My teaching centers on quantitative reasoning as a practice of interpretation, participation, and critical inquiry. Rather than treating mathematics and statistics as purely technical skills, I help students use numbers, graphs, and data to understand social life, inequality, public information, and human experience.
Quantitative Reasoning I & II
I have taught Quantitative Reasoning I and II at The New School for approximately ten semesters, primarily as instructor of record.
Since 2022, my course and instructor evaluations have generally remained around 4.5/5. Over the past two years, several sections have received overall learning experience ratings of approximately 4.8/5.
Interpretation, Participation, and Critical Inquiry
Throughout these years, I have tried to approach teaching not simply as the transmission of technical knowledge, but as a collaborative process of interpretation, participation, and critical inquiry.
I work to create a participatory classroom environment grounded in psychological safety, where students feel comfortable asking questions, making mistakes, and engaging in open discussion without fear of embarrassment or judgment.
I connect quantitative reasoning and statistics to real-world social issues—including labor, inequality, climate change, minimum wage, and public information—so that students see numbers not as abstract formulas but as tools for understanding human experiences and social structures.
More broadly, my teaching philosophy is shaped by the belief that education is not only about learning how to calculate, but also about learning how to interpret the world with curiosity, empathy, and intellectual honesty.
Collaborative whiteboard discussion connecting inflation, labor markets, pricing, inequality, and quantitative interpretation in Quantitative Reasoning.
Field-Based Quantitative Inquiry
In my Quantitative Reasoning courses, students conduct field-based research projects, collect and clean original datasets, interpret visualizations, and connect quantitative reasoning to broader social and economic questions.
One semester-long project asked students to conduct observational fieldwork across Manhattan retail stores, examining pricing, material composition, production geography, branding, labor conditions, and consumer markets. Students combined their observations into a shared dataset and analyzed the results through histograms, boxplots, scatterplots, literature review, and reflective analytical writing.
“A common trend I observed while cleaning the dataset was that items with the highest percentage of polyester fabric were usually produced in countries such as China, Bangladesh, Vietnam, or India, while European and American production appeared more frequently in luxury and boutique stores.”
“Price alone really can’t identify what kind of store something came from. A $200 item at T.J. Maxx and a $200 item at Saks are not the same thing, even if the number is exactly the same.”
“Even the act of collecting data was stratified by store type. Saks was crowded and tightly monitored, while ZARA and T.J. Maxx allowed much freer movement during fieldwork.”
“The trendline is almost flat, and the R² value suggests that price explains virtually none of the variation in cotton composition. This shows that branding, marketing, and symbolic value may matter more than material composition alone.”
“Professor Lee is the best math professor I have ever had. He is extremely clear in his explanations and always takes the time to show not just how to do something, but why it works.”
“This course changed the way I think about math and data. I came in mainly wanting to fulfill a requirement, and I’m leaving with a real interest in quantitative reasoning and how it can be used to understand the world more critically.”
“For me, it summed up what made this course so meaningful: I wasn’t just learning math; I was learning in an environment where people genuinely cared about one another as human beings.”
“The way we progressed from basic concepts to Excel, data visualization, and then full projects made the mathematics feel practical rather than abstract.”
“Working with topics such as plastic waste, sweatshops, minimum wage, inflation, and data misinterpretation helped me see how quantitative reasoning shows up in the news and in everyday decisions.”
“His enthusiasm for the class made the environment a space where I felt I could ask questions and truly understand lofty concepts.”
“Because of Hoyeon, I can understand the importance of statistical data and analysis and how to use it in my profession.”