Objective: Community colleges have considerable potential to grow the number of individuals who complete STEM baccalaureate degrees and to broaden access to educational opportunities in STEM. However, efforts to tap this potential have been hampered by nagging questions about whether community colleges prepare students adequately for advanced STEM…

Despite the plethora of m-learning acceptance studies, few have tackled the importance of examining the actual use of m-learning systems from the lenses of social influence, expectation-confirmation, and satisfaction. Additionally, most of the prior technology adoption literature tends to use the structural equation modeling (SEM) technique in…

Descriptive analyses of socially important or theoretically interesting phenomena and trends are a vital component of research in the behavioral, social, economic, and health sciences. Such analyses yield reliable results when using representative individual participant data (IPD) from studies with complex survey designs, including educational…

Lectures and seminars increasingly strive for continuous interactions between learners and the instructor. I study whether the communication program Slack contributes to these goals by analyzing daily activity statistics in methodological and project-based postgraduate courses at an Irish university. Both semester-long courses were taught online…

Purpose: Bayesian-based models for diagnosis are common in medicine but have not been incorporated into identification models for dyslexia. The purpose of the present study was to evaluate Bayesian identification models that included a broader set of predictors and that capitalized on recent developments in modeling the prevalence of dyslexia.…

Over the last decades, it has been shown that teaching and learning statistics is complex, regardless of the teaching methodology. This research presents the different learning profiles identified in a group of future Primary Education (PE) teachers during the study of the Statistics block depending on the methodology used and gender, where the…

Understanding the educational aspirations of diverse groups among statistics majors provides insight into the discipline of statistics. This study utilizes multi-institution data from the 2019 and 2020 administrations of the National Survey of Student Engagement (NSSE) to explore educational aspirations for statistics majors through comparisons to…

This study investigated the understanding of the effects of online self-directed learning readiness (OSDLR) on academic achievement and course satisfaction for online learning statistics through the mediating variables of self-efficacy to learn statistics (SELS) and 2x2 achievement goal orientation. The current study sought to create awareness and…

The development of assessments as part of the funded LOCUS project is described. The assessments measure students' conceptual understanding of statistics as outlined in the GAISE PreK-12 Framework. Results are reported from a large-scale administration to 3,430 students in grades 6 through 12 in the United States. Items were designed to assess…

Hierarchical linear modeling (HLM) is a useful tool when analyzing data collected from groups. There are many decisions to be made when constructing and estimating a model in HLM including which estimation technique to use. Three of the estimation techniques available when analyzing data with HLM are maximum likelihood, restricted maximum…

We consider an ordinal regression model with latent variables to investigate the effects of observable and latent explanatory variables on the ordinal responses of interest. Each latent variable is characterized by correlated observed variables through a confirmatory factor analysis model. We develop a Bayesian adaptive lasso procedure to conduct…

Large-scale surveys typically exhibit data structures characterized by rich mutual dependencies between surveyed variables and individual-specific skip patterns. Despite high efforts in fieldwork and questionnaire design, missing values inevitably occur. One approach for handling missing values is to provide multiply imputed data sets, thus…

This article illustrates five different methods for estimating Angoff cut scores using item response theory (IRT) models. These include maximum likelihood (ML), expected a priori (EAP), modal a priori (MAP), and weighted maximum likelihood (WML) estimators, as well as the most commonly used approach based on translating ratings through the test…

In psychology and the behavioral sciences generally, the use of the hierarchical linear model (HLM) and its extensions for discrete outcomes are popular methods for modeling clustered data. HLM and its discrete outcome extensions, however, are certainly not the only methods available to model clustered data. Although other methods exist and are…

This article describes Gapminder, a dynamic time-series graph that can be found at http://www.gapminder.org. Gapminder was created by a team of developers (Rosling, Ronnlund, and Rosling 2005) to create beautiful, interactive graphs of otherwise lifeless numbers. Their goal is increased use and understanding of statistics and data that…