Electronic product use among preschool children is gradually widespread. To explore whether and how electronic product use causes problem behaviours in preschool children, this study analyses the relationships between the degree of electronic product use, problem behaviours, and the roles of parenting styles and parent-child relationships in…

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…

Background: Observation Studies, Unmeasured Confounding, and Sensitivity Analysis: An important part of educational research is identifying important, potentially causal, factors that influence children's learning from observational studies. However, it is well-known that discovering such factors from observational studies can be biased due to…

Causal search algorithms have been effectively applied in different fields including biology, genetics, climate science, medicine, and neuroscience. However, there have been scant applications of these methods in social and behavioral sciences. This article provides an illustrative example of how causal search algorithms can shed light on…

The problem this study addressed was whether an intervention, grounded in Reading Recovery strategies, was as effective when used with struggling readers in small groups as it is in 1:1 instruction. The purpose of this causal-comparative study was to investigate the differences in student performance between students who received small group…

The aim of this study was to investigate kindergartners' exploration of interactive causality during their play with a pair of toy sound blocks. Interactive causality refers to a type of causal pattern in which two entities interact to produce a causal force, as in particle attraction and symbiotic relationships. Despite being prevalent in nature,…

Understanding complex systems requires reasoning about causal relationships that behave or appear to behave probabilistically. Features such as distributed agency, large spatial scales, and time delays obscure co-variation relationships and complex interactions can result in non-deterministic relationships between causes and effects that are best…

This paper aims at exploring (a) whether preschoolers recognize that offspring share physical traits with their parents due to birth and behavioural ones due to nurture, and (b) whether they seem ready to explain shared physical traits with a "pre-biological" causal model that includes the contribution of both parents and a rudimentary…

We contribute to debate about causal inferences in educational research in two ways. First, we quantify how much bias there must be in an estimate to invalidate an inference. Second, we utilize Rubin's causal model to interpret the bias necessary to invalidate an inference in terms of sample replacement. We apply our analysis to an inference…

Research using an experimental design is needed to provide firm causal evidence on the impacts of child care subsidy use on child development, and on underlying causal mechanisms since subsidies can affect child development only indirectly via changes they cause in children's early experiences. However, before costly experimental research is…

In this paper we describe a method for exploring young children's views of illness causality in social context. Studies of children's conceptualisation of illness have predominantly focused on the nature of children's knowledge rather than locating that knowledge within socio-cultural contexts. Adopting a socio-constructivist perspective we sought…

This article addresses three questions: Does reduced class size cause higher academic achievement in reading, mathematics, listening, and word recognition skills? If it does, how large are these effects? Does the magnitude of such effects vary significantly across schools? The authors analyze data from Tennessee's Student/Teacher Achievement Ratio…

This paper analyzes 12 recent within-study comparisons contrasting causal estimates from a randomized experiment with those from an observational study sharing the same treatment group. The aim is to test whether different causal estimates result when a counterfactual group is formed, either with or without random assignment, and when statistical…

The purpose of this study was to illustrate the use of Hierarchical Linear Models (HLM) to investigate the effects of school and children's attributes on children' reading achievement. In particular, this study was designed to: (1) develop the HLM models to determine the effects of school-level and child-level variables on children's reading…

Using the first 4 waves of data from the Early Childhood Longitudinal Study-Kindergarten cohort (ECLS-K), this piecewise 3-level (time-student-school) growth-curve model provides a portrait of students' reading growth over the first 2 years of school. On average, students make much greater reading gains in 1st grade than they do in kindergarten.…