The COVID-19 pandemic outbreak has upended the educational system worldwide, possibly with severe long-term consequences as most training institutions were forced to move to an online environment. Given the sudden transition to remote education, the main objective of this contribution is to evaluate the impact of distance education on examination…

Population adjustment methods such as matching-adjusted indirect comparison (MAIC) are increasingly used to compare marginal treatment effects when there are cross-trial differences in effect modifiers and limited patient-level data. MAIC is based on propensity score weighting, which is sensitive to poor covariate overlap and cannot extrapolate…

This article develops a machine learning methodology to analyse the relationship between university accreditation and student experience. It is applied to 98 university accreditations conducted by the Quality Assurance Agency (QAA) in the UK in 2012-2018, and 263,025 university ratings in three categories posted by students on the website…

A regression model of predictor trade-offs is described. Each regression parameter equals the expected change in Y obtained by trading 1 point from one predictor to a second predictor. The model applies to predictor variables that sum to a constant T for all observations; for example, proportions summing to T=1.0 or percentages summing to T=100…

Two meta-analyses assessed whether the relations between reading and mathematics outcomes could be explained through overlapping skills (e.g., systems for word and fact retrieval) or domain-general influences (e.g., top-down attentional control). The first (378 studies, 1,282,796 participants) included weighted random-effects meta-regression…

Field learning is fundamental in geoscience, but cost, accessibility, and other constraints limit equal access to these experiences. As technological advances afford ever more immersive and student-centered virtual field experiences, they are likely to have a growing role across geoscience education. They also serve as an important tool for…

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…

Data in social and behavioral sciences typically contain measurement errors and also do not have predefined metrics. Structural equation modeling (SEM) is commonly used to analyze such data. This article discuss issues in latent-variable modeling as compared to regression analysis with composite-scores. Via logical reasoning and analytical results…

In the logistic regression (LR) procedure for differential item functioning (DIF), the parameters of LR have often been estimated using maximum likelihood (ML) estimation. However, ML estimation suffers from the finite-sample bias. Furthermore, ML estimation for LR can be substantially biased in the presence of rare event data. The bias of ML…

It is widely believed that regression models for binary responses are problematic if we want to compare estimated coefficients from models for different groups or with different explanatory variables. This concern has two forms. The first arises if the binary model is treated as an estimate of a model for an unobserved continuous response and the…

Ordinary least squares (OLS) regression provides optimal linear predictions of a dependent variable, y, given an independent variable, x, but OLS regressions are not symmetric or reversible. In order to get optimal linear predictions of x given y, a separate OLS regression in that direction would be needed. This report provides a least squares…

Universities and students increasingly view internships as valuable learning experiences that complement and augment academic classroom learning. Students benefit from the opportunity to apply recently acquired knowledge in the 'real world,' to identify knowledge gaps that they should address in future coursework, and to secure a post-graduation…

This study documents the effects of social inequality on different dimensions of lexical comprehension in Spanish-speaking Argentinian toddlers, a population in which socioeconomic differences are more striking than in previously studied populations. Using a performance-based forced-choice lexical recognition task implemented on a tablet, an…

Machine learning, a subdomain of artificial intelligence, is a widespread technology that is molding how chemists interact with data. Therefore, it is a relevant skill to incorporate into the toolbox of any chemistry student. This work presents a workshop that introduces machine learning for chemistry students based on a set of Python notebooks…

Teacher attrition is a chronic challenge facing many education systems, and has been shown to negatively impact education quality and equity. Common explanations rooted in occupational choice theory identify pecuniary and non-pecuniary rewards as critical factors in motivating and retaining teachers. Using China Household Income Project (CHIP)…