Undergraduate economics programs prepare students for future careers by developing competency working with data, or "data literacy." Our research examined the data literacy components of undergraduate economics programs at R1 and R2 universities in the United States (N = 190). We developed a protocol with core data skills and coded…

This work reports on the implementation of a self-contained data-literacy exercise designed for use in undergraduate classes to help students practice data literacy skills such as interpreting and evaluating evidence and assessing arguments based on data. The exercises use already developed data-visualizations to test and develop students' ability…

Classification, a fundamental data analytics task, has widespread applications across various academic disciplines, such as marketing, finance, sociology, psychology, education, and public health. Its versatility enables researchers to explore diverse research questions and extract valuable insights from data. Therefore, it is crucial to extend…

The significance of ethics in data science research has attracted considerable attention in recent years. While there is widespread agreement on the importance of teaching ethics within computing contexts, there is no clear method for its implementation and assessment. Studies focusing on methods for integrating ethics into data science courses…

This study presents a mobile application (app) that facilitates undergraduate students to learn data science using their own full-body motion data. The app captures a user's movements through the built-in camera of a mobile device and processes the images for data generation using BlazePose, an open-source computer vision model for real-time pose…

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…

Understanding students' learning of knowledge components (KCs) is an important educational data mining task and enables many educational applications. However, in the domain of computing education, where program exercises require students to practice many KCs simultaneously, it is a challenge to attribute their errors to specific KCs and,…

In this paper, we describe a course project in which teams of undergraduate students propose and execute an end-to-end analytics project to solve a real-world problem. The project challenges students to implement machine learning, optimization, simulation, or a combination of these three techniques on real-world data that they collect. A…

All chemistry students must develop competency in analyzing and making sense of data. However, there are many difficulties that chemistry students may experience while analyzing data. Many students may not use relevant prior knowledge to aid in making sense of data, or they may not form conclusions using all the data provided. Additionally, prior…

Undergraduate research is considered to be a high-impact practice; however, research into the data literacy of students conducting undergraduate research is lacking. In addition, institutionwide assessments of data practices are challenging because of varied disciplinary approaches to data. This study investigates the data practices of…

The use of group work projects is common in introductory statistics courses, including projects where students collect their own data. However, the COVID-induced lockdown at the start of 2020 meant that data collection was compromised. In this study, we examine a situation where students were permitted to use artificial (made-up) data for their…

U.S. colleges and universities are under increasing pressure to appear racially diverse, but have yet to account systematically for a quickly growing contingent of multiracial-identifying students. Drawing on interviews with multiracial-identifying undergraduates at Western University, I demonstrate how everyday university practices compromise…

The development of critical data and artificial intelligence (AI) literacy has become a key focus in current discussions in Higher Education, thus it is necessary to develop and advance capacity building, reflectiveness and awareness across disciplines to critically address the possibilities and challenges presented by data and AI. In this paper,…

This article reports on a study investigating how computational essays can be used to help students in higher education STEM take up disciplinary epistemic agency--cognitive control and responsibility over one's own learning within the scientific disciplines. Computational essays are a genre of scientific writing that combine live, executable…

Procrastination is a prevalent issue among university students and leads to long-term negative impacts on academic performance as well as mental health and quality of life. This paper investigated StudyTracker, a self-tracking digital application (app) that we developed for university students to use to track their study sessions. The app provided…