David Williamson Shaffer has been appointed the Sears Bascom Professor of Learning Analytics in the UW–Madison School of Education.
The honor acknowledges Shaffer’s decades of exemplary teaching, mentorship, and research, which includes establishing the field of quantitative ethnography. Quantitative ethnography (QE) unifies statistical and qualitative research methods to help researchers use the power of “big data” to build more accurate and insightful models of complex and collaborative human activity.
“I am so pleased that Professor Shaffer was awarded the Sears Roebuck Foundation Bascom Professorship,” said Diana Hess, dean of the UW–Madison School of Education. “He is an outstanding teacher, an innovative researcher who has literally created a field, and a great mentor to graduate students.”
Shaffer also holds the title of Vilas Distinguished Achievement Professor of Learning Sciences in the Department of Educational Psychology, and is a principal investigator in the Wisconsin Center for Education Research (WCER).
Since the publication of Shaffer’s book, Quantitative Ethnography, in 2017, his Epistemic Analytics Lab has interacted with more than 300 researchers from 70 institutions in 30 countries. Those researchers’ work spans the fields of anthropology, cognitive science, computer science, education, engineering, environmental science, geography, history, human-computer interaction, learning analytics, learning sciences, linguistics, medicine, psychology, robotics, sociology, and statistics.
Since 2019, researchers using QE have met at the annual International Conference on Quantitative Ethnography, which will be held in 2023 in Melbourne, Australia.
Shaffer says QE lets researchers move past the mindset of “just looking at large chunks of data, finding patterns, and hoping they’re meaningful.”
“That’s not a particularly good way to study human behavior,” he says.
Instead, QE gives researchers the ability to look beneath the surface of data and understand the reasoning and motivation of the people whose actions created the data in the first place.
“All of what we do in QE,” Shaffer argues, “is predicated on the fact that humans are meaning-making machines. We do things because we have intentions, desires, and reason — and QE lets us understand the how and why behind the choices people make.”
Shaffer says the financial resources of the Sears Bascom appointment will support his ability to mentor researchers in the field around the world.
“An important part of my job is to introduce researchers around the world to work on QE, and to help foster collaborations around research and training,” he says. “This kind of funding is an accelerant that will help drive that work forward.”