For decades, researchers and practitioners have made a great deal of effort to study a variety of methods to increase parameter accuracy, but only recently can researchers start focusing on improving parameter estimations by using a joint model that could incorporate RT and students information as CI.

Most previous research involving the study of response times has been conducted using locally developed instruments. The purpose of the current study was to examine the amount of rapid-guessing behavior within a commercially available, low-stakes instrument.

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.

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.

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.