AI Isn’t the Enemy: Teaching Critical Thinking in the Age of ChatGPT

AI is already in the classroom.

Students are using tools like ChatGPT to summarize readings, generate ideas, and draft responses. Some institutions are trying to restrict it. Others are experimenting with it. Most are still figuring out what to do.

But across very different institutions, a similar realization is emerging: AI is not the problem. The problem is how students engage with it.

At Missouri Southern State University, the University of Oklahoma, and SUNY New Paltz, faculty are taking a different approach. Instead of banning AI or ignoring it, they are redesigning learning around it.

Tools like Hypothesis are playing a central role in this shift. By using social annotation, instructors are turning reading into an active, visible process where students analyze, question, and respond to both course content and AI-generated outputs in context.

You can see how institutions are implementing this approach here: https://web.hypothes.is/case-studies/

Why Is AI So Challenging for Higher Education?

AI has entered the classroom faster than institutions can adapt.

Faculty are navigating unclear policies. Students are unsure what is allowed. And assignments designed for a pre-AI world no longer function the same way.

“Reading rhetorically—as if engaging with another human being—is vital at the college level, but students find it challenging,” says Nick LoLordo, Senior Lecturer at the University of Oklahoma.

AI-generated summaries make this even easier to avoid.

At SUNY New Paltz, Rachel Rigolino saw a similar pattern. Students either overused AI or avoided it entirely out of fear.

“Transparency and thoughtful integration are key,” she explains. “I have revised all of my major assignments to address the very real fact that higher education faculty now teach in an AI-inhabited landscape.”

Without structure, both students and instructors are left experimenting in isolation.

What Happens When AI Is Integrated Instead of Avoided?

Instead of treating AI as a shortcut, these instructors turned it into something students must analyze.

At Missouri Southern State University, Diana Fordham asks students to generate responses with AI and then evaluate them for bias, inaccuracy, and oversimplification.

At SUNY New Paltz, students annotate AI-generated outputs directly, identifying gaps and questioning assumptions.

This changes the role of AI entirely.

It becomes a starting point for thinking, not a replacement for it.

And this is where social annotation becomes critical.

Instead of evaluating AI outputs in isolation, students engage with them directly in the text. They highlight claims, question reasoning, and respond to each other in context.

Evaluation becomes visible.

How Does Social Annotation Change Student Engagement?

As AI makes it easier to move quickly, instructors are using social annotation to slow students down.

“Hypothesis allows me to suggest the value of slow reading,” says Nick LoLordo. “It encourages close reading and resists the productivity-driven learning that big tech promotes.”

That shift matters.

At MSSU, Diana Fordham saw a direct impact:

“They’re engaging with the material directly—and forming their own interpretations—before ever turning to AI.”

Students are no longer skipping the reading. They are interacting with it.

At SUNY New Paltz, replacing discussion boards with annotation changed participation immediately.

“Students jump right in and are more engaged with timely, relevant content,” says Rachel Rigolino.

Because responses are tied to specific passages, engagement becomes both deeper and easier to assess.

Read the full case study here: https://web.hypothes.is/case-studies/generative-ai-and-social-annotation/

What Results Are Faculty Seeing?

Across all three institutions, the results are consistent.

Students are:

• Reading more consistently
• Engaging more actively
• Thinking more critically about AI outputs
• Participating more meaningfully in class

At MSSU, reading completion and participation increased.

At the University of Oklahoma, students used AI as a starting point—but refined and challenged it through structured annotation.

At SUNY New Paltz, students not only improved comprehension, but also learned how to evaluate AI critically—an essential skill beyond the classroom.

Why Does This Approach Work?

Because it shifts the focus from output to process.

Instead of asking:
Did the student complete the assignment

It asks:
How did the student think through the material

Annotation-based assignments make that thinking visible.

They require students to:

• Engage directly with texts
• Question AI-generated content
• Justify their reasoning
• Learn from peer perspectives

This is not about controlling AI.

It is about teaching students how to think in a world where AI exists.

You can explore a structured version of this approach here: https://web.hypothes.is/ai-literacy/

Frequently Asked Questions

Do instructors need to ban AI to maintain academic integrity?
No. Many instructors are finding that integrating AI into assignments—while requiring evaluation and verification—is more effective than banning it.

How does social annotation help with AI literacy?
Social annotation requires students to engage directly with texts, question claims, and respond to others in context, making their thinking visible.

Can this approach work across disciplines?
Yes. Faculty across humanities, social sciences, and professional programs are using annotation to support critical thinking and AI evaluation.

Does this increase student engagement?
Yes. When students interact with content in context, participation becomes more consistent and meaningful.

Conclusion

AI is not going away.

The question is not whether students will use it. It is whether they will understand it.

At MSSU, the University of Oklahoma, and SUNY New Paltz, faculty are showing what that looks like in practice.

They are not removing AI from the classroom.
They are teaching students how to question it.

And in doing so, they are building something more important than compliance.

They are building critical thinking.

Explore related blogs:

How Hypothesis Helps Preserve Academic Integrity in the Age of AI
Learn how making student thinking visible supports academic integrity without relying on detection tools.
https://web.hypothes.is/blog/how-hypothesis-helps-preserve-academic-integrity-in-the-age-of-ai/

Combating AI-Generated Essays with Collaborative Annotation Assignments
See how annotation-based assignments reduce AI misuse by requiring contextual, visible engagement with course materials.
https://web.hypothes.is/blog/combating-ai-generated-essays-with-collaborative-annotation-assignments/

Human-Centered Learning in the Age of AI
Explore why focusing on process, engagement, and visible thinking is key to learning in an AI-driven environment.
https://web.hypothes.is/blog/human-centered-learning-in-the-age-of-ai/