Lexical inference refers to the ability to make informed guesses about the meaning of an unknown word. This inferencing ability is affected by learner-related (i.e., morphological awareness and vocabulary knowledge) and language-related (i.e., word semantic transparency) factors. Previous studies have shown that these factors play independent…

Two approaches to causal inference in the presence of non-random assignment are presented: The Propensity Score approach which pseudo-randomizes by balancing groups on observed propensity to be in treatment, and the Endogenous Treatment Effects approach which utilizes systems of equations to explicitly model selection into treatment. The three…

This study explores how feature salience and feature centrality influence inductive generalization in 4- and 5-year-old children and adults. Recent reports indicate that enhancing the salience of a feature--specifically, a creature's head--by making it move shifts children's inductions so that they ignore labels and make inferences that are…

When estimating an average treatment effect with observational data, it's possible to get an unbiased estimate of the causal effect if all confounding variables are observed and reliably measured. In education, confounding variables are often latent constructs. Covariate selection methods used in causal inference applications assume that all…

Random sampling and random allocation are essential processes in the practice of inferential statistics. These processes ensure that all members of a population are equally likely to be selected, and that all possible allocations in an experiment are equally likely. It is these characteristics that allow the validity of the subsequent calculations…

This study introduces inferentialism and, particularly, the "Game of Giving and Asking for Reasons" (GoGAR), as a new theoretical perspective for investigating qualities of procedural and conceptual knowledge in mathematics. The study develops a framework in which procedural knowledge and conceptual knowledge are connected to limited and…

Basic knowledge of ideas of causal inference can help students to think beyond data, that is, to think more clearly about the data generating process. Especially for (maybe big) observational data, qualitative assumptions are important for the conclusions drawn and interpretation of the quantitative results. Concepts of causal inference can also…

Accompanied by increasing demands on school administrator preparation and rapid development of computer technology, educational statistics courses are exposed to unprecedented pressures for changing both curriculum content and computing platforms. In this article, the intended curriculum is reviewed according to data analysis expectations from…

Survival analysis is an important analytic method in the social and medical sciences. Also known under the name time-to-event analysis, this method provides parameter estimation and model fitting commonly conducted via maximum-likelihood. Bayesian survival analysis offers multiple advantages over the frequentist approach for measurement…

Peirce made repeated attempts to clarify what he understood as abduction or creative reasoning in scientific discoveries. In this article, we draw on past and recent scholarship on Peirce's later accounts of abduction to put a case for how teachers can apply his ideas productively to elicit and guide student creative reasoning in the science…

In this digital ITEMS module, Dr. Roy Levy describes Bayesian approaches to psychometric modeling. He discusses how Bayesian inference is a mechanism for reasoning in a probability-modeling framework and is well-suited to core problems in educational measurement: reasoning from student performances on an assessment to make inferences about their…

This study explored the social-cognitive profile of 173 adults referred for an autism assessment. We considered key dimensional traits (autism, empathy and systemising) to understand social cognition in adults diagnosed with an autism spectrum condition compared with those who were referred for, but did not receive a diagnosis. There were no…

In this paper, we address the following questions: What misconceptions do high school students exhibit in their first encounter with significance test problems through a repeated sampling approach? Which theory or framework could explain the presence and features of such patterns? With brief prior instruction on the use of Fathom software to…

This study investigated the connection between translanguaging and reading comprehension of Filipino ESL intermediate learners. The respondents were intermediate pupils enrolled in the selected central schools in Bicol, Philippines. The respondents' ages range from 8 to 12 years old, and 124 students (27.55%) were males while 326 students (72.44%)…

Understanding whether or not different types of students master various attributes can aid future learning remediation. In this study, two-level diagnostic classification models (DCMs) were developed to represent the probabilistic relationship between external latent classes and attribute mastery patterns. Furthermore, variational Bayesian (VB)…