Analysis of Student Achievement to Create a Predictive Model for Appropriate Accountability

• In Event: The Fairness of Examining Teachers' Quality and Competencies

Abstract

This quantitative study analyzed Algebra I End-of-Course (AI-EOC) achievement for Florida county-based school districts in correlation to the percent of socioeconomically disadvantaged students and minority students who took the AI-EOC. The researcher conducted a non-experimental analysis of existing official data from the Florida Department of Education (FLDOE) in order to explore cultural influencing factors. The results from a stepwise multiple linear regression test were analyzed and used to create a predictive model for the expected pass rate for each district. This study resulted in a useable predictive model for passing rates which is a useful tool when holding districts, schools, and teachers accountable for student achievement, as well as, for helping determine appropriate accountability systems that lessen negative unintended consequences.

Author

• Hope Holley, Florida Southern College