is Still a Human Practice
AI can support teaching in powerful ways, but the heart of personalization remains human. Students still need to feel understood, and instructors still need to exercise judgment.
What AI can offer is breathing room. It can help students reflect more clearly on their own learning, and it can help instructors notice patterns that would otherwise take hours to uncover. Most importantly, it can free attention for the human interactions that give teaching its meaning.
Used this way, AI does not pull teaching away from people. It helps bring people back to the center of it.
Gelei Xu is a graduate associate at Notre Dame Learning’s Kaneb Center for Teaching Excellence and is pursuing a Ph.D. in the University’s Department of Computer Science and Engineering.
Originally published by at learning.nd.edu on July 17, 2026.