Boosting Early Detection of Spring Semester Freshmen Attrition: A Preliminary Exploration

Eitel Lauría, Eric Stenton, Edward Presutti

Abstract

We explore the use of a two-stage classification framework to improve predictions of freshmen attrition at the beginning of the Spring semester. The proposed framework builds a Fall semester classifier using machine learning algorithms and freshmen student data, and subsequently attempts to improve the predictions of Spring attrition by including as predictor of the Spring classifier an error measure resulting from the discrepancy between Fall predictions of attrition and actual attrition. The paper describes the proposed method and shows how to organize the data for training and testing and demonstrate how it can be used for prediction. Experimental tests are carried out using several classification algorithms, to explore the validity and potential of the approach and gauge the increase in predictive power it introduces.

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Paper Citation


in Harvard Style

Lauría E., Stenton E. and Presutti E. (2020). Boosting Early Detection of Spring Semester Freshmen Attrition: A Preliminary Exploration.In Proceedings of the 12th International Conference on Computer Supported Education - Volume 2: CSEDU, ISBN 978-989-758-417-6, pages 130-138. DOI: 10.5220/0009449001300138


in Bibtex Style

@conference{csedu20,
author={Eitel Lauría and Eric Stenton and Edward Presutti},
title={Boosting Early Detection of Spring Semester Freshmen Attrition: A Preliminary Exploration},
booktitle={Proceedings of the 12th International Conference on Computer Supported Education - Volume 2: CSEDU,},
year={2020},
pages={130-138},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009449001300138},
isbn={978-989-758-417-6},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 12th International Conference on Computer Supported Education - Volume 2: CSEDU,
TI - Boosting Early Detection of Spring Semester Freshmen Attrition: A Preliminary Exploration
SN - 978-989-758-417-6
AU - Lauría E.
AU - Stenton E.
AU - Presutti E.
PY - 2020
SP - 130
EP - 138
DO - 10.5220/0009449001300138