Most of us believe that when individuals have goals, their performance improves, and this belief is being put to the test in schools today. In an effort to create alignment between district and school improvement efforts, teachers are more likely than ever to have formal performance goals.

In this article, the authors explain how CAT provides a more precise, accurate picture of the achievement levels of both low-achieving and high-achieving students by adjusting questions as the testing goes along. The immediate, informative test results enable teachers to differentiate instruction to meet individual students’ current academic needs.

When New York state released the first results of the exams under the Common Core State Standards, many wrongly believed that the results showed dramatic declines in student achievement. A closer look at the results showed that student achievement may have increased.

This integrative review examines the motivational benefits of computerized adaptive tests (CATs), and demonstrates that they can have important advantages over conventional tests in both identifying instances when examinees are exhibiting low effort, and effectively addressing the validity threat posed by unmotivated examinees.

This study, using real data, provides empirical evidence of construct and invariance construct of MAP scales across grades at different academic calendars for 10 different states.

The current investigative study uses a multiple-indicator, latent-growth modelling (MLGM) approach to examine the longitudinal achievement construct and its invariance for MAP Growth.

These studies are conducted based on assumptions under regular conditions for fixed test forms, such as no missing responses and normal distribution of unidimensional ability for a population.