This study examined the utility of response time-based analyses in understanding the behavior of unmotivated test takers. For an adaptive achievement test, patterns of observed rapid-guessing behavior and item response accuracy were compared to the behavior expected under several types of models that have been proposed to represent unmotivated test taking behavior.

In this study, multivariate models that jointly estimate growth in achievement and self-efficacy during middle school are used to see how underlying developmental processes relate for ELLs.

In this study, we introduce those disengagement metrics for a policy and evaluation audience, including how disengagement might bias estimates of educational effectiveness. Analytically, we use data from a state administering a computer-based test to examine the effect of test disengagement on estimates of school contributions to student growth, achievement gaps, and summer learning loss.

In this study, we examine seasonal patterns of racial/ethnic achievement gaps in kindergarten through eighth grade using a national sample of over two million students.

This study examines academic skills at kindergarten entry from 2010 and 2017 using data from over 2 million kindergarten students. Results indicated kindergarteners in 2017 have slightly lower math and reading skills than in 2010, but that inequalities at school entry by race/ethnicity and school poverty level have decreased during this period.

Educators sometimes ask: do students rapidly guess because they don’t know the answer to a question, or do rapid guesses reflect a lack of engagement with the test? Would a student’s scores improve if that student engaged more with the assessment and rapidly guessed on fewer items? Examining MAP® Growth™ test scores and levels of student test engagement for over 100,000 tests for which students retested within one day, the results showed that students’ test taking engagement often differed between the initial test and the retest.

In this study, we apply the Compound Polynomial or “CP” model in a school evaluation context. The CP model addresses the seasonality of student test scores by simultaneously estimating between- and within-year growth.