New Study Explores Quantitative Data in the Classroom

In the recent study “Fostering Data Literacy: Teaching with Quantitative Data in the Social Sciences”, George Mason University joined 19 other research universities in the United States in interviewing instructors teaching undergraduate, data-intensive courses in the social sciences to identify their needs, challenges, and teaching practices.

“It’s conventional wisdom that the library’s services and collections are essential to the university’s educational mission. What might be less well known is how important data—both its discovery and analysis—has become in that enterprise,” Wally Grotophorst, Associate University Librarian, said. “For the library’s part, we need to understand how quantitative skills are being taught and what barriers to that instruction we can help mitigate. Participating in this study is one tool for getting answers to those questions.”

Mason’s published its findings, “Teaching with Data in the Social Sciences at George Mason University”, in October 2021. Four faculty in the Mason University Libraries—Wendy Mann, Kim MacVaugh, Jasmine Spitler and Andrew Lee—centered their research on Ithaka S+R’s idea that “instructors in the social sciences need support in locating appropriate datasets and identifying tools to help students manipulate, understand, and visualize data.”

The overall study found that instructors focus on the critical interrogation of quantitative information in introductory classes, while teaching students to conduct their own research and analysis in upper division courses. As such, instructors generally avoid asking students to locate data on their own because most students struggle to find appropriate datasets. In addition, faculty said that teaching students to use analytical software is a hands-on process requiring a significant amount of valuable instructional time, sometimes at the cost of teaching discipline-specific perspectives.

“I think the report is important for department chairs and deans as it describes the huge challenge faculty have teaching data analysis—it simply cannot be done in one class. We do often get students who feel their professor didn’t start “at the beginning” and thus are completely lost,” Debby Kermer, Data Services Research Consultant, University Libraries, said. “It also shows how the libraries can and do help: facilitating access to data, helping with software (even jamovi), and recommending teaching materials and other Open Educational Resources. We work with many faculty already, and would love to work with more.”

According to the authors, the study provides the evidence needed to help structure and develop digital and data literacy programs at Mason. The findings represent an important contribution to learning about teaching practices and challenges faced in teaching data-intensive courses. It shows that among the participating institutions, instructors are facing similar issues.

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