AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
PDF (587.4 KB)
Collect
Submit Manuscript AI Chat Paper
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Article | Open Access

Topic Modelling and Sentimental Analysis of Students’ Reviews

Omer S. Alkhnbashi1Rasheed Mohammad Nassr2( )
Information and Computer Science Department, King Fahd University of Petroleum and Minerals, 31261, Kingdom Saudi Arabia
Computer Science Department, School of Computing and Digital Technology, Birmingham City University, Birmingham, B55JU, United Kingdom
Show Author Information

Abstract

Globally, educational institutions have reported a dramatic shift to online learning in an effort to contain the COVID-19 pandemic. The fundamental concern has been the continuance of education. As a result, several novel solutions have been developed to address technical and pedagogical issues. However, these were not the only difficulties that students faced. The implemented solutions involved the operation of the educational process with less regard for students’ changing circumstances, which obliged them to study from home. Students should be asked to provide a full list of their concerns. As a result, student reflections, including those from Saudi Arabia, have been analysed to identify obstacles encountered during the COVID-19 pandemic. However, most of the analyses relied on closed-ended questions, which limited student involvement. To delve into students’ responses, this study used open-ended questions, a qualitative method (content analysis), a quantitative method (topic modelling), and a sentimental analysis. This study also looked at students’ emotional states during and after the COVID-19 pandemic. In terms of determining trends in students’ input, the results showed that quantitative and qualitative methods produced similar outcomes. Students had unfavourable sentiments about studying during COVID-19 and positive sentiments about the face-to-face study. Furthermore, topic modelling has revealed that the majority of difficulties are more related to the environment (home) and social life. Students were less accepting of online learning. As a result, it is possible to conclude that face-to-face study still attracts students and provides benefits that online study cannot, such as social interaction and effective eye-to-eye communication.

References

【1】
【1】
 
 
Computers, Materials & Continua
Pages 6835-6848

{{item.num}}

Comments on this article

Go to comment

< Back to all reports

Review Status: {{reviewData.commendedNum}} Commended , {{reviewData.revisionRequiredNum}} Revision Required , {{reviewData.notCommendedNum}} Not Commended Under Peer Review

Review Comment

Close
Close
Cite this article:
Alkhnbashi OS, Nassr RM. Topic Modelling and Sentimental Analysis of Students’ Reviews. Computers, Materials & Continua, 2023, 74(3): 6835-6848. https://doi.org/10.32604/cmc.2023.034987

107

Views

4

Downloads

3

Crossref

1

Web of Science

3

Scopus

Received: 02 August 2022
Accepted: 26 October 2022
Published: 31 March 2023
© The Author 2024.

This work is licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.