AI in the Classroom is a series highlighting the experiences of Ohio State faculty who are using AI in their teaching — what’s working, what’s still unfolding and where it’s headed next.
Nicholas Denton is a senior lecturer in the College of Pharmacy. He directs the Pharmaceutical Sciences Teaching Laboratory and the lab courses offered at the College of Pharmacy, in addition to instructing survey courses in pharmaceutical science research and cancer research. As a Senior Affiliate to the Michael V. Drake Institute for Teaching and Learning, Denton provides professional development to faculty and trainees on education research and evidence-based teaching practices.
What made you want to start using AI in your course?
I attended a few workshops where educators demonstrated the potential for generative AI to enhance learning, pharmacy practice and pharmaceutical research. They also showed how easy it is for people new to AI to accept outputs that are factually incorrect or incomplete. With more students using generative AI in their learning, I wanted to provide learning opportunities to help them use AI tools effectively and ethically in class.
Can you share specifics on how you have students use AI?
I have offered extra credit for students to create mnemonic parody songs about the mechanisms for the different drugs we were investigating in our pharmacology lab section. I showed students how to prompt Copilot to generate lyrics to submit on a discussion board and invited them to submit a performance for extra credit and the chance to compete in Pharmacologist Idol. Before the final exam, the class played the performances and upvoted their favorite for pharmacology-related prizes.
For teaching students strategic searching for research articles, I demonstrated that using Copilot and AI research tools like literature mapping, as well as traditional searches, resulted in very different articles around a scholarly conversation. We emphasized going beyond the top 2–3 results to find seminal papers on a given research topic.
What were you hoping students would get out of AI?
Aside from completing the immediate tasks of generating useful learning mnemonics and improving their drug mechanism recall, I hoped students would gain competencies in what AI is and how to think critically about the AI tools they will run into in their future careers. This approach supports Ohio State’s AI Fluency learning outcomes, including helping students gain AI technical understanding, critical evaluation, ethical consideration and discipline-based applications.
What’s the most important thing you’ve learned since starting to teach with AI? Have there been any surprises?
I’ve learned how important iteration and fact checking are when engaging with AI-generated outputs. Some outputs can even be factually correct but incomplete. For example, when students generated learning mnemonics, the outputs often included the most commonly used application for a drug but neglected other targets that could result in side effects that weren’t clear in the output.
Is there a moment when you realized AI was actually working better than you expected in your class? What happened?
I was really surprised by research tools that make it much quicker to find the most relevant research papers for a question. I would otherwise spend hours doing this by optimizing search queries and reading to page 5 of the search results.
Some people are nervous about AI, thinking it might hold students back from developing critical thinking or creativity. What’s your take on that?
I’m personally on board with students using AI as they would in the workplace. I emphasize demonstrating reflective iteration and SIFT (Stop, Investigate the source, Find better coverage, Trace claims to the original context) fact-checking principles as an AI-audit along with the final draft submission. That way, students are aware that they are responsible for submitting factually correct and complete assignments.
Will embedding AI in the curriculum actually help students prepare for their careers after graduation?
Absolutely. AI isn't going away, and there are a number of general and discipline-based AI tools in healthcare that students will need to be aware of at the very least, preferably with the knowledge to engage with these tools critically and ethically. In a pharmacy careers course, I've introduced students to Copilot simulated interviews with potential employers and how to reverse engineer a professional development plan to acquire desired skills and experience for a pharmaceutical sciences job the students are interested in.