Diana Fordham
Instructional Designer and Lecturer in Social Sciences, MSSU
Nick LoLordo
Senior Lecturer, Honors College, University of Oklahoma
Rachel Rigolino
Professor of English: Writing and Literature, SUNY New Paltz
AI Isn’t the Enemy: Teaching Critical Thinking in the Age of ChatGPT
Faculty across higher education are facing a new challenge: how to maintain student engagement and academic integrity in the age of AI tools like ChatGPT. Institutions are taking varied approaches: some prohibit AI use in the classroom, others embrace it, and many are cautiously searching for a practical path forward. At Missouri Southern State University, the University of Oklahoma and SUNY New Paltz, faculty are utilizing Hypothesis alongisde to AI tools to promote critical thinking, ethical technology use, and deeper engagement with course content.
This case study explores how social annotation is helping educators strike the right balance, leveraging AI without losing the human element of learning.
Challenges
AI has rapidly entered the classroom, but institutions have struggled to keep pace. Faculty are caught between unclear policies, student anxiety, and the risk of academic dishonesty. The result is an uneven landscape where students lack consistent guidance on how to use AI tools effectively, and ethically.
“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, Honors College at the University of Oklahoma. The availability of AI-generated summaries only deepens this challenge, making it easier for students to avoid direct engagement with course texts.
At Missouri Southern State University, Diana Fordham observed that while K-12 educators are embracing AI, higher education often resists it, leaving faculty unsure how to adapt. SUNY New Paltz’s Rachel Rigolino echoed this concern, noting that students frequently misuse AI or avoid it altogether for fear of plagiarism detection. In addition to addressing student AI use, instructors should reconsider their assignments and assessments.
Without clear frameworks, and a lack of consensus about how and when students might use AI tools, faculty and students are left navigating AI in isolation, each classroom becoming its own lab for experimentation– full of potential, but lacking structure. However, many instructors are reluctant to allow AI use for fear that students will offload the work of learning.
“Transparency and thoughtful integration are key. 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. “
– Rachel Rigolino, Professor of English: Writing and Literature — SUNY New Paltz
Solution
Rather than ban AI or ignore it, faculty at these institutions turned to Hypothesis as a way not only to discourage over-reliance on AI tools but to challenge students to engage with deep, critical reflection on what AI produces or generates. By combining social annotation with structured assignments, they helped students become more critical readers, more thoughtful users of technology, and more confident contributors to academic conversations.
These instructors didn’t just adopt AI: they built frameworks that required students to analyze it, challenge it and understand its limitations. Hypothesis became the foundation for that work, anchoring real-time conversations directly in course texts.
Leveraging AI Thoughtfully
At Missouri Southern State University, Diana Fordham is teaching future educators how to use AI as an instructional partner—not a shortcut. In her graduate course on educational technology, students generate responses using ChatGPT, then evaluate the results for bias, inaccuracy, and oversimplification. “I’m teaching educators how to use AI as an assistant to engage their students better,” she explained. By embedding AI critique into coursework, she’s modeling transparent, ethical use of emerging tools.
At SUNY New Paltz, Rachel Rigolino takes a similar approach, pairing AI with Hypothesis to deepen student analysis. In one assignment, students use AI to generate a SWOT analysis for a fictional business, then annotate the output directly in Hypothesis to critique its gaps. “This approach helps students see AI as a tool, not a crutch,” she said. Students also compare AI-generated summaries to original texts, strengthening their reading comprehension and skepticism. She feels that learning how to evaluate and edit AI-generated material will be a crucial skill in the professional lives of her business majors.
In both classrooms, AI is not a replacement for thinking—it’s a catalyst for it. Hypothesis grounds these conversations in the text itself, prompting students to slow down, respond, and reflect together.
Fostering Engagement Through Hypothesis
As students gain easier access to AI-generated summaries, faculty are using Hypothesis to help them reconnect with the original text. Social annotation encourages students to develop independent thought, and makes it harder to substitute AI-generated content for real comprehension.
“Hypothesis allows me to suggest the value of slow reading. It encourages close reading and resists the productivity-driven learning that big tech promotes.”
– Nick LoLordo, Senior Lecturer, Honors College at the University of Oklahoma
At MSSU, Diana Fordham has seen grades improve as students use Hypothesis to read actively and show up better prepared for class.
“They’re engaging with the material directly—and forming their own interpretations—before ever turning to AI.”
– Diana Fordham, Instructional Designer and Lecturer in Social Sciences, MSSU
At SUNY New Paltz, Rachel Rigolino replaced static discussion boards with Hypothesis and saw an immediate change: “Students jump right in and are more engaged with timely, relevant content.” Because Hypothesis requires students to anchor their comments in specific passages, it creates a level of accountability—and depth—that’s difficult for AI to fake.
Results
Across all three institutions, faculty are seeing measurable improvements in student engagement, comprehension, and AI literacy—not by banning AI, but by integrating it thoughtfully alongside Hypothesis.
At Missouri Southern State University, Diana Fordham saw a sharp rise in reading completion and class participation. “Before Hypothesis, some students didn’t even buy the textbook,” she said. Now, students come to class having read and annotated key sections—and it’s showing in their grades. Just as importantly, faculty attitudes toward AI are shifting. Through modeling and professional development, instructors are learning how to guide students in ethical AI use without sacrificing rigor.
At the University of Oklahoma, Nick LoLordo uses Hypothesis to push back against surface-level AI writing. Structured assignments allow students to use AI as a starting point—but refine, revise, and respond through annotation. “It’s not just about banning shortcuts,” he said. “It’s about helping students think more critically about the tools they’re using.”
At SUNY New Paltz, Rachel Rigolino’s students now analyze AI-generated content using Hypothesis—critiquing what AI gets right and where it falls short. This practice has improved reading comprehension, and also led to an unexpected benefit for Rigolino’s students: they are no longer required to purchase expensive textbooks for her courses. Because she now uses OCR PDF files for social annotating, Rigolino has been able to create her own course reader by combining the PDFs. By adopting Open Educational Resources and pairing them with Hypothesis, Rigolino created space for timely, real-world content without sacrificing student engagement. “They jump right into the reading from day one of the course,” she said. “And they’re thinking more deeply.”
Bridging AI and Active Learning
These case studies show that AI doesn’t have to lower standards or replace critical thinking. When paired with Hypothesis and structured assignments, AI becomes a tool for building deeper engagement—not shortcutting it.
By guiding students to question, annotate, and refine AI-generated content, educators are reinforcing digital literacy and academic integrity—skills that will matter far beyond the classroom.
Conclusion
AI is no longer a future trend—it’s a present reality shaping how students think, read, and write. The question isn’t whether AI will change education. It already has. The real question is whether institutions will respond with intention—or fall behind.
At MSSU, the University of Oklahoma, and SUNY New Paltz, faculty aren’t banning AI or ignoring it. They’re guiding students to engage with it critically, transparently, and ethically. With Hypothesis as a foundation, they’re showing students how to read closely, ask better questions, and contribute meaningfully to academic conversations—even in an AI-saturated world.
This is what AI readiness looks like in practice. Not a blanket policy. Not another digital tool. But a commitment to learning that’s human-centered, evidence-driven, and built to last.
About Hypothesis
Hypothesis is a social annotation platform that helps students read more deeply, think more critically, and engage more actively with course materials. Trusted by over 400 colleges and universities, Hypothesis brings collaborative reading into the digital age—supporting academic integrity, building digital literacy, and preparing students to learn in a world shaped by AI.
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