Purpose: This study examines online speech processing in typically developing and late-talking 2-year-old children, comparing both groups' word recognition, word prediction, and word learning. Method: English-acquiring U.S. children, from the "When to Worry" study of language and social--emotional development, were identified as typical…

For successful learning, students need to evaluate their learning status relative to their learning goals and regulate their study in response to such monitoring. The present study investigated whether making metacognitive judgments on previously studied text would enhance the learning of that studied (backward effect) and newly studied text…

This software review discusses the capabilities of Stata to conduct item response theory modeling. The commands needed for fitting the popular one-, two-, and three-parameter logistic models are initially discussed. The procedure for testing the discrimination parameter equality in the one-parameter model is then outlined. The commands for fitting…

The samples of evidence we use to make inferences in everyday and formal settings are often subject to selection biases. Two property induction experiments examined group and individual sensitivity to one type of selection bias: sampling frames - causal constraints that only allow certain types of instances to be sampled. Group data from both…

Recent critiques of physics education research (PER) studies have revoiced the critical issues when drawing causal inferences from observational data where no intervention is present. In response to a call for a "causal reasoning primer" in PER, this paper discusses some of the fundamental issues in statistical causal inference. In…

Mental model (Johnson-Laird, 2001) and probabilistic theories (Oaksford & Chater, 2009) claim to provide distinct explanations of human reasoning. However, the dual strategy model of reasoning suggests that this distinction corresponds to different reasoning strategies, termed "counterexample" and "statistical,"…

Children have a robust social preference for people similar to them, like those who share their language, accent, and race. In the present research, we show that this preference can diminish when children consider who they want to learn about. Across three experiments, 4- to 6-year-olds (total N = 160; 74 female, 86 male, from the Waterloo region…

Children are sensitive to their own and others' epistemic states and use these to guide their learning and communication. Here, we systematically examined children's use of epistemic states to make diagnostic social inferences. Specifically, we investigated children's group membership inferences based on what others do and do not know and what…

Estimation of causal effects requires making comparisons across groups of observations exposed and not exposed to a a treatment or cause (intervention, program, drug, etc). To interpret differences between groups causally we need to ensure that they have been constructed in such a way that the comparisons are "fair." This can be…

Narrative inquiry is a type of qualitative research that explores human experiences through lived or told stories to understand a phenomenon. Narrative researchers collect data through spoken or written stories and life experiences of an individual (subject). The data is examined in chronological order to understand the meaning of the phenomenon…

In learning about the world children must not only make inferences based on minimal evidence, but must deal with conflicting evidence and question those initial inferences when they appear to be wrong. Four experiments (N = 144) found that young children were significantly more likely to revise their initial inferences when conflicting evidence…

Pseudocontingencies are inferences of correlations between variables, like two options and two outcomes, drawn on the basis of their skewed base rates covarying across a third variable (e.g., two contexts). Here, we investigated the effect of pseudocontingency inference on choice behavior. When choices between two options are not based on the…

A common divide-and-conquer approach for Bayesian computation with big data is to partition the data, perform local inference for each piece separately, and combine the results to obtain a global posterior approximation. While being conceptually and computationally appealing, this method involves the problematic need to also split the prior for…

Over the course of the introductory calculus-based physics course, students are often expected to build conceptual understanding and develop and refine skills in problem solving and qualitative inferential reasoning. Many of the research-based materials developed over the past 30 years by the physics education research community use sequences of…

Quasi-experimental methods are a cornerstone of applied social science, providing critical answers to causal questions that inform policy and practice. Although open science principles have influenced experimental research norms across the social sciences, these practices are rarely implemented in quasi-experimental research. In this paper, we…