A Statistics Practicum course is offered as another option besides an internship or research experience for students to fulfill a required statistics major capstone experience. This article discusses the first and fourth offering of this practicum course, which provides a unique perspective on the initial implementation of the course and its…

This study investigates the support provided using technology for learning the notion of normal distribution in high school students through the implementation of a teaching experiment. A strategy was designed and implemented using Fathom software as the main teaching resource. Data analysis focused on the role of the use of technology in student…

The education landscape in the United States has been changing rapidly in recent decades: student populations have become more diverse; there has been an explosion of data sources; there is an intensified focus on diversity, equity, inclusion, and accessibility; educators and policy makers at all levels want more and better data for evidence-based…

This dissertation project explores the potential for using an inferential statistics test (t-tests) within an existing writing program assessment design. The purpose of using inferential statistics is to provide several perspectives on a data set collected using the existing assessment design thereby improving what a writing program administrator…

Background: Regression Discontinuous Design (RDD) is widely used in educational studies. Through RDD, researchers can obtain unbiased results when Randomized Experimental Design (RED) is inaccessible. Compared to RED, the RDD only requires a cut score variable (continuous) and a cutoff value to assign students to the treatment or control groups.…

This article provides an overview of different computational options for inference following normal theory maximum likelihood (ML) estimation in structural equation modeling (SEM) with incomplete normal and nonnormal data. Complete data are covered as a special case. These computational options include whether the information matrix is observed or…

Conventionally, regression discontinuity analysis contrasts a univariate regression's limits as its independent variable, "R," approaches a cut point, "c," from either side. Alternative methods target the average treatment effect in a small region around "c," at the cost of an assumption that treatment assignment,…

Despite broad applications of growth curve models, few studies have dealt with a practical issue -- nonnormality of data. Previous studies have used Student's "t" distributions to remedy the nonnormal problems. In this study, robust distributional growth curve models are proposed from a semiparametric Bayesian perspective, in which…

Since 2011, the Alaska Performance Scholarship (APS) has awarded Alaska students who excel in high school with more than $100 million in scholarships to help cover the cost of in-state postsecondary education. This report covers: (1) APS Eligibility & Use; (2) High School Outcomes; (3) Postsecondary Outcomes; and (4) Alaska Residency and…

Statistical analysis of categorical data often relies on multiway contingency tables; yet, as the number of categories and/or variables increases, the number of table cells with few (or zero) observations also increases. Unfortunately, sparse contingency tables invalidate the use of standard goodness-of-fit statistics. Limited-information fit…

We investigated the relationship between category learning and domain-general object recognition ability (o). We assessed this relationship in a radiological context, using a category learning test in which participants judged whether white blood cells were cancerous. In study 1, Bayesian evidence negated a relationship between o and category…

Previous research has shown that students form fragmented understandings about variability even after instruction and that these primitive notions function as obstacles to a robust understanding of variability. To investigate the effect of disruptions to students' primitive notions of variability, we examined undergraduate students' reasoning…

Cognitive diagnosis models (CDMs) are the statistical framework for cognitive diagnostic assessment in education and psychology. They generally assume that subjects' latent attributes are dichotomous--mastery or nonmastery, which seems quite deterministic. As an alternative to dichotomous attribute mastery, attention is drawn to the use of a…

Change-point analysis (CPA) is a method for detecting abrupt changes in parameter(s) underlying a sequence of random variables. It has been applied to detect examinees' aberrant test-taking behavior by identifying abrupt test performance change. Previous studies utilized maximum likelihood estimations of ability parameters, focusing on detecting…

Pedigree problems are typical tasks in school genetics classes. However, they are perceived as difficult and often are not successfully completed. Therefore, the purpose of this study is to determine relevant factors that might have an impact on success in pedigree analysis. Based on previous research, we investigate the influence of the…