When Assistant Professor Zhe Wang first arrived at Denison as a freshly minted Ph.D. to teach statistics, she brought with her the methods she had learned in her graduate studies at the University of Connecticut. “I was so mathematical,” she said.
Then she began teaching a highly technical topic to undergraduate students from a range of majors, and she realized things needed to change. “I started doing project-based learning, using stories that illustrate how we use statistics in real life.”
Wang also moved from sharing knowledge to teaching how to learn. The distinction may be subtle, but it’s a critical shift that has made challenging material far more accessible to her students.
“For example, instead of teaching how to run a new model, I teach them how to learn to run a new model,” said Wang, who has just been recognized for her transformative teaching with the Early Career Undergraduate Impact Award for junior faculty, given by her peers at Mu Sigma Rho, the National Statistics Honorary Society.
Data analytics major Jordyn Maurer ’26 says that approach works well for her. In a 300-level advanced predictive methods class, which Maurer says is the “first step into learning what more we can do with D.A.,” Maurer said Wang has shifted the class away from what could have been a “big roadblock” to higher levels of data analytics.
“She takes a complicated subject and breaks it down until it makes sense,” said Maurer, adding that Wang “supports her students in a way that guides them but doesn’t spoon feed them the answers.”
Wang mentored Maurer on her senior capstone research project about predicting injuries in sport. “It’s not a very well-researched field, and the methods that were available were way outside my realm,” said Maurer. “I had no idea where to start.”
So Wang did her own research into the question and pointed Maurer to several options.
“As students, we can tell if a professor cares about you and your success, and she is absolutely one of those professors,” said Maurer.
Chanel Anderson ’26, a double major in data analytics and economics, said Wang is “insanely invested in her students’ learning” and blocks off time to talk with them about their progress.
“She asks questions about you, wants to know about your interests, then she’ll do some research and suggest scholarships, programs, and grad schools.”
Wang is also “effortlessly funny,” said Anderson. “We can be tired, and then she’ll make a joke that just invigorates us. And because it’s so unexpected, it’s even better.”
Associate Professor Anthony Bonifonte said her impacts can be seen across Denison’s data analytics curriculum, “from the introductory course through the capstone seminar.”
“In our introductory course, which has no mathematics requirements, she teaches the intuition behind statistical testing and how to conduct and interpret the tests with statistical software — without focusing on the mathematical details,” he said.
“By contrast, in her advanced methods and elective sequential analysis course, she teaches more mathematical details.”
Associate Professor Sarah Supp has observed and been impressed by Wang’s teaching. “She identifies hands-on activities that students can do to make statistical concepts concrete and fun,” said Supp.
”I’ve seen the way this method of teaching can help students move past their own feelings of impostor syndrome, start to get more excited about learning statistics, and gain confidence,” she said.
Wang says she’s benefited immensely from talking with her colleagues. “At Denison, data analytics is a very interdisciplinary program. We teach from different perspectives, such as biology, economics, and computer science.”
“We go to faculty lunches, talk about our materials, and share our teaching methods,” she said. “Everyone is so friendly.”
Wang’s students have earned recognition outside the classroom, including third place in the 2025 ASA Undergraduate Statistics Research Project Competition and first place in the 2025 ASA Columbus Chapter Scientific Communication Video Contest.
Her students have also presented their work at academic conferences, including Women in Statistics and Data Science, the Nebraska Conference for Undergraduate Women in Mathematics, the Annual Ohio State Sports Analytics Conference, and the International Workshop in Sequential Methodologies.
Anderson said that Wang is “just a good person to be around.”
“She brings a human aspect to something that’s so technical,” said Anderson. “I’m glad she’s getting the recognition she deserves.”
