Most of us remember working with word problems in high school math class, which taught us how to apply numbers in context. But Sociology Prof. Esther Wilder believes that the strong emphasis on testing in many high schools dilutes these quantitative reasoning (QR) skills. Instead of developing the ability to apply numbers and data in real-world situations, she says, students focus exclusively on getting the right answer.
Funded by a recent $600,000 grant from the National Science Foundation (NSF), she and more than a dozen colleagues in The City University of New York are developing a new CUNY-wide, online course that will train faculty to teach QR skills, not just in math class, but across disciplines.
“Quantitative Reasoning is a competency and comfort in working with numerical data, which enables individuals to reason and solve quantitative problems found in a wide array of everyday life situations,” explains Dr. Wilder. “They can understand and create sophisticated arguments, supported by quantitative evidence, and clearly communicate those arguments in a variety of formats, such as words, tables, graphs, and equations.” Unfortunately, she adds, studies have shown that many students today lack the QR skills needed for personal and professional success.
QR is increasingly being recognized as an essential goal of a college education, and dozens of schools throughout the country, ranging from community colleges to four-year colleges and universities, have implemented some kind of course or program to strengthen their students’ QR skills. At CUNY, the new proposed core curriculum identifies both mathematics and QR as essential areas of undergraduate education.
“I want people to be able to read The New York Times, look at a chart and critically analyze it,” says Dr. Wilder. “QR gives students a variety of skills, like interpreting mathematical information and communicating that information to support their arguments. These skills are essential whether a student becomes a reporter, teacher, researcher, social worker, bank teller, or any of the dozens of occupations that our students will choose.”
Dr. Wilder heads the project as its Principal Investigator (PI), working with a team of more than a dozen faculty members from throughout CUNY. Lehman Economics Professor Dene Hurley and LaGuardia Community College Mathematics Professor Frank Wang are the project’s co-PIs. Over the course of the three-year grant, several dozen more CUNY faculty will collaborate with the team.
Their goals range from teaching faculty to apply QR within a disciplinary context to identifying and implementing best practices for teaching QR. Those might include active learning (such as lab work in which students analyze data first-hand), collaborative student learning, and writing about data. The idea is to move away from a traditional lecture format where students are passive recipients of information.
The team hopes to offer the course within CUNY in the summer of 2012. In subsequent years, the team will refine the course, open it to additional CUNY faculty, and promote its dissemination nationally.
“To make an initiative like this succeed, it needs to be institutionalized,” says Dr. Wilder. “We believe it will be more effective to first teach the teachers.” The course will be hosted by the Science Education Resource Center at Carleton College, a widely used Internet resource. “Our underlying philosophy is that repeated exposure is required throughout the curriculum for students to master these skills.”
Dr. Wilder joined the Lehman faculty in 2002. She received her B.A. in journalism from the University of Massachusetts and her Ph.D. in sociology from Brown University. From 2004 to 2007, she was the Principal Investigator for a NSF-sponsored grant to infuse data analysis throughout Lehman’s sociology curriculum. As a result of that project, she published two articles in the American Sociological Association’s journal Teaching Sociology.