Higher education presents

The AI Midway

Higher Ed's Lost Carnival

The fair closed years ago, but the rides still run. Each attraction is one of higher education's answers to AI — improvised, contradictory, occasionally on fire. Walk the midway. Play the games. Decide for yourself.

🎟 Take a ticket — enter the midway

Every carnival has an exit

You leave through the mouth — what will you take with you?

Text navigation

Every attraction works with keyboard and screen reader. Use these if the films are difficult to navigate.

About this experience

The AI Midway is a ruined carnival where each attraction is a failure mode in higher education's response to AI: contradictory policy, unreliable detection, vendor hype, brittle assessment, and unverified citations. Each game takes 3–8 minutes and ends with a reflection you can export. Everything is stored only in your browser — nothing is sent anywhere.

Films are ambient loops with optional sound — use the 🔇 ambience toggle. Motion can be switched off with the 🎞 toggle; the site also honors your system's reduced-motion setting.

The Policy Wheel

Round and round the policy goes — five revolutions, zero forward motion.

Clarity 50

Fairness 50

Learning 50

✒ Reflection at the exit gate

What makes an AI policy usable for students and instructors? Where does your current institutional policy feel clear, vague, or contradictory?

Tag:

The Mirror Maze

Every mirror claims to detect the truth. Can you find the way out of unreliable AI detection?

The case file

A sophomore submits a polished literacy narrative. A detection tool flags it “97% AI-generated.” The student is multilingual, says she used Grammarly, and wrote the essay across two weeks in Google Docs. Inspect the mirrors, then choose your response.

✒ Reflection at the exit door

What evidence would you need before making a judgment about student AI use? What response protects both academic integrity and student dignity?

Tag:

EdTech Shady Shack

The neon still works. So does the sales pitch. Step right up — trust us.

✒ Reflection at checkout

What questions should faculty and institutions ask before adopting an AI edtech tool? Who benefits, who pays, and who carries the risk?

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The Assessment Carousel

The horses go in circles and so does the assignment. Redesign the ride, or keep spinning.

The brittle assignment

“Final essay. Five pages. Submitted once, at the end. Grade = 100% product.” In the age of AI, this ride tells you nothing about who did the thinking. Choose 4 painted panels to rebuild the carousel so learning is visible.

✒ Reflection on solid ground

How can an assignment make thinking, process, and judgment visible without turning the course into surveillance?

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Citation Shootout

The last stallkeeper still runs one game: knock down the false sources before they retreat.

✒ Reflection at the prize counter

What verification moves should students learn before they cite, quote, or rely on AI-assisted research?

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Reflection Journal

Your carnival inspection ledger. Stored only in this browser — export before you leave.

Inspection Ledger

Resource Library

The quiet tent at the edge of the midway. Context for when you want more than games.

🧭 AI policy examples — what usable looks like

Course-level clarity: a syllabus statement that names permitted uses (brainstorming, feedback), prohibited uses (submitting unedited output), and the disclosure expected.
Tiered permissions: "AI-free," "AI-assisted with disclosure," and "AI-integrated" assignment labels, so expectations change per task rather than per rumor.
One source of truth: institutions that publish a single, findable page defining encouraged, tolerated, and prohibited uses — instead of scattering contradictions across offices.

🏷 AI disclosure template

AI Disclosure
Tool(s) used: ______________________
What I used it for: (brainstorming / outlining / feedback on a draft / editing / other)
What I did myself: ______________________
What changed because of the AI's input: ______________________
One thing I double-checked or verified: ______________________

Disclosure works when it is a routine label, not a confession. Give students examples of good disclosures before asking for one.

🪞 AI detection cautions

Detection scores are probabilities without evidence — they cannot show process, intent, or authorship.
False positives fall hardest on multilingual writers and formulaic academic prose.
Prefer process evidence (draft history, notes, conferences) and non-accusatory conversations over scores.
If a case can't survive without the detector's number, it isn't a case yet.

🎠 Assessment redesign strategies

Grade process artifacts alongside products: proposals, annotated drafts, revision memos.
Add metacognitive reflection: "What did you decide, and why?"
Use oral defenses or conferences for high-stakes work.
Design tasks anchored in local, specific, current material that generic output can't fake well.
Make AI use discussable: a disclosure label costs less than a surveillance apparatus.

🧪 Vendor evaluation questions

What data do you collect, where is it stored, and how long do you keep it?
Was the product validated with students like ours? Can we see the study?
What happens to our content and student work if we cancel?
Who does the extra labor when the tool is wrong?
Is it accessible — screen readers, captions, low bandwidth?
Who benefits, who pays, and who carries the risk?

Exit & Next Steps

You leave through the clown's mouth. The gate converts play into action.

🎟 Your visit

✍ Three takeaways

Name three things you're taking with you out of the midway.

🧭 Action plan

What is one concrete thing you will change, propose, or try in the next month?

💬 Discussion questions for class

Which attraction felt closest to your own institution — and why?
Where does responsibility for AI policy actually live on your campus? Where should it?
What would it take to replace one detection-based workflow with a process-based one?
Which vendor promise would your campus be most tempted by, and what question would puncture it?

📦 Export your journal

Exports include your reflections, takeaways, and action plan.