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…

This paper illustrates how years 1 and 2 students were guided to engage in data modelling and statistical reasoning through interdisciplinary mathematics and science investigations drawn from an Australian 3-year longitudinal study: "Interdisciplinary Mathematics and Science Learning" (https://imslearning.org/). The project developed…

Modernizing mathematics refers to the idea that teachers should rethink how mathematics has traditionally been taught in schools by making rich tasks and collaboration the focus of instruction and promoting opportunities for active learning. "Modern Math Tasks to Provoke Transformational Thinking" presents carefully crafted tasks that…

Statistics courses are frequently perceived by tertiary students as extremely difficult and anxiety-inducing, negatively impacting student outcomes and experiences. To address this, the present study considered worked example videos (where an instructor demonstrates the solution to a problem while narrating the process) as a blended learning…

Nolan and Temple Lang's "Computing in the Statistics Curricula" (2010) advocated for a shift in statistical education to broadly include computing. In the time since, individuals with training in both computing and statistics have become increasingly employable in the burgeoning data science field. In response, universities have…

This design case details a data science summer learning experience designed by University of Memphis faculty for HBCU students (NSF #: 1918751) with recruiting assistance provided by LeMoyne-Owen College. The summer learning experience included elements of didactic and collaborative problem-solving during the first five weeks of the internship,…