Is AI going to make us better educators?
How artificial intelligence could push educators back to the fundamentals of meaningful learning
Recent discussions about AI in higher education have centered on an “assessment crisis,” where AI enables students to produce polished products without necessarily engaging in meaningful learning. While this is something important that we need to contend with, perhaps AI isn’t creating a crisis. Perhaps, it’s revealing one that has existed all along.
AI is compelling educators to reconsider what it truly means to know something. I believe this reckoning can redirect us to the essential principles of effective learning design.
AI is not creating an assessment crisis; it is exposing weaknesses that already existed in how we design learning and evaluate understanding.
While it can be debated what the purpose and uses of higher education are, for the goals of this post, I subscribe to the belief that a core purpose of the university is to prepare students for flexible adaptation to new problems and settings. In essence, institutions serve as engines of human capital. This inherently assumes that a graduate brings a level of competence in a knowledge base that they can expertly transfer to various settings and problems. How, then, do we effectively assess a student’s level of understanding (i.e., knowledge and skills) and their ability to transfer that understanding before graduation?
Too often, for myriad reasons, and despite knowing better, we educators and learning experience designers end up relying on a single snapshot of evaluation - asking students to recall, recognize, or “plug in” isolated, discrete bits of knowledge or skill, one at a time. But the advent of AI is forcing us to move away from this approach, pushing us towards the design of more meaningful forms of assessment.
What will authentic assessments look like in AI-rich classrooms?
When designed well, assessment becomes less like a single snapshot of a student’s work and more like a “scrapbook” of mementos, creating a collection of moments that together create a vivid picture of a learner’s growth [1]. This “scrapbook” might include checks of understanding (such as oral questions, observations, dialogues); traditional quizzes, tests, and open-ended prompts; and performance tasks and projects. Ideally, they’ll vary in scope (from simple to complex), time frame (from short- to long-term), setting (from decontextualized to authentic contexts), and structure (from highly directive to unstructured). Moreover, effective assessment utilizes formative feedback, not just summative. Formative assessment is like giving students a GPS; when instructed on how to properly use the feedback, the student is put in the driver’s seat and can effectively track their progress towards their final destination. Students need the tools (i.e., feedback from formative assessment) to learn how to assess the demands of a task, evaluate their own knowledge and skills, plan their approach, monitor their progress, and adjust their strategies as needed.
If you are struggling with where to begin, you’re not alone. I find a great place to start is revisiting the following guiding questions:
“Given the goals, what performance evidence signifies that they have been met?”
“What evidence do we need to find hallmarks of our goals, including that of understanding?”
Once the appropriate task or performance is identified, “What specific characteristics in student responses, products, or performances should we examine to determine the extent to which the desired results were achieved?” This is where criteria, rubrics, and exemplars come into play.
“Does the proposed evidence enable us to infer a student’s knowledge, skill, or understanding?”
Keep in mind that traditional quizzes and tests (e.g., paper and pencil, selected-response, constructed response) are really effective at assessing knowledge that is “worth being familiar with” and even “important to know and do”. But this is what is heavily relied on in classrooms now, and what is easily faked with AI. If you really want to assess for deep understanding, performance tasks that are complex, open-ended, and authentic will be the answer (meaning the assessment is realistically contextualized; requires judgment and innovation; asks the student to “do” the subject; replicates key challenging situations in which adults in the field are truly tested; allows for appropriate opportunities to rehearse, practice, consult resources, and get feedback then refine and repeat the process over again).
The Paradox of AI in Education
Ironically, the rise of AI may bring education closer to its original purpose. By making superficial assessments easier to game, AI pushes educators toward designing experiences that prioritize understanding over output, process over product, and growth over performance.
AI may not replace educators. Instead, it may demand that we become better ones by forcing us to design for learning that cannot be faked.
[1] Wiggins, G. P., & McTighe, J. (2005). Understanding by design (2nd ed.). Pearson.
This really resonates. As the founder of a hybrid learning centre, we’re seeing this shift very clearly. AI isn’t going away, and reacting to it with fear would be a mistake. In many ways it’s becoming an incredibly useful tool for helping students plan, expand and structure their thinking.
At the same time, it has forced us to rethink what “real knowing” actually looks like. Interestingly, we’ve found ourselves returning to some very old-school methods to ensure authenticity — handwritten revision notes (using the Cornell method), fast handwritten narrative writing, discussion-based tasks and other activities where students must process ideas in real time.
What’s been surprising is how refreshing this has been. Handwriting — something I once thought might disappear — is having a revival, and the research around how it activates multiple areas of the brain compared to typing is hard to ignore.
For us the answer isn’t rejecting AI, but integrating it thoughtfully while preserving the kinds of learning experiences that require genuine thinking and personal ownership.