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Beyond AI Detection: Creating Assessments that Promote Learning
Posted September 9, 2026
by IDLT
Beyond AI Detection: Creating Assessments that Promote Learning
Generative AI has changed the assessment landscape in higher education. Faculty are increasingly asking questions such as:
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How can I tell whether a student completed the work themselves?
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How do I assess learning when AI can generate essays, solve problems, or create content in seconds?
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How can I encourage students to use AI responsibly without letting it do the learning for them?
While there is no such thing as a completely "AI-proof" assignment, emerging research suggests that the most effective response is not to focus solely on detection. Instead, instructors can design assessments that emphasize the learning process, critical thinking, and authentic application of knowledge.
Focus on Learning, Not Just Performance
Recent research highlights what some scholars call the performance paradox. Students using AI often perform better on short-term tasks because AI can quickly generate answers, summarize information, and solve problems. However, students who rely too heavily on AI may miss the mental effort required to build lasting knowledge and critical thinking skills.
In other words, AI can improve performance without necessarily improving learning.
When designing assessments, consider what knowledge or skills students should still be able to demonstrate independently. Then create opportunities for students to engage with that material before turning to AI tools.
Move Beyond Traditional Essays
Assignments that ask students to simply summarize information or produce a final product are often easy for AI to complete.
Instead, consider assessments that require students to:
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Apply concepts to real-world situations
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Analyze local or current issues
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Create discipline-specific solutions
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Defend decisions and explain reasoning
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Reflect on their learning process
Authentic tasks connected to professional practice are often more meaningful for students and provide stronger evidence of learning.
Make the Process Visible
One of the most effective strategies is to assess not only the final product but also the work that led to it.
Examples include:
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Research notes or annotated sources
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Draft submissions
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Reflection statements
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Peer feedback activities
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Project milestones
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Recorded presentations or discussions
When students document how they arrived at a solution, instructors can better evaluate understanding and provide meaningful feedback.
Let Students Think First
Research on creativity and problem solving suggests that students develop stronger ideas when they spend time working through challenges on their own before consulting AI.
Consider asking students to:
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Brainstorm independently.
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Create an initial outline, sketch, solution, or response.
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Then use AI as a critique partner, tutor, or source of alternative perspectives.
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Reflect on how AI influenced their thinking.
This approach encourages students to use AI as a learning tool rather than a substitute for learning.
Teach Students How to Use AI Responsibly
Many students receive little guidance on what appropriate AI use looks like in an academic setting. Clear expectations can help.
Consider communicating:
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When AI use is permitted
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When AI use is restricted
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How AI contributions should be acknowledged
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What types of assistance are acceptable
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Why certain assignments require independent work
Transparency reduces confusion and helps students make informed decisions.
Small Changes Can Have a Big Impact
You do not need to redesign an entire course overnight. Simple changes such as adding reflection prompts, incorporating draft submissions, requiring students to explain their reasoning, or connecting assignments to authentic disciplinary practice can help preserve the learning opportunities that matter most.
The goal is not to eliminate AI from the classroom. The goal is to design experiences that encourage students to engage in the critical thinking, creativity, and problem-solving that AI cannot do for them.
Further Resources
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UPCEA. (2026, July 29). An AI-aware approach to online assessment.
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Bruff, D. (2026). Study hall with Flower Darby, Josh Eyler, and Regan Gurung (Intentional Teaching podcast).
