The Stories We Tell: Math, Race, Bias, & Opportunity positions educators as professional decision-makers whose every day choices are deeply consequential. After exploring topics ranging from the early identification of talent, the use of demographic characteristics to make academic decisions, and the problematic casting of a 'gap' in mathematical performance as about the students themselves, the book explores how professional decision making, and a more precise use of data, can impact mathematical performance outcomes. With gentle precision, the book analyzes the patterns of practice in place as educators sort children according to perceived needs. Through case studies, the authors reconfigure the mathematics achievement gap as being about opportunity provided or denied at both the classroom and systemic levels. The book has implications for school personnel as well as others curious about how opportunity impacts outcomes and how data is (or is not) used to make decisions about children. Educators who challenge themselves to engage with the possibility of bias, and then face the stories we tell ourselves about the race/talent development/student merit relationship, will have the opportunity to write a powerful and equitable story going forward.
Autorentext
Dr. Valerie N. Faulkner is a Teaching Associate Professor in Elementary Education in the Department of Teacher Education and Learning Sciences at NC State University. Her current work focuses on K-2 mathematics education and issues of access and equity within schools.
Dr. Patricia L. Marshall is a Professor of Multicultural Studies in the Department of Teacher Education and Learning Sciences at NC State University. She is interested in the impact of elements of culture including race, class, language on the teaching-learning process and teachers' acquisition of cross-cultural competency.
Dr. Lee V. Stiff is Professor of Mathematics Education in the Department of Science, Technology, Engineering, and Mathematics Education and Associate Dean for Faculty and Academic Affairs in the College of Education at NC State University. He is interested in affecting change that promotes the mathematics education of all students by effectively using data to better align existing resources to address issues of equity, student access to high-quality math courses, and course placement disparities.
Inhalt
Acknowledgements
Introduction
Section I- The Gap-Maker
Chapter 1- The Farce of Early Identification: A Hidden Story in Gap-Making
The Promise of Promise
Talent Development
The Flawed Pillars of Early Identification
Talent is Detected in the Young
Talent is Innate
A Restricted Talent Pool is Desirable
The Story of Early Identification
Chapter 2- Data Doppels: Professional Stories and Gap-Making
Data and High-Stakes Decision-Making
Beware the Data Doppel
Decision-Making and Data Doppels in Action
Heart Attacks and the Goldman Index
Symphony Orchestras and Blind Auditions
Baseball and Moneyball
Data Doppels in Schools
What student data drives mathematics opportunities?
The At-Risk Model
An imagined conversation
Remediation as Elevation
Data Doppels in Math Class
National Data and Middle School Mathematics Placement
How Should We Think About This?
Section II- Academic Opportunity in Schools
Chapter 3- Diversity in Our Schools: Cultural Preconceptions & Instructional Choices
Multiple Dimensions of Student Diversity in Schools
New Normals, Societal Scourges and Childhoods Lost?
Intersecting Social Axes and Opportunity Gaps for Other People's Children
Beyond Diversity & The Abyss of Accountability
Homogeneous Ability Grouping: The Smoke and Mirrors of Effective Teaching?
Early Identification and Mindset in Grouping for Instruction
Perceptions and Scapegoats
Gap-Making through Teacher Decision-Making
Cultural Difference as a Factor In Teachers' Decision Making
Teacher Preconceptions: Critical Indicators of Student Learning Potential?
Heterogeneous Groups and Growth Mindset: Toward Neutralizing Problematic Decision Making
Troubling Stratification
Chapter 4- Follow the Data: Gifts, Access, Cuts, and The-Gap
Rigor for All
Different Strokes
A Brief History of Giftedness
Access to the Gift
The Cut
Following Data
Campbell's Law
Beyond Gifted