Policy changes are an ever-present part of education. In 2019, legislators upended over two decades of gifted education policy in Texas with the removal of direct funding for gifted education. In its wake, the removal of funding shook educator morale and created uncertainty as to the future of gifted education in the state. In this article, we…

We report the results of a study on informal covariate statistical reasoning conducted with 22 students (aged 16 and 18 years). We designed and implemented a task in a digital technology environment to introduce the line of best fit. The task design having elements that foresee misconceptions reported in the literature, and by focusing on four…

Statistical modeling continues to gain prominence in the secondary curriculum, and recent recommendations to emphasize data science and computational thinking may soon position algorithmic models into the school curriculum. Many teachers' preparation for and experiences teaching statistical modeling have focused on probabilistic models.…

The formula for the variance of a binomial distribution is both concise and elegant. However, it is often taught without reference to the underlying reasoning. That being the case, is it important, or useful, to understand why this formula can be used to calculate the requisite result? In this article, the author demonstrates a teaching sequence…

Kaggle is a data modeling competition service, where participants compete to build a model with lower predictive error than other participants. Several years ago they released a simplified service that is ideal for instructors to run competitions in a classroom setting. This article describes the results of an experiment to determine if…

In the past 10 years, new data science courses and programs have proliferated at the collegiate level. As faculty and administrators enter the race to provide data science training and attract new students, the road map for teaching data science remains elusive. In 2019, 69 college and university faculty teaching data science courses and…

Temporality-driven covariate classification had limited impact on: the specification of directed acyclic graphs (DAGs) by 85 novice analysts (medical undergraduates); or the risk of bias in DAG-informed multivariable models designed to generate causal inference from observational data. Only 71 students (83.5%) managed to complete the…

This article proposes a general parametric item response theory approach for identifying sources of misfit in response patterns that have been classified as potentially inconsistent by a global person-fit index. The approach, which is based on the weighted least squared regression of the observed responses on the model-expected responses, can be…

Our study uses data from the Wabash National Study of Liberal Arts Education to interrogate the affinity disciplines hypothesis through students' perceptions of faculty use of six of Chickering and Gamson's ("AAHE Bull" 39(7):3-7, 1987) principles of good practice for undergraduate education. We created a proportional scale based on…

Empirical evidence attests the impact that career image has on objective career success, yet little is known of how career practitioners conceptualise and operationalise this information. This article presents the quantitative findings of an online survey of career practitioners (n = 399, 74% female, 89% white and 75% from the U.K.) exploring…

Over the past 20 years, a movement to offer greater access and choice in public education has begun to challenge the traditional attendance boundary school system. Public school choice provides an opportunity for parents who do not have the resources to change attendance boundaries but who want additional public school options. Proponents argue…

Publication bias distorts the available empirical evidence and misinforms policymaking. Evidence of publication bias is mounting in virtually all fields of empirical research. This paper proposes the endogenous kink (EK) meta-regression model as a novel method of publication bias correction. The EK method fits a piecewise linear meta-regression of…

Comparative Judgement (CJ) aims to improve the quality of performance-based assessments by letting multiple assessors judge pairs of performances. CJ is generally associated with high levels of reliability, but there is also a large variation in reliability between assessments. This study investigates which assessment characteristics influence the…

Heat maps have become ubiquitous in the media, yet students are rarely exposed to them and their inherent limitations and potential for misleading consumers. This article makes a case for exposing students to them in statistics instruction at the secondary and tertiary level.

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…