Author: Gregory, Palardy J., & Peng, Luyao

Title: The Effect of Summer on Value-added Assessments of Teacher and School Performance

University Affiliation: University of California Riverside

Email: gjpalardy@gmail.com

Research Question:

  1. To what extent are value added assessments (VAA) estimates of teacher and school performance affected by summer learning differences?
  2. Can any summer effect be ameliorated without biannual assessments (i.e., fall and spring) using control covariates that are typically available to school districts, such as student demographics and contextual characteristics of classrooms and schools?
  3. To what degree does including summer in VAA estimates result in biases against teachers and schools serving low income and ethnic minority children?

Published: Yes

Journal Name or Institutional Affiliation: Education Policy Analysis Archives

Journal Entry: Vol. 23, No. 92, Pp. 1-26

Year: 2015

Findings:

  1. A substantial portion of the variance in YoY (Year over Year) VAA estimates originates from summer and that summer variance alters the quintile rankings of a high percentage of teachers and schools.
  2. The summer effect invariably underestimated the performance of teachers and schools in the lowest quintile of summer change and overestimated the performance of teachers and schools in the highest quintile of summer change.
  3. Including an extensive number of demographic and contextual variables does not substantively reduce the summer effects on VAA estimates. These results suggest that twice-annual assessment may be necessary to remove the summer effects from VAA estimates.
  4. Including summer in VAA estimates results in systematic biases against schools serving higher concentrations of students who qualify for FRL. Students from low SES families tend to have greater declines in reading achievement over summer, but learn at similar rates as other students during the school year.

Scholarship Type Journal Article Empirical Research

Keywords: Academic Achievement, Accountability

Regions National

Methodologies: Quantitative

Research Designs: Secondary Survey Data

Method of Analysis: Multilevel Models

Sampling Frame: 2,251 first grade students students, 682 classrooms, and 168 schools

Sample Types: Nationally Representative

Unit of Analysis: Classroom, School, Student

Data Types: Quantitative-Longitudinal

Data Description: