Applying qualitative comparative analysis (QCA) to large Ns relaxes researchers' case-based knowledge. This is problematic because causality in QCA is inferred from a dialogue between empirical, theoretical, and case-based knowledge. The lack of case-based knowledge may be remedied by various robustness tests. However, being a case-based method,…

Statistical literacy is a skill that will be required by all students, but only limited insights exist into how it can be developed in middle schools. Research is required that identifies design principles and provides didactic materials for developing statistical literacy in actual middle school classrooms, meaning classrooms in which statistics…

A vast majority of social science students experience statistics anxiety in their statistics class, a course often perceived as the most difficult one of their academic paths. The present study examines the role of attitudes towards statistics, cognitive emotion regulation strategies, and satisfaction of psychological needs in the prediction of…

The computerized adaptive tests (CAT) apply an adaptive process in which the items are tailored to individuals' ability scores. The multidimensional CAT (MCAT) designs differ in terms of different item selection, ability estimation, and termination methods being used. This study aims at investigating the performance of the MCAT designs used to…

This article discusses the development of an interactive online textbook for undergraduate teaching, in response to moving teaching online due to COVID-19. The development took place initially for a university with less than 5% of students studying online in 2019. The online textbook was incorporated into a large, diverse, multidisciplinary and…

Governmental and educational organizations have pointed out that students coming into the biological sciences require stronger skills in statistics and data modeling that are not usually addressed in typical engineering-based calculus courses. Our work here documents how faculty in biology and mathematics addressed this issue at a large urban…

Biology students need analytical and critical thinking skills to analyze data and apply their knowledge to real-life situations. To meet this growing need while helping students to discover the relevance of learning through applications, we created an academic learning community (LC) between Ecology and Biostatistics courses. Selected case-studies…

It is recommended that teacher-scholars of data science adopt reproducible workflows in their research as scholars and teach reproducible workflows to their students. In this article, we propose a third dimension to reproducibility practices and recommend that regardless of whether they teach reproducibility in their courses or not, data science…

This article synthesizes ideas that emerged over the course of a 10-week symposium titled "Teaching Reproducible Research: Educational Outcomes" https://www.projecttier.org/fellowships-and-workshops/2021-spring-symposium that took place in the spring of 2021. The speakers included one linguist, three political scientists, seven…

In this article we present our findings regarding the challenges of offering a massive university's free-of-charge online course. The online course "Introduction to data science (with R)" was offered by one professor at the Federal University of Sao Paulo, Osasco Campus, Brazil, from 11 to 28 of January of 2022, to 680 students from all…

This study aims to identify some perceived gaps in a selection of statistical skills and software abilities of professors of education in United States colleges and universities. In addition to a general U. S. sample, a sample of education professors in Historically Black Colleges and Universities (HBCUs) was examined in order to understand their…

Data analysis is one of the most popular fields of mathematics and includes statistics and probability. These two mathematical domains are some of the most well-known, influencing everyday life and the various sciences. Their teaching lays the foundation for primary education and culminates in secondary education. Probability and statistics are…

The goal of the paper is to pay attention to some important techniques and approaches including adequate designations as a tool for unambiguous understanding and a key to success in solving problems, vivid visual images as a mnemonic techniques, and special formulas as a universal tool for solving typical problems, when teaching medical students…

Many of the analytical models commonly used in educational research often aim to maximize explained variance and identify variable importance within models. These models are useful for understanding general ideas and trends, but give limited insight into the individuals within said models. Data envelopment analysis (DEA), is a method rooted in…

This study used a propensity score approach to estimate treatment effects in a multilevel setting. The propensity score approach involves the estimation of propensity scores for covariate balancing and the estimation of treatment effects. This study aimed at understanding how propensity scores estimated through a simple logistic regression compare…