deeper learning, critical thinking, c ...
The Old Model and Why It's Under Pressure Essays and homework were long the stalwarts of assessment. They measure knowledge, writing skills, and critical thinking. But with the presence of AI, it is now easy to produce well-written essays, finish problem sets, or even codes in minutes. That does notRead more
The Old Model and Why It’s Under Pressure
Essays and homework were long the stalwarts of assessment. They measure knowledge, writing skills, and critical thinking. But with the presence of AI, it is now easy to produce well-written essays, finish problem sets, or even codes in minutes.
That does not mean students are learning less—it’s just that the tools they use have changed. Relying on the old model without adapting is like asking students to write out multiplication tables manually once calculators are employed everywhere. It’s not getting it.
Redesigning Exams
Exams are designed to test individual knowledge. When AI is introduced, we may need to:
- Shift from recall to reasoning: Instead of “What happened in 1857?” ask “How might the outcome of the 1857 revolt have changed if modern communication technology existed?” This tests creativity and analysis, not memorization.
- Use open-book / open-AI exams: Allow students to use tools but focus on how well they apply, critique, and cross-check AI’s output. This mirrors real-life work environments where AI is available.
- In-person oral or viva testing: Requiring students to orally discuss their answers tells you whether they actually understand, even if they had AI help.
- Timed, real-world problem-solving: For math, science, or business, create scenarios that require quick, reasonable thinking—not just memorization of formulas.
Testing is less “what do you know” and more “how you think.”
Rethinking Projects & Coursework
Projects are where AI may either replace effort or spark new creativity. To keep them current:
- Process over product: Teachers need to grade the process—research notes, drafts, reflection, even the mistakes—not just the polished final product. AI can’t get away with that iterative process so easily.
- AI within the assignment: Instead of banning it, design assignments that require students to show how they’ve used AI. For example: “Employ ChatGPT to generate three possible outlines for your paper. Compare them, and explain what you retained and what you eliminated.”
- Collaborative assignments: Group work encourages skills AI finds it difficult to replicate well—negotiation, delegation, creativity in group work.
- Hands-on or practical elements: A project assignment could be an interview of grandparents, a science project would be the making of a small prototype. AI must complement but not replace lived experiences.
This reverses coursework from being outsourcing-oriented to reflection, uniqueness, and human effort.
Reframing Coursework Purposes Altogether
If AI is already capable of doing the “garden variety” work, maybe education can focus on more higher-order goals :
- Critical thinking with AI: Are students able to recognize errors, biases, or gaps in AI-generated work? That’s a skill used in the real world today.
- Authenticity and voice: AI can generate text, but it can’t replicate the lived experience, feeling, or creative individuality of a student. Assignments could emphasize personal connections or insights.
- Interdisciplinary study: Promote projects that combine math, art, history, or ethics. AI is good at doing one thing, but human learning thrives at points of convergence.
The Human Side
This’s not about “catching cheaters.” It’s about recognizing that tools evolve, but learning doesn’t. Students want to be challenged, but also supported. When it all turns into a test of whether they can outsmart AI bans, motivation falters. When, on the other hand, they see AI as just one of several tools, and the question is how creatively, critically, and personally they employ it, then education comes alive again.
Last Thought
Just as calculators revolutionized math tests, so will AI revolutionize written work. Prohibiting homework or essays is not the answer, but rather reimagining them.
The future of exams, project work, and coursework must:
- Distrust memorization more than thinking, applying, and creating.
- Welcome AI openly but insist on reflection and explanation.
- Strive for process and individuality as much as product.
- Retain the human touch—feelings, experiences, collaboration—at its center.
In short: assessments shouldn’t try to compete with AI—they should measure what only humans can uniquely do.
See less
Why Old-Fashioned Tests Come Up Short Assignments and tests were built on the model of recall for years: reciting definitions, remembering dates from history, calculating standard math problems. These were easy to grade and standardize. But the danger is self-evident: a pupil can memorize just enougRead more
Why Old-Fashioned Tests Come Up Short
Assignments and tests were built on the model of recall for years: reciting definitions, remembering dates from history, calculating standard math problems. These were easy to grade and standardize. But the danger is self-evident: a pupil can memorize just enough to get through a test but exit without true understanding. Worse, they can “forget” everything in weeks.
If we only measure what can be memorized, we are likely to reward short-term cramming instead of lifelong learning. And with all the AI around us, remembering is no longer the key skill.
What Deeper Learning Looks Like
Deeper learning is *transfer*—the capacity to apply knowledge to *new, unfamiliar* contexts. It takes the form of:
The question is: how do we measure these?
1. Open-Ended Performance Tasks
Rather than multiple-choice, give students messy problems with no single best solution.
In this way, the student is asked to synthesize information, reconcile perspectives, and justify choices—thinking, not recalling.
2. Portfolios & Iterative Work
One essay illustrates a final product, but not the learning process. Portfolios allow students to illustrate drafts, revisions, reflections, and growth.
This is all about process, not perfection—of crucial importance to creativity.
3. Real-World, Applied Assessments
Inject reality into assessment.
These exercises reveal whether students can translate theory into practice.
4. Socratic Seminars & Oral Defenses
When students explain their thought process verbally and respond to questions, it reflects depth of understanding.
If they can hold their ground in defending their argument, adapt when challenged, and expound under fire, it is a sign of actual mastery.
5 Reflection & Metacognition
Asking students to reflect on their own learning makes them more self-aware thinkers.
Example questions:
This is not right or wrong—it’s developing self-knowledge, a critical lock to lifelong learning.
6. Collaborative & Peer Assessment
Learning is a social process. Permitting students to evaluate or draw on each other’s work reveals how they think in dialogue.
Collaboration skills are harder to fake, but critically necessary for work and civic life.
The Human Side
Assessing deeper learning is more time-consuming, labor-intensive, and occasionally subjective. It’s not just a matter of grading a multiple-choice test. But it also respects students as human beings, rather than test-takers.
It tells students:
This makes testing less of a trap and more of an honest reflection of real learning.
Last Reflection
While recall tests shout, “What do you know?”, deeper tests whisper, “What can you do with what you know?” That’s all the difference in an AI age. Machines can recall facts instantly—but only humans can balance ethics, see futures, design relationships, and make sense.
The future of assessment has to be less about efficiency and more about authenticity. Because what’s on the line is not grades—it’s preparing students for a chaotic, uncertain world.
See less