Classification of Peruvian Elementary School Students with Low Achievement Problems Using Clustering Algorithms and ERCE Evaluation

Nancy Rojas-Salvatierra, Lucas Parodi-Roman, Peter Montalvo

2024

Abstract

At present there are several problems that affect students and their academic performance such as low socioeconomic status that can cause lack of resources both in their homes and in the school. In addition to psychological and personal problems in which students can be involved. According to various national and international examinations the academic level in Peru is quite low because the problems mentioned above are difficult to identify, it is not possible to propose a viable solution, which is why we propose a Machine Learning model based on Clustering algorithms such as KMeans, Birch and Aglomerative that manage to group students by the most relevant characteristics or disadvantages they present.

Paper Citation

in Harvard Style

Rojas-Salvatierra N., Parodi-Roman L. and Montalvo P. (2024). Classification of Peruvian Elementary School Students with Low Achievement Problems Using Clustering Algorithms and ERCE Evaluation. In Proceedings of the 21st International Conference on Smart Business Technologies - Volume 1: ICSBT; ISBN 978-989-758-710-8, SciTePress, pages 37-43. DOI: 10.5220/0012814200003764

in Bibtex Style

@conference{icsbt24,
author={Nancy Rojas-Salvatierra and Lucas Parodi-Roman and Peter Montalvo},
title={Classification of Peruvian Elementary School Students with Low Achievement Problems Using Clustering Algorithms and ERCE Evaluation},
booktitle={Proceedings of the 21st International Conference on Smart Business Technologies - Volume 1: ICSBT},
year={2024},
pages={37-43},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012814200003764},
isbn={978-989-758-710-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 21st International Conference on Smart Business Technologies - Volume 1: ICSBT
TI - Classification of Peruvian Elementary School Students with Low Achievement Problems Using Clustering Algorithms and ERCE Evaluation
SN - 978-989-758-710-8
AU - Rojas-Salvatierra N.
AU - Parodi-Roman L.
AU - Montalvo P.
PY - 2024
SP - 37
EP - 43
DO - 10.5220/0012814200003764
PB - SciTePress