Topic Modelling and Sentimental Analysis of Students’ Reviews

Alkhnbashi, Omer S. and Mohammad, Rasheed (2022) Topic Modelling and Sentimental Analysis of Students’ Reviews. Computers, Materials and Continua, 74 (3). 6835-6848.. ISSN 1546-2218

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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.

Item Type: Article
Identification Number:
26 October 2022Accepted
28 December 2022Published Online
Uncontrolled Keywords: Topic modelling, sentimental analysis, COVID-19, students’ input
Subjects: CAH22 - education and teaching > CAH22-01 - education and teaching > CAH22-01-01 - education
CAH22 - education and teaching > CAH22-01 - education and teaching > CAH22-01-02 - teacher training
Divisions: Faculty of Computing, Engineering and the Built Environment > School of Computing and Digital Technology
Depositing User: Rasheed Mohammad
Date Deposited: 03 Jan 2023 12:04
Last Modified: 03 Jan 2023 12:04

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