Data-Driven Decision-Making Models in Practice: A Case Study of Classroom and Student Placement Processes

• In Event: Separate and Still Not Equal: Consequences of Between- and Within-School Tracking in the 21st Century

Abstract

Recent emphasis on data use has raised questions about the ways in which data are conceptualized and used to justify or argue against classroom placement and ability grouping decisions. Using in-depth observations and interviews, we examine how data are used during the class formation and student placement process in elementary schools, building on Ikemoto & Marsh’s (2007) models of data-driven decision making. Findings show that educators collected similar types of diverse data across schools, but there were key differences in analysis and decision making. Depending on teacher teams and the principal, different types of sorting logics prevailed. However, assessing student needs holistically and balancing high needs students across classes were consistent features

Authors

• Vicki Park, San José State University

• Amanda L. Datnow, University of California - San Diego

• Elise St John, San Jose State University

• Bailey Miyeon Choi, University of California - San Diego