Download: PDF, Data Programming class at UW.
“A data programming CS1 course” by Ruth Anderson, Michael D. Ernst, Robert Ordóñez, Paul Pham, and Ben Tribelhorn. In SIGCSE: Proceedings of the 46th ACM Technical Symposium on Computer Science Education, (Kansas City, MO, USA), Mar. 2015, pp. 150-155.
This paper reports on our experience teaching introductory programming by means of real-world data analysis. We have found that students can be motivated to learn programming and computer science concepts in order to analyze DNA, predict the outcome of elections, detect fraudulent data, suggest friends in a social network, determine the authorship of documents, and more. The approach is more than just a collection of “nifty assignments”; rather, it affects the choice of topics and pedagogy.
This paper describes how our approach has been used at four diverse colleges and universities to teach CS majors and non-majors alike. It outlines the types of assignments, which are based on problems from science, engineering, business, and the humanities. Finally, it offers advice for anyone trying to integrate the approach into their own institution.
Download: PDF, Data Programming class at UW.
BibTeX entry:
@inproceedings{AndersonEOPT2015,
author = {Ruth Anderson and Michael D. Ernst and Robert Ord{\'o}{\~n}ez
and Paul Pham and Ben Tribelhorn},
title = {A data programming {CS1} course},
booktitle = {{SIGCSE}: Proceedings of the 46th ACM Technical Symposium
on Computer Science Education},
pages = {150--155},
address = {Kansas City, MO, USA},
month = mar,
year = {2015}
}
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