Back to Search Start Over

Teaching Computational Modeling in the Data Science Era.

Authors :
Giabbanelli, Philippe
Mago, Vijay
Source :
Procedia Computer Science; 2016, Vol. 80, p1968-1977, 10p
Publication Year :
2016

Abstract

Integrating data and models is an important and still challenging goal in science. Computational modeling has been taught for decades and regularly revised, for example in the 2000s where it became more inclusive of data mining. As we are now in the ‘data science’ era, we have the occasion (and often the incentive) to teach in an integrative manner computational modeling and data science. In this paper, we reviewed the content of courses and programs on computational modeling and/or data science. From this review and our teaching experience, we formed a set of design principles for an integrative course. We independently implemented these principles in two public research universities, in Canada and the US, for a course targeting graduate students and upper-division undergraduates. We discuss and contrast these implementations, and suggest ways in which the teaching of computational science can continue to be revised going forward. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
18770509
Volume :
80
Database :
Supplemental Index
Journal :
Procedia Computer Science
Publication Type :
Academic Journal
Accession number :
115845100
Full Text :
https://doi.org/10.1016/j.procs.2016.05.517