AI Proof Your Assignments
Learn how to design assignments that reduce AI misuse and promote authentic student thinking. These AI-proofing strategies help you stay one step ahead.
Let’s accept some facts: students are using generative AI for their assignments. They’re experimenting, shortcutting, and yes, sometimes outright outsourcing. So what do you do?
Some of you may be thinking, “I’m fine. My university has AI detection software.”
Newsflash: These tools have high error rates. And you don’t want to incorrectly accuse a student of misconduct based on a shaky algorithm. That’s not just awkward—it’s potentially harmful.
You could go analog—literally. Some professors have reintroduced the blue book to prevent ChatGPT from influencing take-home essays (Entrepreneur). But banning tech won’t stop tech-savvy students.
Here’s the good news: you don’t have to out-tech AI—you just have to outsmart it. With a few strategic design tweaks (and yes, a little help from AI itself), you can create assignments that promote deeper learning and make AI misuse less appealing.
Step 1: Use AI to Audit Your Assignment for Weak Spots
Use AI to critique your assignments. You can get ChatGPT to identify gaps, vague prompts, or easy answers.
Try prompting:
Act as a student trying to use AI to complete this assignment. What would you input? What output would you get?How could I revise the prompt to encourage more critical thinking?
How can I redesign the assignment so students can't use LLMs to complete the assignment?
How can I make this assignment AI-resistant?Assignment Design Strategies
Here are some suggestions for AI-proof assignments.
Process-focused assignments: Have students submit their drafts, outlines, and reflections that demonstrate student thinking.
Oral defense or interviews: Have students explain their work and thought process in person or via video.
In-class components: Include in-class writing or coding to assess baseline skills.
Use AI in the assignment: Ask students to analyze AI outputs, critique them, or improve them — turning the tool into the subject.
Redesign Suggestions
Here are 5 suggestions on how to redesign your assignments.
1. Traditional Essay ➡️ Layered Reflection
Old: “Write a 1,500-word essay analyzing the theme of identity in Beloved.”
Redesigned: “Write a 750-word analytical essay on identity in Beloved. Then, in a separate 500-word reflection, explain:
What questions or interpretations you struggled with.
How you revised your ideas over time.
What feedback (peer or otherwise) shaped your thinking.
If you used any digital tools (AI, Grammarly, etc.), how and why?”
The reflection reveals the student’s thought process. AI struggles to fake personal growth and revision.
2. Research Paper ➡️ Annotated Research Journey
Old: “Write a research paper on climate change policy.”
Redesigned: “Submit:
A research question and hypothesis.
An annotated bibliography with personal notes on 5 sources.
A rough outline showing your structure.
A final paper.
A brief statement on your writing process, including any AI support you used.”
Process steps make it hard to hand off to an AI. Personal annotations and reflections are key.
3. Coding Assignment ➡️ Code + Rationale
Old: “Write a Python script to scrape data from a website.”
Redesigned: “Submit your Python code along with:
A 3–5 minute video walkthrough explaining what the code does, where you encountered errors, and what you learned.
A short written reflection on whether you used any AI assistance (e.g., GitHub Copilot or ChatGPT), and if so, how.”
AI can generate code, but students still have to understand and explain it — which is the real learning goal.
4. Discussion Post ➡️ Personal Application Response
Old: “Respond to this week’s reading in 300 words.”
Redesigned: “Identify one insight from this week’s reading that connects to your own experience, field of study, or current events. Explain why it matters to you. Responses should be specific, not generic.”
AI struggles with personal or contextual relevance — especially current or local examples.
5. Group Project ➡️ Tracked Contributions + Reflection
Old: “Submit a group presentation on ethical design in tech.”
Redesigned: “Each team submits:
A shared slide deck.
Individual contributions tracked via version history (e.g., Google Docs).
A short reflection from each member on what they contributed, how they collaborated, and how they handled disagreements.
(Optional) A shared AI use log: how, if at all, AI supported their brainstorming, scripting, etc.”
Process and collaboration tracking make accountability visible.
💡 Parting Thoughts
AI-proofing isn’t about playing defense—it’s about designing assignments that elevate real learning. When you treat AI as a collaborator, not a competitor, you unlock more creative, engaging, and authentic work from your students—and a lot less grading déjà vu for yourself.