Analyzing User Feedback in Massive Open Online Courses: A Bibliometrics-Based Systematic Review

Proceedings of the 2022 6th International Conference on Education and E-Learning Pub Date : 2022-11-21 DOI:10.1145/3578837.3578882

Xiaomeng Li, Chang Boon Lee

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Abstract

With the development of technology, MOOCs (Massive Open Online Courses) have gained popularity in the field of e-learning. Considering that MOOCs still have many shortcomings, analyzing users’ feedback has become a useful method to improve MOOCs performance. This study used both bibliometric and systematic methods to explore the intellectual structure for MOOCs user feedback literature. The results showed the annual publication figures, the contributing entities, and the relevant publication outlets. Based on co-citation analysis, the study found two clusters of cited references. One deals with the definition, design, and assessment of MOOCs. The other is related to MOOCs discussion forum and students’ interactions. Co-word analysis revealed the focus of publications and the future trend. The results showed that current studies have explored different types of user feedback, methods of analyzing user feedback, and the aim of learning user feedback. Future research can extend the use of machine learning techniques, collect user feedback from various sources, and concentrate on different components of user feedback.

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大规模在线开放课程的用户反馈分析:基于文献计量学的系统评价

随着技术的发展，mooc (Massive Open Online Courses，大规模在线开放课程)在网络学习领域得到了广泛的应用。鉴于mooc还存在许多不足，分析用户反馈成为提高mooc性能的有效方法。本研究采用文献计量学和系统方法对mooc用户反馈文献的智力结构进行了探讨。结果显示了年度出版数字、投稿单位和相关出版网点。基于共被引分析，本研究发现了两类被引文献。一篇是关于mooc的定义、设计和评估。二是mooc讨论论坛和学生互动。共词分析揭示了出版物的焦点和未来趋势。结果表明，目前的研究已经探索了不同类型的用户反馈，分析用户反馈的方法，以及学习用户反馈的目的。未来的研究可以扩展机器学习技术的使用，从各种来源收集用户反馈，并专注于用户反馈的不同组成部分。

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Proceedings of the 2022 6th International Conference on Education and E-Learning

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