Using Non-Achievement-Based Variables to Differentiate District Performance Grades

• In Event: AERA Poster Session 6
  In Poster Session: Demographics and K–12 Accountability Systems in the Time of COVID-19 (San Diego)

Abstract

The COVID-19 pandemic disrupted many school accountability systems that rely on student-level achievement data. Many states have encountered uncertainty about how to meet federal accountability requirements without typical school data. Prior research provides an abundance of evidence that student achievement is correlated to students' social background, which raises concerns about the predictive bias of accountability systems. The focus of this quantitative study is to explore the predictive ability of non-achievement based variables (i.e., students' social background) on measures of school accountability in one Midwest state. Results suggest that social background and community demographic variables have a significant impact on measures of school accountability, and might be interpreted cautiously. Implications for policy and future research are discussed.

Authors

• Timothy Donald Folger, Bowling Green State University

• Audrey Conway Roberts, Bowling Green State University

• Jonathan David Bostic, Bowling Green State University