Schools are increasingly held accountable for their contributions to students’ academic growth in math and reading. Under The Every Student Succeeds Act, most states are estimating how much schools improve student achievement over time and using those growth metrics to identify the bottom 5% of schools for remediation.

How does rapid-guessing differ from solution behavior? Research provides insight into test disengagement and how disengagement should be managed in scoring.

Learn more about our examination of student disengagement and how it may bias estimates of effectiveness based on observed test results.

In this Ed Tech Digest article, Cindy Jiban discusses how oral reading fluency assessment is now commonplace in the primary grades. This represents a significant step for data-based problem solving in education. However, given some of the side effects that have emerged, it is clear that fluency assessment is due for significant structural improvement.

The development of academic English proficiency and the time it takes to reclassify to fluent English proficient status are key issues in English learner (EL) policy. This article develops a shared random effects model (SREM) to estimate English proficiency development and time to reclassification simultaneously, treating student-specific random effects as latent covariates in the time to reclassification model.

This paper briefly discusses the trade-offs involved in making such a transition, and then focuses on a relatively unexplored benefit of computer-based tests – the control of construct-irrelevant factors that can threaten test score validity.

When computer-based tests are used, disengagement can be detected through occurrences of rapid-guessing behavior. This empirical study investigated the impact of a new effort monitoring feature that can detect rapid guessing, as it occurs, and notify proctors that a test taker has become disengaged.