In this study, we condition results from a variety of detection methods used to identify disengaged survey responses on response times. We then show how this conditional approach may be useful in identifying where to set response time thresholds for survey items, as well as in avoiding misclassification when using other detection methods.

In this article, we examined the prevalence of rapid guessing to determine if this behavior varied by grade, subject, and teacher, and evaluated if rapid guessing influenced teacher value-added estimates. We observed differences in rapid guessing across grades, subjects, and teachers; however, this behavior did not appear to have a substantive effect on teacher value-added estimates.

This study examines whether test effort differs by student subgroup, including by race and gender. The sensitivity of achievement gap estimates to any differences in test effort is also considered.

Achievement gaps are a metric of fundamental importance to U.S. practice and policy. Gap estimates are often used to measure the effectiveness and fairness of the education system at a given point in time, over the course of decades, and as children progress through school.

In this study, we examine whether behaviors indicative of academic disengagement like chronic absenteeism and course failures are related to behaviors indicative of test disengagement like rapidly guessing on items.

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.