Saltz, Jeffery, et al. “Helping Data Science Students Develop Task Modularity”. Proceedings of the 52nd Hawai’i International Conference on System Sciences (HICSS-52), 2019, doi:10.24251/HICSS.2019.134.
Keywords
Abstract
<p>This paper explores the skills needed to be a data scientist. Specifically, we report on a mixed method study of a project-based data science class, where we evaluated student effectiveness with respect to dividing a project into appropriately sized modular tasks, which we termed task modularity. Our results suggest that while data science students can appreciate the value of task modularity, they struggle to achieve effective task modularity. As a first step, based our study, we identified six task decomposition best practices.
Year of Conference
2019
Conference Name
Proceedings of the 52nd Hawai'i International Conference on System Sciences (HICSS-52)
URL
http://hdl.handle.net/10125/59549
DOI
10.24251/HICSS.2019.134