In age of big data, Shaffer's leading-edge work bridges the gap between quantitative and qualitative research

INNOVATION

At UW–Madison’s School of Education, innovation is a way of life. In our classrooms, in our research and even in our spare time, we are creating knowledge and seeking ways to improve and transform lives across fields as diverse as the arts, health and education.

In this issue of “Learning Connections,” we hope to pique your curiosity and deepen your appreciation of the School by spotlighting a sampling of the many ways in which faculty, staff and students are developing creative programs, conducting leading-edge research and advancing innovative tools — all of which can help us better address the many challenges of the modern world.

In age of big data, Shaffer’s leading-edge work bridging the gap
between quantitative & qualitative research

There’s no shortage of data in the digital age.

Every time someone searches for information online, posts on social media, takes a standardized test or swipes a credit card, they leave behind a drop in the vast stream of information that computers collect.

This might seem like a bonanza for education researchers but too often computers only look for trends and associations in big data. To actually understand what students and teachers are doing, and why they are doing it, researchers need to go beyond searching blindly for patterns.

Shaffer pull quoteThat is why social scientists in the School of Education and across the UW–Madison campus collect detailed “thick” data through qualitative research. These help researchers understand how people learn: how a teacher designs small-group activities or how students learn from talking with each other. But while these methods work with observations or video from a few classrooms, they do not scale well to the big data that computers now collect.

For the past 15 years, UW–Madison’s David Williamson Shaffer has been developing innovative tools that bridge the gap between quantitative and qualitative research.

In April, Shaffer published “Quantitative Ethnography,” a groundbreaking methods book that describes a new science for understanding what people do and why they do it. Now, Shaffer and his team have received another $2.5 million in funding from the National Science Foundation to help researchers use quantitative ethnography to analyze classroom videos, educational games, interviews, focus groups, social media and a host of other kinds of data.

“The book is the culmination of nearly two decades of work,” says Shaffer, the Vilas Distinguished Achievement Professor of Learning Science with the No. 1-ranked Department of Educational Psychology. “It explains, in straightforward language, how we can understand our increasingly datarich world. This new grant will let us make these tools much easier to use.”

Shaffer explains that what makes this work revolutionary is the way it helps researchers combine qualitative and quantitative methods, using statistical methods on field notes, interviews, observations and other kinds of “thick” data.

“This is a book about understanding why, in the digital age, the old distinctions between qualitative and quantitative research methods, between the sciences and humanities, and between numbers and understanding, limit the kinds of questions we can ask, in some cases, and lead us to accept superficial answers in others,” Shaffer writes in the book.

Education scholar Morten Misfeldt of Aalborg University in Copenhagen says that “Quantitative Ethnography” offers an introduction to the humanities for statisticians, an introduction to data science for qualitative researchers, and provides a compelling philosophical and intellectual journey for anyone looking to better understand learning, culture and behavior in the digital era.

In his role as a data philosopher and director of the Epistemic Games Group in the Wisconsin Center for Education Research, Shaffer has collaborated with colleagues across campus and around the globe, including researchers studying everything from fMRI and eye-tracking data, to classroom video, surgical simulations and teacher interviews.

“In the 21st century we need tools that can capture complex collaborative thinking in science, technology, engineering and mathematics — learning that goes beyond conventional tests of knowledge or measures of basic competencies,” says Shaffer. “We need to be able to assess how well students work together to make connections between ideas and understand complex problems. The tools of quantitative ethnography are designed to do just that.”
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