Randomized A/B tests allow causal estimation without confounding but are often under-powered. This paper uses a new dataset, including over 250 randomized comparisons conducted in an online learning platform, to illustrate a method combining data from A/B tests with log data from users who were not in the experiment. Inference remains exact and…

Multidimensional Item Response Theory (MIRT) is widely used in educational and psychological assessment and evaluation. With the increasing size of modern assessment data, many existing estimation methods become computationally demanding and hence they are not scalable to big data, especially for the multidimensional three-parameter and…

A wide range of machine-learning-based approaches have been developed in the past decade, increasing our ability to accurately model nonlinear and nonadditive response surfaces. This has improved performance for inferential tasks such as estimating average treatment effects in situations where standard parametric models may not fit the data well.…

Listening to music activates representations of movement and social agents. Why? We test whether causal reasoning plays a role, and find that from childhood, people can intuitively reason about how musical sounds were generated, inferring the events and agents that caused the sounds. In Experiment 1 (N = 120, pre-registered), 6-year-old children…

To reach rational conclusions, we often draw inferences about the evidence that supports one solution over another. This evidence can be "direct" and indicate why one option is correct, or "indirect" and indicate why the alternative option is incorrect. Understanding how young children interpret and use different types of…

The standard methodology for many large-scale assessments in education involves regressing latent variables on numerous contextual variables to estimate proficiency distributions. To reduce the number of contextual variables used in the regression and improve estimation, we propose and evaluate principal component analysis on the covariance matrix…

This study examined the teacher-child interactions during shared book reading (SBR) in the domain of early mathematics. We investigated preschool teachers' and children's talk in terms of (1) communicative acts, mathematical focus, and level of abstraction (literal versus inferential), (2) the sequential relation between teacher's talk and…

Background: Executive function (EF) is significantly associated with reading comprehension outcomes, yet the interaction between EF and critical language skills (including vocabulary, morphological awareness (MA) and syntactic knowledge), across these levels of reading comprehension (literal, inferential and evaluative comprehension) has rarely…

Background/purpose: This study aims to examine the inferential statistical literacy of mathematics education students based on their cognitive styles--field-dependent (FD) and field-independent (FI). Inferential statistical literacy involves not only understanding statistical concepts such as hypothesis testing and parameter estimation but also…

Recent studies on text sequencing found learning advantages of interleaving over blocking in terms of high-level inferences. We conducted a 2 × 2 × 2 mixed factorial experiment with college students (n = 117) by manipulating text sequence (interleaved vs. blocked) and self-questioning activity while reading (spontaneous vs. prompted) between…

Research suggests exposure to misinformation continues to impact belief and reasoning, even if that misinformation has been corrected (referred to as the "Continued Influence Effect, CIE"). The proposed experiment explores two potentially important factors that may impact the effect: (a) learner age and (b) length of delay between…

It is not always clear how to adjust for control data in causal inference, balancing the goals of reducing bias and variance. We show how, in a setting with repeated experiments, Bayesian hierarchical modeling yields an adaptive procedure that uses the data to determine how much adjustment to perform. The result is a novel analysis with increased…

Background: Meta-analysis is considered to be the gold standard for evidence synthesis. It involves combining data from multiple independent sources to produce a summary estimate with improved precision. Traditionally, meta-analysis methods have been applied to a large collection of studies, and past research efforts have indicated its numerous…

The primary purpose of this study was to systematically review the literature regarding the characteristics, use, and implementation of an emerging assessment methodology, "SRL microanalysis." Forty-two studies across diverse samples, contexts, and research methodologies met inclusion criteria. The majority of studies used microanalysis…

Measurement error affects the quality of population orderings of an index and, hence, increases the misclassification of the poor and the non-poor groups and affects statistical inferences from binary regression models. Hence, the conclusions about the extent, profile, and distribution of poverty are likely to be misleading. However, the size and…