Quasi-Experimental Test of the Elementary School Success Profile Model of Assessment & Prevention: Empowering Stakeholders to Improve Academic Success
Methods: The study had a quasi-experimental design in which 3-year trajectories of proficiency rates on standardized reading tests of a 3rd grade cohort of students in four ESSP MAP schools were compared to the trajectories for 10 different cohorts and six other schools in the same district. The design controlled for cohort, history, school, and maturation effects. Longitudinal hierarchical linear modeling was used to test differences in the starting points and slopes of the trajectories across the treatment and comparison groups. In addition to comparing school-level trajectories for all students in the treatment and comparison conditions, we studied the trajectories for African American, Latino, and low and non-low income subgroups.
Results: Findings from the study indicated there was significantly faster growth in school-level standardized reading scores for all students combined, and for the African American, European American, and non-low income subgroups in the ESSP MAP schools and cohort compared to the non-treatment clusters. Annual increases in the percentage of students proficient in reading in the ESSP MAP clusters ranged from 4.2 to 11.8 points higher than the growth among comparison groups.
Conclusions & Implications: Stakeholders from students and parents to principals and district administrators are not satisfied with the academic progress that has been made over the past decade with federal mandates. The ESSP-MAP uses data from multiple stakeholders as the starting point of a school-level, self-determined process to promote student success. The current study offers preliminary evidence that this theoretically and empirically based approach works. Policy implications include the need to replace top-down mandates with efforts to build local capacity and decision-making. Practice implications include promoting school social workers as facilitators of autonomous data-driven decision making.