Students with Attention-Deficit/Hyperactivity Disorder (ADHD) are struggling writers. Yet no comprehensive model has been validated to explain their poor writing outcomes. This study aims to test whether an extended version of the Not-So-Simple View of Writing (NSVW) model can describe the effects of key abilities on writing performance in…

Reading research in the United States has mainly focused on early or, less frequently, middle grades and on monolingual (MN or English-only) rather than on multilingual (ML) students. To address these gaps, we focused on factors contributing to high school ML students' reading achievement. In particular, we first used machine learning to identify…

Self-regulation in early childhood is an important predictor of success across a variety of indicators in life, including health, well-being, and earnings. Although conceptually self-regulation has been defined as multifaceted, previous research has not investigated whether there is conceptual and empirical overlap between the factors that…

Much research shows academic self-concept and achievement are reciprocally related over time, based on traditional longitudinal data cross-lag-panel models (CLPM) supporting a reciprocal effects model (REM). However, recent research has challenged CLPM's appropriateness, arguing that CLPMs with random intercepts (RI-CLPMs) provide a more robust…

This paper develops models to measure growth in student achievement with a focus on the possibility of differential growth in achievement for low and high-achieving students. We consider a gap-closing model that evaluates the degree to which students in a target group -- students in the bottom quartile of measured achievement -- perform better…

Research with school-age readers suggests that the contributions of reading and language skills vary across reading comprehension assessments and proficiency levels. With a sample of 168 struggling adult readers, we estimated the explanatory effects of decoding, oral vocabulary, listening comprehension, fluency, background knowledge, and…

Research with school-age readers suggests that the contributions of reading and language skills vary across reading comprehension assessments and proficiency levels. With a sample of 168 struggling adult readers, we estimated the explanatory effects of decoding, oral vocabulary, listening comprehension, fluency, background knowledge, and…

In this article, a science interest network model (SINM) is introduced and a first empirical test of the model is presented. The SINM models interest as a dynamic relational construct, in which different interest components, that is, affective, behavioral, and cognitive components and related motivational components mutually reinforce one another…

If we wish to embed assessment for accountability within instruction, we need to better understand the relative contribution of different types of learner data to statistical models that predict scores and discrete achievement levels on assessments used for accountability purposes. The present work scales up and extends predictive models of math…

This three-article dissertation considers the pedagogical practices for developing statistically literate students and teaching data-driven decision-making with the goal of preparing students for civic engagement and improving student achievement. The first article discusses a critical review of the literature on data-driven decision-making…

Data mining has been successfully used by financial and retail companies since the mid-1960's to create predictive models and reveal unexpected relationships. However, it remains underutilized as a tool in educational research. Large-scale standardized assessment programs such as the Trends in International Mathematics and Science Study (TIMSS)…

Recently, students' interest in science has been conceptualized as a network model: the science interest network model (SINM) in which affective, behavioural and cognitive components interact together; building on science interest being a dynamic relational construct. In the current study, we combine the Australian Programme for International…

Measures of variability are successfully used in predictive modeling in research areas outside of education. This study examined how standard deviations can be used to address research questions not easily addressed using traditional measures such as group means based on index variables. Student survey data were obtained from the Organisation for…

This study aims to analyse the relationship between students' mathematics achievement in Programme for International Student Assessment (PISA) 2012 and the instructional climate-related factors in the index of principals' perceptions (learning hindrance, teacher morale and teacher intention). As preliminary analysis procedure, the chi-squared…

Mathematics competency is fast becoming an essential requirement in ever greater parts of day-to-day work and life. Thus, creating strategies for improving mathematics learning in students is a major goal of education research. However, doing so requires an ability to look at many aspects of mathematics learning, such as demographics and…