Mixed Membership Models (MMMs) are a popular family of latent structure models for complex multivariate data. Instead of forcing each subject to belong to a single cluster, MMMs incorporate a vector of subject-specific weights characterizing partial membership across clusters. With this flexibility come challenges in uniquely identifying,…

This short article continues the exploration of the Common Online Data Analysis Platform (CODAP) and statistics begun in the previous article "Statistical Investigations and CODAP, Part 1: EDA." In Part 2, the author discusses the teaching of statistical inference focusing on activities for the senior secondary years. In particular, the…

Bayesian methods seem a natural choice for combining sources of evidence in meta-analyses. However, in practice, their sensitivity to the choice of prior distribution is much less attractive, particularly for parameters describing heterogeneity. A recent non-Bayesian approach to fixed-effects meta-analysis provides novel ways to think about…

The purpose of this study is to further our understanding of orchestrating math-talk with digital technology. The technology used is common in Swedish mathematics classrooms and involves personal computers, a projector directed towards a whiteboard at the front of the class and software programs for facilitating communication and collective…

Most students have interacted with scientific representations that are used as teaching resources in schools. Often these external representations present challenges for understanding. By utilizing a framework based on an inferential, epistemic approach to scientific representations, we have analyzed students' representational constructions of the…

We are sometimes forced to use the Interrupted Time Series (ITS) design as an identification strategy for potential policy change, such as when we only have a single treated unit and cannot obtain comparable controls. For example, with recent county- and state-wide criminal justice reform efforts, where judicial bodies have changed bail setting…

Bayesian inference for structural equation models (SEMs) is increasingly popular in social and psychological sciences owing to its flexibility to adapt to more complex models and the ability to include prior information if available. However, there are two major hurdles in using the traditional Bayesian SEM in practice: (1) the information nested…

Multisite field experiments using the (generalized) randomized block design that assign treatments to individuals within sites are common in education and the social sciences. Under this design, there are two possible estimands of interest and they differ based on whether sites or blocks have fixed or random effects. When the average treatment…

The influence of fonts in marketing education may be underestimated as font usage/selection may benefit both department programs and courses in terms of attracting students and enhancing student learning outcomes. Across four studies, this research examines the effects of handwritten fonts on student inferences from course information. A course…

The purpose of this study was to examine the role of the causal connectivity of the statements ("low-medium-high"), elaboration question condition ("focused on the identification of main ideas-focused on the identification of speakers' emotions") and the modality of presentation of discourse ("oral-written") in the…

Using software to teach statistical inference in introductory courses opens the door for methods and practices that are more conceptually appealing to students. With an increasing number of fields requiring competency in statistics including data science, natural and social sciences, public health and more, it is crucial that we as instructors…

The following research presents the outcomes of a cohort study investigating formal thinking skills among first and second-year secondary school students. A specially crafted instrument, the Logical Thought Performance Test for Adolescents (LTPA), was employed to gauge the level of formal thought. The LTP-A assesses various aspects, including:…

Most current statistics courses include some instruction relevant to causal inference. Whether this instruction is incorporated as material on randomized experiments or as an interpretation of associations measured by correlation or regression coefficients, the way in which this material is presented may have important implications for…

Causal reasoning is a fundamental cognitive ability that enables individuals to learn about the complex interactions in the world around them. However, the mechanisms that underpin causal reasoning are not well understood. For example, it remains unresolved whether children's causal inferences are best explained by Bayesian inference or…

In today's digital context, it is essential for students' academic and personal development to improve their digital reading comprehension. A comparative analysis of digital reading comprehension between three modalities is presented: dual (multimodal), auditory, and visual (monomodal). We used an experimental design and a standardized test…