Considerable attention and legislation are currently focused on developmental dyslexia. A major challenge to these efforts is how to define and operationalize dyslexia. In this article, we argue that rather than defining dyslexia on the basis of an underlying condition, dyslexia is best viewed as a label for an unexpected reading disability. This…

This article is an extension of a work in progress paper originally presented at the conference FiE 2020, Frontiers in Education by (Schirichian et al., 2020), as a result of Schirichian's master's in science dissertation. It studies the relations between academic performance, protection factors, life at university, and personal characteristics to…

In order to evaluate the effect of a policy or treatment with pre- and post-treatment outcomes, we propose an approach based on a transition model, which may be applied with multivariate outcomes and accounts for unobserved heterogeneity. This model is based on potential versions of discrete latent variables representing the individual…

Differences in socioeconomic status (SES) correlate both with differences in cognitive development and in brain structure. Associations between SES and brain measures such as cortical surface area and cortical thickness mediate differences in cognitive skills such as executive function and language. However, causal accounts that link SES, brain,…

Self-regulated learning (SRL), which involves the regulation of cognitive, affective, metacognitive, and motivational processes, is an important construct for analyzing effective student learning in open-ended learning environments (OELEs). Novice K-12 students working on complex learning tasks in OELEs often engage in sub-optimal use of SRL…

A vast body of work highlights executive functions (EFs) as robust correlates of mathematics achievement over the primary and preschool years. Yet, despite such correlational evidence, there is limited evidence that EF interventions yield improvements in early years mathematics. As intervention studies are a powerful tool to move beyond…

This study assesses the impact of involuntary job loss on college persistence by leveraging different job-loss timings relative to a student's college enrollment decision. We find that job loss increases the probability that a working college student leaves college before attaining a degree, but access to short-term credit through credit card…

In the complex world of educational policy, causal inferences will be debated. As we review non-experimental designs in educational policy, we focus on how to clarify and focus the terms of debate. We begin by presenting the potential outcomes/counterfactual framework and then describe approximations to the counterfactual generated from the…

This paper describes the nature of home-school value discrepancies perceived by students, and tests associations between such value discrepancies and teacher-student relationships with student generational status as a moderator. Using a sample of 1,551 students from grades 10 and 11, chi-square tests and ANOVAs were used to describe the nature of…

This study examines the relationship between reputational threat and altruistic behavior in children aged 6-11 and explores how social inhibition and group relationships affect this behavior. Study 1 involved 204 children and found that age and reputational threat influence altruism, with age 8 being a key turning point. Study 2 focused on 130…

This study proposes a two-stage causal modeling with instrumental variables to mitigate selection bias, provide correct standard error estimates, and address nonnormal and missing data issues simultaneously. Bayesian methods are used for model estimation. Robust methods with Student's "t" distributions are used to account for nonnormal…

Cyberbullying has become increasingly prevalent, particularly on social media. There has also been a steady rise in cyberbullying research across a range of disciplines. Much of the empirical work from computer science has focused on developing machine learning models for cyberbullying detection. Whereas machine learning cyberbullying detection…

One of the core dimensions of historical and social science inquiry is "[d]eveloping questions and planning inquiries" according to the National Council for the Social Studies' College, Career, and Civic Life (C3) Framework. Yet existing education research, instructional resources, and assessment have ignored how students frame problems…

Social scientists are often interested in estimating the marginal effects of a time-varying treatment on an end-of-study continuous outcome. With observational data, estimating these effects is complicated by the presence of time-varying confounders affected by prior treatments, which may lead to bias in conventional regression and matching…

I use rich administrative data and several quasi-experiments in Texas to study which students benefit most from college grant aid and why. For "extensive-margin" students, grant aid causes enrollment in college, and therefore has potentially large benefits relative to these students' no-college counterfactual. In contrast,…