5Ws AND 1H OF TERM PROJECTS IN THE INTRODUCTORY DATA SCIENCE CLASSROOM

Abstract

Many data science applications involve generating questions, acquiring data and preparing it for analysis—be it exploratory, inferential, or modeling focused—and communicating findings. Most data science curricula address each of these steps as separate units in a course or as separate courses. Open-ended term projects, on the other hand, allow students to put each of these steps into practice, sequentially and iteratively. In this paper we discuss what we mean by data science projects, why they are crucial in introductory data science courses, who works on these projects and how, when in the term they can be implemented, and where they can be shared.

A secret agent? K-12 data science learning through the lens of agency

“…Many articles highlight the importance of programming to the statistics and data science disciplines (Çetinkaya-Rundel et al, 2022;Çetinkaya-Rundel & Ellison, 2021;Dogucu & Çetinkaya-Rundel, 2021;Fergusson & Pfannkuch, 2020;Hardin et al, 2015;Heiznman, 2020;Kim & Hardin, 2021;Kim & Henke, 2021). Also, an emphasis on programming has been an emphasis for researchers who approach data science through the lens of computing education and the role of data in the work of computer scientists (Dryer et al, 2018;Schanzer et al, 2022).…”

“…Çetinkaya-Rundel and Ellison's (2021) paper is emblematic of this approach. Other papers extend this sophisticated infrastructure to emphasize reproducibility through the use of the server tool Docker (Çetinkaya-Rundel & Rundel, 2018) and other technically sophisticated technologies and programming tools (Burckhardt et al, 2021;Dogucu & Çetinkaya-Rundel, 2022;Kim & Henke, 2021). Thus, a second focus is on creative, thoughtfully designed course structures, especially at the undergraduate level.…”

The possibilities of exploring nontraditional datasets with young children

“…Developing skills to transform data that do not follow traditional structures into useful information is a part of the data science movement. Data science has been understood as “the science of learning from data” [7], as an advanced form of exploratory data analysis [6] and as the process of extracting knowledge from data [17]. Today, data science is not only a requirement in a data‐driven society but also an explicit recommendation for the curriculum [2].…”