Research on students' attitudes toward statistics has attracted many statistics instructors and statistics education researchers. In this study, we use confirmatory factor analysis to analyze data collected from an introductory statistics course using the Survey of Attitudes toward Statistics. The results suggest that the items and six factors are…

Researchers have documented many misconceptions students hold about sampling variability. This study takes a different approach--instead of identifying shortcomings, we consider the productive reasoning pieces students construct as they reason about sampling distributions. We interviewed eight undergraduate students newly enrolled in an…

The purpose of this study was to test three pathways from achievement goals to academic performance in statistics classes. Participants were 247 undergraduate students in psychology taking an introductory course on statistics. They completed questionnaires shortly after the midterm, and their final grades were provided by their professors at the…

Simulation is an effective tool for analyzing probability models as well as for facilitating understanding of concepts in probability and statistics. Unfortunately, implementing a simulation from scratch often requires users to think about programming issues that are not relevant to the simulation itself. We have developed a Python package called…

All studies with randomized controlled experiments (scientific studies) on the effectiveness of SAT test preparation courses were analyzed to find SAT prep's true effectiveness (the average point change to average course hours ratio). The scientific studies complete with both known average point change and known average course length (complete…

Between 1983 and 1993, grade 7/8 to grade 12 apparent retention rates more than doubled and secondary schools developed vocational education and training (VET) programmes as alternative pathways through secondary school. Previous research indicates that participation in VET programmes is associated with having low-educated parents and/or attending…

Despite recent interest in flipped classrooms, rigorous research evaluating their effectiveness is sparse. In this study, the authors implement a randomized controlled trial to evaluate the effect of a flipped classroom technique relative to a traditional lecture in an introductory undergraduate econometrics course. Random assignment enables the…

What teachers teach, how they teach it and when they teach it should be guided by the curriculum. This paper focuses on teachers' reports about how they integrate the curriculum documentation in teaching mathematics and statistics concepts. Questionnaires containing both Likert scale and closed and open-ended questions were administered to 75…

Over the most recent two decades, federal policy has urged high schools to embed applied science, technology, engineering, and mathematics (STEM) courses into the curriculum to reinforce concepts learned in traditional math and science classes as well as to motivate students' interests and long-term pursuits in STEM areas. While prior research has…

This chapter outlines conceptual and mathematical underpinnings of local indicators of spatial association, or LISA statistics. An empirical application shows how LISAs can be used to detect localized spatial processes impacting students and campuses.

This study examines the impact of joining a National Panhellenic Conference sorority on first-year retention. We compiled and analyzed data for first-year sorority members from 86 chapters using institutional records at sixteen 4-year colleges and universities. A total of 4,243 cases comprised the data set, which included records for 2,104 members…

This study examined the use of Bayesian analysis methods for the estimation of item parameters in a two-parameter logistic item response theory model. Using simulated data under various design conditions with both informative and non-informative priors, the parameter recovery of Bayesian analysis methods were examined. Overall results showed that…

Brian Kotz is Professor of Mathematics and Statistics at Montgomery College. He is a former member of the American Statistical Association/American Mathematical Association of Two-Year Colleges (ASA)/(AMATYC) Joint Committee and the current chair of the AMATYC Data Science Subcommittee. This interview took place via email on November 23,…

In this digital ITEMS module, we introduce the framework of nonparametric item response theory (IRT), in particular Mokken scaling, which can be used to evaluate fundamental measurement properties with less strict assumptions than parametric IRT models. We walk through the key distinction between parametric and nonparametric models, introduce the…

With this article, we propose using a Bayesian multilevel latent class (BMLC; or mixture) model for the multiple imputation of nested categorical data. Unlike recently developed methods that can only pick up associations between pairs of variables, the multilevel mixture model we propose is flexible enough to automatically deal with complex…