For assessments that use different forms in different administrations, equating methods are applied to ensure comparability of scores over time. Ideally, a score scale is well maintained throughout the life of a testing program. In reality, instability of a score scale can result from a variety of causes, some are expected while others may be…

Score differencing is one of the six categories of statistical methods used to detect test fraud (Wollack & Schoenig, 2018) and involves the testing of the null hypothesis that the performance of an examinee is similar over two item sets versus the alternative hypothesis that the performance is better on one of the item sets. We suggest, to…

Jokes, cartoons, songs, videos, and quotes can be useful ways to engage students in discussion and learning key concepts about polling.

In this article, we discuss our attempt to teach applied statistics techniques typically taught in advanced courses, such as clustering and principal component analysis, to a non-mathematical educated audience. Considering the negative attitude and inclination toward mathematical disciplines of our students we introduce them to our topics using…

Score differencing is one of six categories of statistical methods used to detect test fraud (Wollack & Schoenig, 2018) and involves the testing of the null hypothesis that the performance of an examinee is similar over two item sets versus the alternative hypothesis that the performance is better on one of the item sets. We suggest, to…

While computing has become an important part of the statistics field, course offerings are still influenced by a legacy of mathematically centric thinking. Due to this legacy, Bayesian ideas are not required for undergraduate degrees and have largely been taught at the graduate level; however, with recent advances in software and emphasis on…

This paper addresses a common challenge with computational cognitive models: identifying parameter values that are both theoretically plausible and generate predictions that match well with empirical data. While computational models can offer deep explanations of cognition, they are computationally complex and often out of reach of traditional…

Purpose: Clinicians depend on the accuracy of research in the speech, language, and hearing sciences to improve assessment and treatment of patients with communication disorders. Although this work has contributed to great advances in clinical care, common statistical misconceptions remain, which deserve closer inspection in the field. Challenges…

Student academic success depends on a variety of factors, one of which is self-regulation of learning. An important part of self-regulation involves selecting from a myriad of course resources available and planning to use those resources. This study explores the use of an online tool to help undergraduate students improve self-regulation by…

Statistics anxiety is a prevalent form of anxiety experienced by students during statistics lectures or when conducting statistical analysis. This anxiety negatively impacts their performance and enjoyment of the subject. The present study investigates the relationship between lecturer support and undergraduate students' statistics anxiety, and…

The issue of model uncertainty has been gaining interest in education and the social sciences community over the years, and the dominant methods for handling model uncertainty are based on Bayesian inference, particularly, Bayesian model averaging. However, Bayesian model averaging assumes that the true data-generating model is within the…

Item compromise has long posed challenges in educational measurement, jeopardizing both test validity and test security of continuous tests. Detecting compromised items is therefore crucial to address this concern. The present literature on compromised item detection reveals two notable gaps: First, the majority of existing methods are based upon…

In today's data-driven society, strong statistical literacy is essential for all citizens. Within the educational context, teachers play a crucial role in developing students' statistical competencies. However, pre-service teachers' attitudes toward statistics can impact how they approach its instruction. This study examines changes in future…

In this study, we applied elastic-net logistic regression to explore critical predictors of students' mathematics and science levels using data from eighth-grade students in the 2019 Trends in International Mathematics and Science Study (TIMSS). The elastic-net approach, a machine learning based approach combining Ridge and Least Absolute…

Over the last decade, reform in science education has placed an emphasis on the science practices as a way to engage students in the process of science and improve scientific literacy. A critical component of developing scientific literacy is learning to apply quantitative reasoning to authentic scientific phenomena and problems. Students need…