We present the design of a citizen science system that uses machine learning to guide the presentation of image classification tasks to newcomers to help them more quickly learn how to do the task while still contributing to the work of the project. A Bayesian model for tracking volunteer learning for training with tasks with uncertain outcomes is…

In dichotomous item response theory (IRT) framework, the asymptotic standard error (ASE) is the most common statistic to evaluate the precision of various ability estimators. Easy-to-use ASE formulas are readily available; however, the accuracy of some of these formulas was recently questioned and new ASE formulas were derived from a general…

Due to low success of traditional, postsecondary remediation mathematics, The Maryland Mathematics Reform Initiative First in the World Grant (MMRI-FITW) sought to develop and implement a statistics pathway as an alternative to traditional algebra-based math, to accelerate developmental mathematics students' progress into credit-bearing…

The present study aims to examine the effect of teachers' attitudes towards statistics on their attitudes towards postgraduate education. Accordingly, the "Attitude Towards Statistics Scale" and the "Attitude Towards Postgraduate Education Scale" were applied to 511 teachers working in different fields of primary schools,…

Immediacy is one of the necessary criteria to show strong evidence of treatment effect in single case experimental designs (SCEDs). With the exception of Natesan and Hedges (2017) no inferential statistical tool has been used to demonstrate or quantify it until now. We investigate and quantify immediacy by treating the change-points between the…

In this study, we re-analyze recent empirical research on replication from a meta-analytic perspective. We argue that there are different ways to define "replication failure," and that analyses can focus on exploring variation among replication studies or assess whether their results contradict the findings of the original study. We…

The integration of computer-assisted language learning (CALL) has held increasing interest among the community over the last three decades. One paper which has taken stock of this interest and modelled the factors that impact integration has been written by Hong (2010). While Hong's model has significantly contributed to understanding technology…

The increasing prevalence of online courses has highlighted the importance of digital literacy for students. This study investigates the relationship between digital literacy and academic achievement among students who participate in an online course on anatomy and physiology. The study also evaluates how different aspects of digital literacy,…

This study examined the effect of gamification on visual programming and computational thinking skills among primary school students, aiming to investigate how gamified learning environments enhance cognitive skill development and conceptual integration compared to traditional teaching methods. A quasi-experimental design was employed, involving…

We present noncompetitive adsorption as "particles in a box with one sticky wall." We start with a general model that can be modeled as a simple ordinary differential equation (ODE). To verify the ODE students run a computer simulation. The ODE's solution imperfectly fits the simulation's data. This leads to the diffusion partial…

Multidimensional item response theory (MIRT) models use data from individual item responses to estimate multiple latent traits of interest, making them useful in educational and psychological measurement, among other areas. When MIRT models are applied in practice, it is not uncommon to see that some items are designed to measure all latent traits…

Previous studies have detailed the consequence of ignoring a level of clustering in multilevel models with straightly hierarchical structures and have proposed methods to adjust for the fixed effect standard errors (SEs). However, in behavioral and social science research, there are usually two or more crossed clustering levels, such as when…

Considerable attention has been given to methods for knowledge estimation, a category of methods for automatic assessment of a student's degree of skill mastery or knowledge at a specific time. Knowledge estimation is frequently used to make decisions about when a student has reached mastery and is ready to advance to new material, but there has…

Numerous researchers have proposed methods for evaluating the quality of rater-mediated assessments using nonparametric methods (e.g., kappa coefficients) and parametric methods (e.g., the many-facet Rasch model). Generally speaking, popular nonparametric methods for evaluating rating quality are not based on a particular measurement theory. On…

The consideration of context is crucial in the discipline of statistics. In this paper, I present a Foucauldian discourse analysis (FDA) of two popular high school mathematics textbook series in the United States investigating what contextual situations they construct for the (re)use of statistics. As FDA is a novel approach in statistics…