Exploring how different project management methodologies impact data science students

Jeffrey Saltz, Robert Heckman, Ivan Shamshurin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

This paper reports on a controlled experiment comparing different approaches on how to guide students through a semester long data science project. Four different methodologies, ranging from a traditional “just assign some intermediate milestones” to other more agile methodologies, are compared. The results of the experiment shows that the project methodology used in the classroom made a significant difference in student outcomes. Surprisingly, an Agile Kanban approach was found to be much more effective than an Agile Scrum methodology, which was not one of the leading ap-proaches.

Original languageEnglish (US)
Title of host publicationProceedings of the 25th European Conference on Information Systems, ECIS 2017
PublisherAssociation for Information Systems
Pages2939-2948
Number of pages10
ISBN (Electronic)9780991556700
StatePublished - Jan 1 2017
Event25th European Conference on Information Systems, ECIS 2017 - Guimaraes, Portugal
Duration: Jun 5 2017Jun 10 2017

Other

Other25th European Conference on Information Systems, ECIS 2017
CountryPortugal
CityGuimaraes
Period6/5/176/10/17

Keywords

  • Agile development
  • Big data education
  • Data science education
  • Project management

ASJC Scopus subject areas

  • Information Systems

Fingerprint Dive into the research topics of 'Exploring how different project management methodologies impact data science students'. Together they form a unique fingerprint.

Cite this