Causal inference involves determining whether a treatment (e.g., an education program) causes a change in outcomes (e.g., academic achievement). It is well-known that causal effects are more challenging to estimate than associations. Over the past 50 years, the potential outcomes framework has become one of the most widely used approaches for…

In this article, we extend Liao's test for across-group comparisons of the fixed effects from the generalized linear model to the fixed and random effects of the generalized linear mixed model (GLMM). Using as our basis the Wald statistic, we developed an asymptotic test statistic for across-group comparisons of these effects. The test can be…

This study explored the validity of growth on two computer adaptive tests, Star Reading and Star Math, in explaining performance on an end-of-year achievement test for a sample of students in Grades 3 through 6. Results from quantile regression analyses indicate that growth on Star Reading explained a statistically significant amount of variance…

Learning to solve arithmetic word problems is an essential part of the primary school mathematics curriculum. The success of word-problem solving was previously found to relate to reading comprehension ability of children. However, the relationships between specific reading comprehension component skills and word-problem solving remain largely…

The aim of this pilot study is to evaluate the relevance of the use of history in mathematics education. This paper presents an experiment carried out in France with sixth-grade students (n=108) in which an ancient number system is used, an approach that is commonly suggested in French sixth-grade textbooks but has previously been unassessed.…

Curriculum-based measurements (CBM) are used in schools to screen students for academic difficulties. Oral reading fluency curriculum-based measures (CBM-R) are the most popular, yet several studies have identified predictive bias in CBM-Rs in relation to key variables (e.g., race, sex). Despite a massive increase in the use of these measures as…

The main objective of the study was to explore the main predictors that influence academic stress among fourth-grade elementary school students using data from the Panel Study on Korean Children via a least absolute shrinkage and selection operator (LASSO) regularized penalty regression model. The study examined 280 explanatory variables using the…

Recent research provides evidence that an intersectional approach to defining reference and focal groups results in a higher percentage of comparisons flagged for potential DIF. The study presented here examined the generalizability of this pattern across methods for examining DIF. While the level of DIF detection differed among the four methods…

The current research used longitudinal data from the National Institute of Child Health and Human Development Study of Early Child Care and Youth Development (N = 1,103) to examine the developmental autoregressive cascades of prosocial behavior, academic competence, and peer exclusion in Grades 3-6. The cascade paths revealed that Grade 3…

This paper analyses the associations between computer use in schools and at home and test scores by using TIMSS data covering over 900,000 children in fourth grade. When controlling for school fixed effects, pupils who use computers at school, especially those who use them frequently are found to achieve less than students who never use computers.…

The purpose of the study is to analyze the affective traits that affect mathematics achievement through Structural Equation Modeling (SEM) as a traditional regression model and Multivariate Adaptive Regression Splines (MARS), as one of the data mining methods. Structural Equation Modeling, one of the regression-based methods, is quite popular for…

Despite the overwhelming focus on the overall average treatment effect in the methodological and statistical literature, in many cases the efficacy of an educational program or intervention might vary based on unit background characteristics. The identification of subgroups for which an educational intervention is particularly effective or, on the…

Background: The importance of high school completion for jobs and postsecondary opportunities is well- documented. Combined with federal laws where high school graduation rate is a core performance indicator, school systems and states face pressure to actively monitor and assess high school completion. This proposal employs machine learning…

In studies of educational achievement, students' self-reported number of books in the family home is a frequently used proxy for social, cultural, and economic background. Absent hard evidence about what this variable captures or how well, its use has been motivated by strong associations with student outcomes. I show that these associations rest…

Knowledge components (KCs) define the underlying skill model of intelligent educational software, and they are critical to understanding and improving the efficacy of learning technology. In this research, we show how learning curve analysis is used to fit a KC model--one that was created after use of the learning technology--which can then be…