Teaching Students to Read Critically in an AI-Driven World
Reading in the Age of Shortcuts
Generative AI tools like ChatGPT have transformed how students engage with information. With a few prompts, learners can access summaries, interpretations, even arguments—instantly. But this speed comes at a cost. When students rely on AI to bypass reading, they lose more than time—they lose depth, context, and connection.
Faculty across higher education are asking a pressing question: How do we preserve critical reading in a world designed for shortcuts? The answer, increasingly, is to slow things down—and make the process of reading visible.
That’s where Hypothesis comes in.
1. Why Critical Reading Still Matters
Reading isn’t just a box to check. It’s the foundation of critical thinking, academic success, and lifelong digital literacy. When students truly engage with texts—pausing to question, interpret, and connect ideas—they develop the skills needed to thrive across disciplines and careers.
But AI-generated summaries can flatten nuance, skip key details, and discourage curiosity. Instructors must be intentional about building assignments that resist passivity and reward authentic engagement.
2. Using Annotation to Slow Down and Think Deeply
Social annotation offers one of the most effective ways to reclaim the reading process. With Hypothesis, students read actively—line by line—leaving comments, raising questions, and responding to one another directly in the margins.
Faculty can scaffold this work by embedding prompts or notes into texts, modeling critical engagement along the way.
“Hypothesis allows me to suggest the value of slow reading,”
— Nick LoLordo, University of Oklahoma
Annotations don’t just show what students know—they show how students think. Confusion, insight, connection—it’s all captured in real time, creating a feedback loop between student and instructor that AI simply can’t replicate.
3. Making AI Part of the Learning Process
Rather than banning AI, some faculty are turning it into the very subject of inquiry. With Hypothesis, students can annotate AI-generated content—identifying what’s missing, what’s misleading, and what needs refinement.
At SUNY New Paltz, Professor Rachel Rigolino asks students to generate SWOT analyses using AI, then annotate the results to surface gaps in logic or depth.
“This approach helps students see AI as a tool, not a crutch,”
— Rachel Rigolino, SUNY New Paltz
By comparing AI-generated summaries to the original text, students build their own interpretations—and begin to recognize the limitations of artificial intelligence.
4. Scaffolding Digital Literacy and Skepticism
As AI-generated content becomes more common, students need more than reading skills—they need discernment. What’s missing in this summary? Where’s the nuance? What’s biased or overly simplistic?
Annotation helps students slow down and ask those questions. In classrooms at Missouri Southern State University, Diana Fordham trains future educators to generate ChatGPT responses, then annotate them for bias and inaccuracy.
Through assignments like these, students learn to navigate complex information ecosystems with curiosity and skepticism—two skills that AI can’t replace.
Want to try it in your course? Check out our assignment examples that integrate AI critique →
Conclusion: Preparing Students for a Complex Information Landscape
Students don’t need another summary—they need to learn how to read. Critically. Curiously. Skeptically. In a world shaped by instant AI output, that’s what sets learners apart.
By encouraging students to annotate, reflect, and converse, Hypothesis helps faculty rebuild the habit of close reading. It’s not just about avoiding AI misuse—it’s about developing authentic intellectual habits in a digital-first world.
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