When reviewing course options, seeing “writing intensive” too often leaves students feeling overwhelmed before the course even begins.
Researchers at Old Dominion University are testing how to decrease that intimidation by incorporating artificial intelligence (AI) tools at key points in the course. Their findings: more students succeeded.
“We wanted to improve two things: self-confidence in writing and the overall course pass rate,” said Elizabeth Brown, Ph.D., M.P.A., assistant professor in the Department of Health Behavior, Policy, and Management and program director for the Bachelor of Science in Public Health.
Dr. Brown has spent the past three years refining a writing-intensive undergraduate course designed to improve both student confidence and success rates. With assistance from Joint School of Public Health colleagues Maria Kronenberg, Ph.D. (MBA ’90, Ph.D. ’00), Ashlee Steeley, D.H.Sc. (D.H.Sc. ’26), and recent graduate Diana Tagbor (B.S.P.H. ’25), the course blended structured teaching methods, iterative feedback and carefully guided use of AI. The idea came to Dr. Brown after she attended a conference in 2024, where it was clear that the concern about AI and writing went far beyond her students. In response, PUBH 403W: Social and Behavioral Aspects of Public Health was redesigned around a semester-long research project where students analyze a real community health issue, identify a target population, design an intervention and ultimately evaluate whether their program would work.
While the assignment isn’t new to public health, the approach of incorporating AI into the structure of this particular class is.
“It’s about helping students tell a story with data,” Dr. Brown said. “They start with demographics and health behaviors, then move into planning — who is affected, who are the stakeholders and what can be done.”
To support students along the way, Dr. Brown incorporated assignments like online discussion posts and reflections. These early activities help students practice summarizing material, exploring public health concepts and experimenting with AI tools in a structured way.
Dr. Brown emphasizes that success is not just about grades, but about the way students learn and grow. That’s also why she and the research team asked recent Monarch graduate Diana Tagbor to assist with literature review and writing from a student perspective. Tagbor was a senior in the program at the time.
The experience of working with faculty outside of class on research was invaluable, Tagbor said, because it helped her understand what it takes to do research on a high level. She plans to attend graduate school for a Master of Public Health and eventually pursue her career in public health research and policy.
“As students, we have an idea of what we think we want to do, but being involved helps create a pathway to that career,” said Tagbor. “As students, we have to look for those pathways and opportunities to work with professors outside of class to really learn new things.”
The key, Dr. Brown said, is allowing AI, but with clear limits. Early in the course, students are encouraged to use AI to summarize readings or explore basic public health concepts with detailed instructions and guardrails.
As the course progresses, AI use becomes more restricted. By the time students are connecting theories and designing interventions, they must rely on their own critical thinking.
“When we start connecting dots and applying theories, I need the student to do that on their own,” Dr. Brown said.
By the final section, where students design an evaluation plan, AI is no longer allowed.
“There’s no shortcut there, because you have to explain and defend your decisions,” Dr. Brown said. “AI can give you the basics –– the definitions and the overview –– but the higher-level thinking, like analyzing, evaluating and applying, that’s where students grow.”
The redesigned course has shown steady student improvements. While pass rates initially hovered around 80 percent, they have climbed to more than 85 percent in only two years time.
“Students became more engaged, more reflective and more confident in their writing,” she said.
For Tagbor, it helped her understand how AI is changing research and writing from a broader perspective.
“Before the course, I wasn’t really interested in AI and I didn’t even want to touch it,” she said. “But after the course, I’m more aware of it and trying to see what I can do with it in public health.”
Dr. Brown and the team are now sharing their research with others in the hopes of inspiring more writing intensive public health courses to successfully use AI tools and decrease student intimidation. The group has published a paper on the subject in the Journal of Health Administration Education, and Dr. Brown presented her research through Global’s Research Institute for Digital Innovation in Learning during the Spring 2026 semester.
Despite the promise of AI in helping students strengthen their skills, people remain the experts, especially in a field like public health. Whether addressing chronic disease, accessibility to green space or disparities in pregnancy outcomes, real-world public health work requires empathy, communication and trust, she said.
“AI can explain theories or design a program, but it can’t replace human connection,” Dr. Brown said. “You still need to talk to people in order to understand their fears and lived experiences. AI can’t do that.”