Data science is collaborative and its students should learn teamwork and collaboration. Yet it can be a challenge to fit the teaching of such skills into the data science curriculum. Team-Based Learning (TBL) is a pedagogical strategy that can help educators teach data science better by flipping the classroom to employ small-group collaborative…

Monte Carlo methods are an accepted methodology in regards to generation critical values for a Maximum test. The same methods are also applicable to the evaluation of the robustness of the new created test. A table of critical values was created, and the robustness of the new maximum test was evaluated for five different distributions. Robustness…

This dissertation's idea began with my class notes and questions in the statistics courses I attended in my doctoral program. These notes and questions originally were about the concepts of the bell shape, statistical distribution, and hypothesis testing. They then became my inquiries of p-values because what I learned in the courses about how the…

With the development of technology-enhanced learning platforms, eye-tracking biometric indicators can be recorded simultaneously with students item responses. In the current study, visual fixation, an essential eye-tracking indicator, is modeled to reflect the degree of test engagement when a test taker solves a set of test questions. Three…

Multilevel data are a reality for many disciplines. Currently, although multiple options exist for the treatment of multilevel data, most disciplines strictly adhere to one method for multilevel data regardless of the specific research design circumstances. The purpose of this Monte Carlo simulation study is to compare several methods for the…

A procedure that can be used to evaluate the variance inflation factors and tolerance indices in linear regression models is discussed. The method permits both point and interval estimation of these factors and indices associated with explanatory variables considered for inclusion in a regression model. The approach makes use of popular latent…

Young and Holsteen (YH) introduce a number of tools for evaluating model uncertainty. In so doing, they are careful to differentiate their method from existing forms of model averaging. The fundamental difference lies in the way in which the underlying estimates are weighted. Whereas standard approaches to model averaging assign higher weight to…

Cognitive modelling shares many features with statistical modelling, making it seem trivial to borrow from the practices of robust Bayesian statistics to protect the practice of robust cognitive modelling. We take one aspect of statistical workflow--prior predictive checks--and explore how they might be applied to a cognitive modelling task. We…

Persistent underrepresentation of Black and Hispanic Statistics degree holders relative to the U.S. population occurs at all levels in post-secondary education, contributing to the underrepresentation of Black and Hispanic Bio/Statisticians. Attempting to address this inequity before the undergraduate level, Memorial Sloan Kettering (MSK)'s Bridge…

The detection of differential item functioning (DIF) is important in psychological and behavioral sciences. Standard DIF detection methods perform an item-by-item test iteratively, often assuming that all items except the one under investigation are DIF-free. This article proposes a Bayesian adaptive Lasso method to detect DIF in graded response…

This paper reports on teachers developing their own data literacy and then acting as data coaches for colleagues in their schools. The 13 teachers from 7 schools in the study analysed standardised data using a data conversation protocol to identify students with significant mathematical misconceptions. They then took data-informed action with…

The rapid advancement of educational technologies in recent decades has underscored the increasing importance of digital literacy (DL) as a core competency for all students, as recognised in various educational policies and programs. Evaluating students' DL is crucial for providing valuable insights to guide future educational initiatives. This…

Despite growing interest in task-based language teaching (TBLT), limited empirical work has examined how different rhetorical task types influence second language (L2) writing development, especially in relation to affective variables, such as writing anxiety. Existing research in TBLT has largely focused on cognitive dimensions, often neglecting…

Threshold concepts are transformative elements of domain knowledge that enable those who attain them to engage domain tasks in a more sophisticated way. Existing research tends to focus on the identification of threshold concepts within undergraduate curricula as challenging concepts that prevent attainment of subsequent content until mastered.…

Research courses are part of many higher education curricula. However, students' attitudes towards statistics and research courses tend to be negative. One way to measure students' attitude is with the Revised-Attitudes Towards Research scale (R-ATR). The current study examined: (1) the internal reliability of the R-ATR, (2) the attitude of Dutch…