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Sunday, October 20, 2019

New Book Explores How Data Can Contribute to Inequity in Mathematics Classrooms | Research and Impact - NC State College of Education

For many minority students, high performance doesn’t guarantee access to advanced mathematics classes. A new book explores how data and bias can lead to inequity in the classroom, inform Janine Bowen, Writer and Editor at NC State University.

Could appropriate use of data by educators lead to more equitable access to high-quality mathematics for K-12 students? This is the question three NC State College of Education faculty explore in their new book The Stories We Tell: Math, Race, Bias, and Opportunity. 

Teaching Associate Professor Valerie Faulkner, Ph.D., Professor of Multicultural Studies Patricia L. Marshall, Ed.D., and Associate Dean for Faculty and Academic Affairs Lee V. Stiff, Ph.D., began collaborating several years ago. One of their articles, “Less is More,” examined how irrelevant data gets used in all manner of decision making including how education professionals group students for instruction. Following the publication of that article, Rowman and Littlefield approached the trio about expanding their work into a book.

“One of the things we examine is how teacher perspectives about students are often colored by ideas about race and by those features or group categories over which students have no control and really are not relevant to making a decision about who gets to have access to particular mathematics courses,” Marshall said.

The authors analyze the patterns of practice that are in place as children are sorted according to perceived needs. Through multiple case studies within and outside of schools, the book highlights what the authors refer to as “data doppelgangers” or “data doppels,” which occur when data or facts that are not relevant to a decision are used to inform the decision making process...

The book explores how professional decision making, along with a more precise use of data, can impact mathematical performance outcomes. The authors suggest that, in some cases, too much irrelevant data is used to determine which students can access advanced mathematics. Instead, they recommend, educators should focus entirely on performance data when determining placement.
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Recommended Reading

The Stories We Tell: Math, Race, Bias, and Opportunity
Source: NC State College of Education