The dramatic changes brought on by the COVID-19 pandemic have changed the way in which mathematics and statistics support is offered. Students and staff have been presented with new opportunities and challenges. One-on-one interviews were conducted late in 2020 with 23 students and staff who had experience with fully online mathematics and…

Background: We present results of the development and feasibility testing of CATCH Healthy Smiles, a school-based oral health program, among children in grades K-2 in Houston, Texas. Methods: Study design was cross-sectional (N = 2 schools; N = 125 parent-child dyads; 31 kindergarteners, 42 first graders, and 52 second graders). CATCH Healthy…

Informed by theories of reading comprehension and prior reviews of reading comprehension intervention, this meta-analysis uniquely contributes to the literature because it describes the relative effects of various approaches to comprehension intervention for struggling readers in Grades 3 through 12. Findings from 64 studies demonstrate…

This study explored the transition from secondary to postsecondary education among a national sample of students who had or had not studied music in high school. Using evidence from the High School Longitudinal Study of 2009, a nationally representative longitudinal study of 21,440 American high school students who were ninth graders in the…

Previous research indicates that long-term memory (LTM) may contribute to performance in working memory (WM) tasks. Across 3 experiments, we investigated the extent to which active maintenance in WM can be replaced by relying on information stored in episodic LTM, thereby freeing capacity for additional information in WM. First, participants…

Bayesian latent change score modeling (LCSM) was used to compare models of triannual (fall, winter, spring) change on elementary math computation and concepts/applications curriculum-based measures. Data were collected from elementary students in Grades 2-5, approximately 700 to 850 students in each grade (47%-54% female; 78%-79% White, 10%-11%…

Textbook data is essential for teaching statistics and data science methods because it is clean, allowing the instructor to focus on methodology. Ideally textbook datasets are refreshed regularly, especially when they are subsets taken from an ongoing data collection. It is also important to use contemporary data for teaching, to imbue the sense…

Theories explaining why students drop out of college have evolved to emphasize interactions between students and their college environments. While the interactionist model underscores the influence of social integration on student retention, few have examined the role of students' social networks in the decision-making process. Drawing on a survey…

As the field of K-12 data science education continues to take form, humanistic approaches to teaching and learning about data are needed. Data feminism is an approach that draws on feminist scholarship and action to humanize data and contend with the relationships between data and power. In this review paper, we draw on principles from data…

Although an increasing number of ethical data science and AI courses is available, with many focusing specifically on technology and computer ethics, pedagogical approaches employed in these courses rely exclusively on texts rather than on algorithmic development or data analysis. In this paper we recount a recent experience in developing and…

Educational institutions seek to transform the teaching-learning conditions through the use of new pedagogical and technological models. The aim of this quantitative research is to analyze the use of flipped classroom in the teaching-learning process on descriptive statistics through data science. The participants are 49 students who took the…

In this paper the authors present a unique approach to teaching introductory statistics at both the undergraduate and graduate levels. The approach uses a feature in Excel called "spinners" to dynamically adjust key variables, such as sample size, confidence levels, and probabilities, among others, to enable an expanded discussion of…

New knowledge tracing models are continuously being proposed, even at a pace where state-of-the-art models cannot be compared with each other at the time of publication. This leads to a situation where ranking models is hard, and the underlying reasons of the models' performance -- be it architectural choices, hyperparameter tuning, performance…

Anxiety surrounding the taking of online statistics courses in higher education is a common issue. Many studies have been conducted on the cause of math anxiety as well as anxiety in computer-based learning. The purpose of this study was to examine whether using gamification and Mayer's Multimedia principles in an asynchronous, online statistics…

This study examines modelling with machine learning. In the context of a yearlong data science course, the study explores how upper secondary students apply machine learning with Jupyter Notebooks and document the modelling process as a computational essay incorporating the different steps of the CRISP-DM cycle. The students' work is based on a…