A decision consistency (DC) index is an estimate of the consistency of a classification decision on an exam. More specifically, DC estimates the percentage of examinees that would have the same classification decision on an exam if they were to retake the same or a parallel form of the exam again without memory of taking the exam the first time.…

Universal screening to predict students' risk for reading problems is a foundational component of the Multi-Tiered Systems of Support framework and is required by law in many US states. School or district administrators are tasked with selecting screening assessments that are both technically adequate and feasible given the resources of their…

Universal screening to predict students' risk for reading problems is a foundational component of the Multi-Tiered Systems of Support framework and is required by law in many US states. School or district administrators are tasked with selecting screening assessments that are both technically adequate and feasible given the resources of their…

The purpose of this study was to compare the classification accuracy of data produced by the previous year's end-of-year New York state assessment, a computer-adaptive diagnostic assessment ("i-Ready"), and the gating combination of both assessments to predict the rate of students passing the following year's end-of-year state assessment…

Drawing from the developmental and cognitive mathematics literature, the purpose of this study was to investigate the reliability, validity, and diagnostic utility of a widely-researched number line task in kindergarten. Specifically, the Number Line Assessment 0-100 (NLA 0-100) as compared to an established kindergarten screening measure was…

A strong foundation in early literacy supports children's academic pursuits and impacts personal, social, and economic outcomes. Therefore, examining the adequacy of early literacy assessments as predictors of future performance on important outcomes is critical for identifying students at risk of reading problems. This study explored the…

Educators use universal screening to identify students who may be at risk for not meeting proficiency on the state assessment. Given the potential high-stakes of state tests, using accurate screeners is critical. Independent research is emerging on screeners such as the Measures of Academic Progress (MAP), a computer adaptive test, and the…

Clinical Question: When assessing a kindergarten student in the area of early reading skills, does dynamic assessment provide additional classification accuracy over and above static, standardized assessments when determining if the student exhibits a difference in early learning experiences or a true disorder? Method: Systematic Review. Study…

This paper demonstrated the use of the supervised Machine Learning (ML) for text classification to predict students' final course grades in a hybrid Advanced Statistics course and exhibited the potential of using ML classified messages to identify students at risk of course failure. We built three classification models with training data of 76,936…

The main purpose of this study was to validate the curriculum-based measure "Indicadores de Progreso de Aprendizaje en Matemáticas" (IPAM [Indicators of Basic Early Math Skills]) in a local, Spanish-speaking context. This tool has been designed to identify first-grade students at risk for mathematics learning disabilities. The IPAM…

A critical task for tutors is to provide learners with suitable reading materials in terms of difficulty. The challenge of this endeavor is increased by students' individual variability and the multiple levels in which complexity can vary, thus arguing for the necessity of automated systems to support teachers. This chapter describes…

This technical report is an addendum to a study we initially reported on in 2014 (Wray, Lai, Saez, Alonzo, & Tindal, 2014). In response to a request for additional analyses, in particular reporting confidence intervals around the results, we re-analyzed the data from the Wray et al study. This supplementary report presents the results of the…

Within higher education systems, different institutions deliver different patterns of disciplines. A simple analysis of the structure of that pattern of disciplines across institutions in one higher education system uncovers a surprising relationship. That is, the key dimensions which describe that structure align nearly perfectly with dimensions…

A growing body of research suggests that accounting for student specific variability in educational data can improve modeling accuracy and may have implications for individualizing instruction. The Additive Factors Model (AFM), a logistic regression model used to fit educational data and discover/refine skill models of learning, contains a…

This study examined the predictive validity and classification accuracy of individual- and group-administered screening measures relative to student performance on a year-end state reading assessment in two states. A sample of 321 students was assessed in the areas of word-level and text fluency, as well as reading comprehension in the fall of…