Data-Driven Teaching and Learning Effect Evaluation in Online Education

The rapid development of online education has underscored the necessity of data-driven teaching functions for enhancing teaching quality and efficiency. This paper investigates the role of data-driven approaches in online education, with a particular focus on the practical application of data for evaluating learning outcomes. It highlights the importance of integrating diverse evaluation methods to provide a comprehensive understanding of student performance. Additionally, the paper emphasizes the need for effective data visualization and interpretation to support informed decision-making in educational settings. It also addresses the challenges encountered in implementing data-driven teaching, such as data privacy concerns, technological limitations, and teachers' data literacy, proposing targeted countermeasures to overcome these obstacles. The findings aim to provide valuable insights and practical guidance for the advancement of data-driven teaching practices in online education.

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Publication Details

Journal
International Journal of Web-Based Learning and Teaching Technologies
Published
2025-06-18
DOI
https://doi.org/10.4018/ijwltt.381307
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
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article

Data-Driven Teaching and Learning Effect Evaluation in Online Education

Ling Wang, Guochu Liang
International Journal of Web-Based Learning and Teaching Technologies
Online Learning and Analytics
article

Data-Driven Teaching and Learning Effect Evaluation in Online Education

Ling Wang, Guochu Liang
article en

Abstract

The rapid development of online education has underscored the necessity of data-driven teaching functions for enhancing teaching quality and efficiency. This paper investigates the role of data-driven approaches in online education, with a particular focus on the practical application of data for evaluating learning outcomes. It highlights the importance of integrating diverse evaluation methods to provide a comprehensive understanding of student performance. Additionally, the paper emphasizes the need for effective data visualization and interpretation to support informed decision-making in educational settings. It also addresses the challenges encountered in implementing data-driven teaching, such as data privacy concerns, technological limitations, and teachers' data literacy, proposing targeted countermeasures to overcome these obstacles. The findings aim to provide valuable insights and practical guidance for the advancement of data-driven teaching practices in online education.

International Journal of Web-Based Learning and Teaching TechnologiesVol. 20(1)
Yulin Normal University (CN)
Quality Education
Openalex Percentile: Top 86%
Online Learning and Analytics
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Data-Driven Teaching and Learning Effect Evaluation in Online Education — Ling Wang, Guochu Liang · International Journal of Web-Based Learning and Teaching Technologies (2025) | TGRS Research Map | TGRS