Research on Academic Warning of Online Learning Behavior based on K-Means Clustering Algorithm

Yaqing Wei, Yaqing Wei, Zepeng Yan, Zepeng Yan, Jingyi Wang, Jingyi Wang, Thelma Palaoag

2023

Abstract

In China, with the acceleration of education informatization, especially since the COVID-19 outbreak in 2020, the scale of online teaching and learning has been expanding, and the teaching platform has generated a large amount of learning behavior data. How to fully utilize these data to obtain useful and valuable information to serve the field of education is of great significance to both teachers and students. Through the analysis of online learning behavior, the research team classify students, find out the problem students, and give feedback and guidance to students; students understand their own learning situation and make up for their shortcomings as soon as possible. They can also improve their learning efficiency and avoid failing the course assessment.In this paper, the K-means clustering algorithm model is used to realize the effective clustering of students' online learning behavior data, and a quadrant classification early warning model is obtained to predict the possible performance trend. According to the classification results, orange and red warnings are issued to students with problems, thus achieve the purpose of giving students academic warning.

Paper Citation

in Harvard Style

Wei Y., Yan Z., Wang J. and Palaoag T. (2023). Research on Academic Warning of Online Learning Behavior based on K-Means Clustering Algorithm. In Proceedings of the 1st International Conference on Data Processing, Control and Simulation - Volume 1: ICDPCS; ISBN 978-989-758-675-0, SciTePress, pages 46-50. DOI: 10.5220/0012145700003562

in Bibtex Style

@conference{icdpcs23,
author={Yaqing Wei and Zepeng Yan and Jingyi Wang and Thelma Palaoag},
title={Research on Academic Warning of Online Learning Behavior based on K-Means Clustering Algorithm},
booktitle={Proceedings of the 1st International Conference on Data Processing, Control and Simulation - Volume 1: ICDPCS},
year={2023},
pages={46-50},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012145700003562},
isbn={978-989-758-675-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Data Processing, Control and Simulation - Volume 1: ICDPCS
TI - Research on Academic Warning of Online Learning Behavior based on K-Means Clustering Algorithm
SN - 978-989-758-675-0
AU - Wei Y.
AU - Yan Z.
AU - Wang J.
AU - Palaoag T.
PY - 2023
SP - 46
EP - 50
DO - 10.5220/0012145700003562
PB - SciTePress