Framing Early Alert of Struggling Students as an Anomaly Detection Problem: An Exploration

Eitel J. M. Lauría

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Paper

Framing Early Alert of Struggling Students as an Anomaly Detection Problem: An Exploration

Topics: Educational Data Mining; Learning Analytics and Educational Data Mining; Machine Learning

In Proceedings of the 13th International Conference on Computer Supported Education - Volume 1: CSEDU, 26-35, 2021

Author: Eitel J. M. Lauría

Affiliation: School of Computer Science & Mathematics, Marist College, Poughkeepsie, NY, U.S.A.

Keyword(s): Early Detection, At-risk Students, Anomaly Detection, Learning Analytics, Predictive Modeling, Machine Learning.

Abstract: This exploratory study analyses the feasibility of implementing an early-alert system of academically vulnerable students using anomaly detection techniques for cases in which the number of struggling students is small in comparison to the total student population. The paper focuses on a semi-supervised approach to anomaly detection where a first stage made up of an ensemble of unsupervised anomaly detectors contributes features to a second-stage binary classifier. Experiments are carried out using several semesters of college data to compare the predictive performance of this semi-supervised approach relative to stand-alone classification-based methods.

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Paper citation in several formats:

Lauría, E. (2021). Framing Early Alert of Struggling Students as an Anomaly Detection Problem: An Exploration. In Proceedings of the 13th International Conference on Computer Supported Education - Volume 1: CSEDU; ISBN 978-989-758-502-9; ISSN 2184-5026, SciTePress, pages 26-35. DOI: 10.5220/0010471900260035

@conference{csedu21,
author={Eitel J. M. Lauría.},
title={Framing Early Alert of Struggling Students as an Anomaly Detection Problem: An Exploration},
booktitle={Proceedings of the 13th International Conference on Computer Supported Education - Volume 1: CSEDU},
year={2021},
pages={26-35},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010471900260035},
isbn={978-989-758-502-9},
issn={2184-5026},
}

TY - CONF

JO - Proceedings of the 13th International Conference on Computer Supported Education - Volume 1: CSEDU
TI - Framing Early Alert of Struggling Students as an Anomaly Detection Problem: An Exploration
SN - 978-989-758-502-9
IS - 2184-5026
AU - Lauría, E.
PY - 2021
SP - 26
EP - 35
DO - 10.5220/0010471900260035
PB - SciTePress