@inproceedings{4e4bccb8582248d8878d444cb29930cd,
title = "Predicting group programming project performance using SVN activity traces",
abstract = "This paper presents a model for integrating student activity traces in a collaborative programming project using SVN, and relates different attributes of the SVN activities to student and team performance. We show how student participation patterns can be related to the grades of their group programming projects. Graph theory, entropy analysis and statistical techniques are applied to process and analyze data.",
keywords = "Collaborative project, Data mining, Entropy analysis, Graph theory, Group project, SVN",
author = "Sen Liu and Jihie Kim and Macskassy, {Sofus A.} and Erin Shaw",
note = "Publisher Copyright: {\textcopyright} 2013 International Educational Data Mining Society. All rights reserved.; 6th International Conference on Educational Data Mining, EDM 2013 ; Conference date: 06-07-2013 Through 09-07-2013",
year = "2013",
language = "English",
series = "Proceedings of the 6th International Conference on Educational Data Mining, EDM 2013",
publisher = "International Educational Data Mining Society",
editor = "D'Mello, {Sidney K.} and Calvo, {Rafael A.} and Andrew Olney",
booktitle = "Proceedings of the 6th International Conference on Educational Data Mining, EDM 2013",
address = "United States",
}