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Whether and How to Use State Tests to Measure Student Achievement in a Multi-State Randomized Experiment: An Empirical Assessment Based on Four Recent Evaluations

NCEE
Author(s):
Marie-Andrée Somers, Pei Zhu, and Edmond Wong: MDRC
Publication date:
October 2011
Publication number:
NCEE 20124015

Summary

An important question for educational evaluators is how best to measure academic achievement, the outcome of primary interest in many studies. In large-scale evaluations, student achievement has typically been measured by administering a common standardized test to all students in the study (a “study-administered test”). In the era of No Child Left Behind (NCLB), however, state assessments have become an increasingly viable source of information on student achievement. Using state tests scores can yield substantial cost savings for the study and can eliminate the burden of additional testing on students and teaching staff. On the other hand, state tests can also pose certain difficulties: their content may not be well aligned with the outcomes targeted by the intervention and variation in the content and scale of the tests can complicate pooling scores across states and grades.

This NCEE Reference Report, Whether and How to Use State Tests to Measure Student Achievement in a Multi-State Randomized Experiment: An Empirical Assessment Based on Four Recent Evaluations, examines the sensitivity of impact findings to (1) the type of assessment used to measure achievement (state tests or a study-administered test); and (2) analytical decisions about how to pool state test data across states and grades. These questions are examined using data from four recent IES-funded experimental design studies that measured student achievement using both state tests and a study-administered test. Each study spans multiple states and two of the studies span several grade levels.

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Research Report
NCEE

Whether and How to Use State Tests to Measure Student Achievement in a Multi-State Randomized Experiment: An Empirical Assessment Based on Four Recent Evaluations

By: Marie-Andrée Somers, Pei Zhu, and Edmond Wong: MDRC
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