Implementation of Data Mining Approach to Find the Adaptability of Students in Online Education during Covid-19 Pandemic

Open Access

Year : 2023 | Volume :9 | Issue : 2 | Page : 1-8
By

    Trailokya Raj Ojha

  1. Assistant Professor, Department of Computer Science Engineering, Nepal Engineering College, Bhaktapur, Nepal

Abstract

The global Covid-19 pandemic has severely affected very aspects of human life, including education. The virus’ stunning spread created havoc in the educational system, causing educational institutions to close. As an effect, students must quickly adopt to the change to synchronous online learning. This study identified the different aspects affecting the adaptability level of students in online class. It also identifies the student’s adaptability level in different circumstances in online classes. A sample of 1205 school, college and university students from Bangladesh has been examined using data mining technique to find their adaptability level. The result shows that college and university students have more adaptability than the school students

Keywords: Online learning, adaptability, Covid-19, K-means algorithm, Kaggle repository, educational data mining

[This article belongs to Journal of Artificial Intelligence Research Advances(joaira)]

How to cite this article: Trailokya Raj Ojha , Implementation of Data Mining Approach to Find the Adaptability of Students in Online Education during Covid-19 Pandemic joaira 2023; 9:1-8
How to cite this URL: Trailokya Raj Ojha , Implementation of Data Mining Approach to Find the Adaptability of Students in Online Education during Covid-19 Pandemic joaira 2023 {cited 2023 Jan 30};9:1-8. Available from: https://journals.stmjournals.com/joaira/article=2023/view=97369

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Regular Issue Open Access Article
Volume 9
Issue 2
Received July 26, 2022
Accepted August 9, 2022
Published January 30, 2023
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