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.

Important educational policy decisions, like whether to shorten or extend the school year, often assume that growth in achievement is linear through the school year.  This research examines this untested assumption using data from seven million students in kindergarten through 8th grade across the fall, winter, and spring of the 2016-17 school year.

In this National Institute of Statistical Sciences (NISS) Ingram Olkin “Statistics Serving Society” Forum, experts from around the country share statistical and data-analytic challenges they have faced as they have reported on and researched issues around the impact of COVID-19 in U.S. schools. Read more on the forum and presenters on the NISS webpage.