The ability to use computational tools to collect, organize, visualize, and analyze data is a valuable skill both inside and outside of computer science. In this paper we describe the design and implementation of a statistics-infused introduction to computer science, developed in collaboration with statistics faculty, at St. Olaf College. We propose that there exists a growing demographic of 'data-centric' students who expect to write small amounts of code in the context of work in other fields, and who are eager to take a CS course adapted to their needs. This particular data-centric CS1 course has been a catalyst for collaboration between faculty in multiple fields and multiple institutions.
|Original language||English (US)|
|Title of host publication||SIGCSE 2015 - Proceedings of the 46th ACM Technical Symposium on Computer Science Education|
|Editors||Adrienne Decker, Kurt Eiselt, Jodi Tims, Carl Alphonce|
|Publisher||Association for Computing Machinery|
|Number of pages||6|
|State||Published - Feb 24 2015|
|Event||46th SIGCSE Technical Symposium on Computer Science Education, SIGCSE 2015 - Kansas City, United States|
Duration: Mar 4 2015 → Mar 7 2015
|Name||SIGCSE 2015 - Proceedings of the 46th ACM Technical Symposium on Computer Science Education|
|Other||46th SIGCSE Technical Symposium on Computer Science Education, SIGCSE 2015|
|Period||3/4/15 → 3/7/15|
Bibliographical notePublisher Copyright:
Copyright © 2015 ACM.
- Computer science education
- Data science