Background: Academic help-seeking benefits students' achievement, but existing literature either studies important factors in students' selection of all help resources via self-reported surveys or studies their help-seeking behavior in one or two separate help resources via actual help-seeking records. Little is known about whether computing…

Two-year colleges provide the opportunity for students of all ages to try new subjects, change careers, upskill, or begin exploring higher education, at affordable rates. Many might begin their exploration by taking a course at a local two-year college. Currently, not many of these institutions in the U.S. offer data science courses. This article…

The objectives of this study were to identify gaps in educational training for undergraduate and graduate students in agricultural data science, propose paths for filling these gaps, and provide an annotated list of resources currently available to different training levels. Data in this study was collected through three voluntary surveys catered…

In recent years, big data has become ubiquitous in our day-to-day lives. Therefore, it is imperative for educators to integrate nontraditional (big) data into statistics education to ensure that students are prepared for a big data reality. This study examined graduate students' expressions of uncertainty while engaging with traditional and…

Student emotions influence assessment task behaviour and performance but are difficult to study empirically. The study combined qualitative data from focus group interviews with 22 students and 4 teachers, with quantitative real-time learning analytics (facial expression, mouse click and keyboard strokes) to examine student emotional engagement in…

Academic and practitioner interest in data science has increased considerably. Yet scholarly understanding of what motivates students to learn data science is still limited. Drawing on the theory of planned behavior, we propose a research model to examine the determinants of behavioral intentions to learn data science. In the proposed research…

While many instructors are aware of the "Literary Digest" 1936 poll as an example of biased sampling methods, this article details potential further explorations for the "Digest's" 1924-1936 quadrennial U.S. presidential election polls. Potential activities range from lessons in data acquisition, cleaning, and validation, to…

The field of Data Science has seen rapid growth over the past two decades, with a high demand for people with skills in data analytics, programming, statistics, and ability to visualize, predict from, and otherwise make sense of data. Alongside the rise of various artificial intelligence (AI) and machine learning (ML) applications, we have also…

This dissertation explores technological affordances in blended learning, their influence on the flexibility of statistics and data science curricula, and students' satisfaction with learning. While blended learning is often perceived as a flexible learning approach, its correlation with flexibility lacks substantial evidence in existing…

This article reports on a multi-method study of a high school course in data science, finding that students who take data science take more mathematics courses than those who do not, there are more under-represented students in data science than is typical for other advanced mathematics courses; that the students who take data science are more…

A professional practice is a type of internship, a practicum, that encompasses a supervised hands-on training experience for students to develop and identify the core and enabling competencies required in a professional environment. It also allows them to identify the developed and underdeveloped skills that are important in the labour environment…

When pressing societal challenges (e.g., COVID-19, access to clean water) are sidelined in science classrooms, science education fails to leverage the knowledge and experiences of minoritized students in school, thus reproducing injustices in society. Our conceptual framework for "justice-centered STEM education" engages all students in…

Purpose: Knowing the students' readiness for the fourth industrial revolution (4IR) is essential to producing competent, knowledgeable and skilled graduates who can contribute to the skilled workforce in the country. This will assist the Higher Education Institutions (HEIs) to ensure that their graduates own skill sets needed to work in the 4IR…

In this article, we presented our findings regarding an online project-based learning course, delivered to 64 students from the Federal University of Sao Paulo, Brazil, during the COVID-19 pandemic, in the second semester of 2021. The course had the goal of teaching Project Management by means of a competition (the Data Science Olympics). Our goal…

Tutorials for EXperimentalisT Interactive LEarning (TEXTILE) is an interactive semi-linear module-based curriculum for training students at various educational levels on data science methodologies currently utilized by research laboratories. We show how we developed our eleven module TEXTILE program to train 15 students from high school,…