Research has indicated that undergraduate students struggle with conceptual understanding of confidence intervals, negatively impacting statistical literacy skills, and advocates have suggested the flipped classroom pedagogy as a potential solution. The purpose of this nonequivalent control group quasi-experimental study was to determine if a…

The purpose of this article is to understand how educators may support students from different backgrounds (both relatively privileged and marginalized) to participate equitably and meaningfully in ethical data science discussions. To do this, we draw on the literature regarding STEM identity formation, use Cobb and Yackel's (1996) framework for…

This study investigated how pre-service middle school mathematics teachers attend, interpret, and respond to the students' thinking about statistical concepts in a case-based teacher training environment. 25 pre-service middle school mathematics teachers participated in the study, and they were asked to make evaluations on the cases given. Based…

During COVID-19 lockdowns, online learning activities had to be developed for the Undergraduate and Masters by Coursework Bioinformatics students at RMIT University. Therefore, we designed an integrative, industry-based research assignment, which guided the students through a drug discovery project from target identification to lead optimization.…

This Report is submitted in fulfillment of the requirement in "The Career Preparation Expansion Act" (CPEA), Chapter 695 of 2018 (see Education Article § 21-206, Annotated Code of Maryland). The Maryland Longitudinal Data System (MLDS) Center and the Governor's Workforce Development Board (GWDB) are required to produce a report on high…

The increasing use of the Learning Management Systems (LMSs) is making available an ever-growing, volume of data from interactions between teachers and students. This study aimed to develop a model capable of predicting students' academic performance based on indicators of their self-regulated behavior in LMSs. To accomplish this goal, the authors…

The mixed treatment comparison (MTC) method has been proposed to combine results across trials comparing several treatments. MTC allows coherent judgments on which of the treatments is the most effective. It produces estimates of the relative effects of each treatment compared with every other treatment by pooling direct and indirect evidence. In…

Publication bias and other forms of outcome reporting bias are critical threats to the validity of findings from research syntheses. A variety of methods have been proposed for detecting selective outcome reporting in a collection of effect size estimates, including several methods based on assessment of asymmetry of funnel plots, such as the…

The article describes an assignment that makes writing-to-learn feasible in high-enrollment statistics classes. It combines the principles of structured writing with Bloom's taxonomy. The assignment helped improve related exam scores and was easy to implement and grade for instructors.

"Data science" is a discipline that provides principles, methodology, and guidelines for the analysis of data for tools, values, or insights. Driven by a huge workforce demand, many academic institutions have started to offer degrees in data science, with many at the graduate, and a few at the undergraduate level. Curricula may differ at…

Differences in rater judgments that are systematically related to construct-irrelevant characteristics threaten the fairness of rater-mediated writing assessments. Accordingly, it is essential that researchers and practitioners examine the degree to which the psychometric quality of rater judgments is comparable across test-taker subgroups.…

In order to extract the regularities underlying a continuous sensory input, the individual elements constituting the stream have to be encoded and their transitional probabilities (TPs) should be learned. This suggests that variance in statistical learning (SL) performance reflects efficiency in encoding representations as well as efficiency in…

Model selection is important in any statistical analysis, and the primary goal is to find the preferred (or most parsimonious) model, based on certain criteria, from a set of candidate models given data. Several recent publications have employed the deviance information criterion (DIC) to do model selection among different forms of multilevel item…

The negative hypergeometric distribution is often not formally studied in secondary or collegiate statistics in contexts other than drawing cards without replacement. We present a different context with the potential of engaging students in simulating and exploring data.

Individuals draw conclusions about possibilities from assertions that make no explicit reference to them. The model theory postulates that assertions such as disjunctions refer to possibilities. Hence, a disjunction of the sort, "A or B or both," where "A" and "B" are sensible clauses, yields mental models of an…