Finding Pathways to Student Success from Data

Brendan Mumey, Sean Yaw, Christina Fastnow, David J. Singel

Abstract

We propose some novel computational approaches to analyzing historical student transcript data to help improve course sequencing and generate default pathways for students to complete a college degree. Additionally, we examine whether there are “hidden prerequisites” to courses and whether there are courses which, when taken early in a student’s career, may improve their chances of graduation. Our analysis was done on a dataset consisting of all student-course enrollments for a period of 10 years at Montana State University.

References

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Paper Citation


in Harvard Style

Mumey B., Yaw S., Fastnow C. and Singel D. (2015). Finding Pathways to Student Success from Data . In Proceedings of the 7th International Conference on Computer Supported Education - Volume 1: CSEDU, ISBN 978-989-758-107-6, pages 457-460. DOI: 10.5220/0005487704570460


in Bibtex Style

@conference{csedu15,
author={Brendan Mumey and Sean Yaw and Christina Fastnow and David J. Singel},
title={Finding Pathways to Student Success from Data},
booktitle={Proceedings of the 7th International Conference on Computer Supported Education - Volume 1: CSEDU,},
year={2015},
pages={457-460},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005487704570460},
isbn={978-989-758-107-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 7th International Conference on Computer Supported Education - Volume 1: CSEDU,
TI - Finding Pathways to Student Success from Data
SN - 978-989-758-107-6
AU - Mumey B.
AU - Yaw S.
AU - Fastnow C.
AU - Singel D.
PY - 2015
SP - 457
EP - 460
DO - 10.5220/0005487704570460