New research examining academic achievement and growth of students in special education and their peers who were never in special education during each school year and summer in grades K-4 shows that students with disabilities grow as much or more academically during the school year than their peers without disabilities during some years, but that steeper summer learning losses for students with disabilities contribute to widening disparities.

This study compares within- and across-years academic growth for students who were ever in special education (ever-SPED) to students who were never in special education (never-SPED) in grades K-4. Ever-SPED students grew more in math and reading than never-SPED students during many school years, but lost more learning during every summer than their peers, leading to expanding disparities. These findings suggest that summer learning opportunities are crucial for improving educational outcomes for students with disabilities.

This research study is the first time of applying the thinking of semi-supervised learning into CDM. Also, we used the validating test to choose the appropriate parameters for the ANNs instead of using typical statistical criteria, such as AIC, BIC.

To avoid the subjectivity of having a single person evaluate a construct of interest (e.g., a student’s self-efficacy in school), multiple raters are often used. This study provides a model for estimating growth in the presence of multiple raters.

This study uses reading test scores from over 728,923 3rd–8th-grade students in 2,056 schools across the US to compare threshold-setting methods to detect noneffortful item responses. and so helps provide guidance on the tradeoffs involved in using a given method to identify noneffortful responses.

This paper describes a method for identifying partial engagement and provides validation evidence to support its use and interpretation. When test events indicate the presence of partial engagement, effort-moderated scores should be interpreted cautiously.

This report presents the results of a mode comparability study conducted through simulations to evaluate how scores from MAP Growth administered on the constraint-based engine (CBE) compare to those administered on the current MAP Growth engine known as COLO.