Exploring Key Factors Affecting Students' Adaptability in Online Learning

Under the impact of the COVID-19 pandemic, traditional classroom teaching has been obstructed, making online learning the primary choice for education. Students' adaptability to online learning environments significantly affects their learning outcomes and overall quality of education. This study aims to identify the key factors affecting students' adaptability to online learning. We first preprocess the data by creating dummy variables to make the data suitable for subsequent statistical analysis. Secondly, a quartile relation matrix is used to visualize the Pearson relation coefficients between various variables. Then, the R package IsingFit is employed for model fitting, and a psychometric network model is used to visualize the network relationships, resulting in an undirected relation graph. The experimental results indicate that family economic status, home address, online learning equipment, and the usability of the school's student management system are key factors affecting student adaptability. The results highlight the necessity of improving home learning conditions, providing technical support, and optimizing school management to enhance the online learning experience for students.

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Published
2024-09-13
DOI
https://doi.org/10.1109/itme63426.2024.00128
Primary Topic
Education and Learning Interventions
Type
article
Field-Weighted Citation Impact
0.00

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article

Exploring Key Factors Affecting Students' Adaptability in Online Learning

Yue Sun, Hong Wang, Yingying Fan
Education and Learning Interventions
article

Exploring Key Factors Affecting Students' Adaptability in Online Learning

Yue Sun, Hong Wang, Yingying Fan
article en

Abstract

Under the impact of the COVID-19 pandemic, traditional classroom teaching has been obstructed, making online learning the primary choice for education. Students' adaptability to online learning environments significantly affects their learning outcomes and overall quality of education. This study aims to identify the key factors affecting students' adaptability to online learning. We first preprocess the data by creating dummy variables to make the data suitable for subsequent statistical analysis. Secondly, a quartile relation matrix is used to visualize the Pearson relation coefficients between various variables. Then, the R package IsingFit is employed for model fitting, and a psychometric network model is used to visualize the network relationships, resulting in an undirected relation graph. The experimental results indicate that family economic status, home address, online learning equipment, and the usability of the school's student management system are key factors affecting student adaptability. The results highlight the necessity of improving home learning conditions, providing technical support, and optimizing school management to enhance the online learning experience for students.

Shandong Normal University (CN)
National Natural Science Foundation of China
Quality Education
Openalex Percentile: Top 54%
Education and Learning Interventions
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