Sentiment Analysis of user reviews in an Online Learning Environment: Analyzing the Methods and Future Prospects

Abstract

The pandemic compelled most of us to switch to remote & hybrid work culture from the traditional and eLearning from the traditional classroom-based learning. Although eLearning has opened boundless opportunities for students at minimal cost, it has also brought a major challenge for the educators. Some of these are- lack of one-to-one interaction between teachers and students, the inability of teachers to assess the quality of their teaching, and more. To make eLearning more effective, it is important for administrators to fill such gaps. This is where sentiment analysis can play a vital role. It can help educators analyze student feedback and optimize their teaching methods for the best results. This paper is a systematic review of the learning-based methods available for sentiment analysis in an online learning environment- through online comments/reviews, web discussions or online forums, learning content, and student feedback. We also discussed some of the combined approaches used for Sentiment Analysis in online learning. Most importantly, the paper ends with a discussion of the limitations and challenges faced by researchers and the further scope for work in this field. Concluding from the research available, Sentiment Analysis has proved to be effective for both educators and students through various channels such as reviews, comments, learning content, web discussions and forums, and more. It has helped teachers improve their teaching methodology and revise course content to better suit students. For students, this has led to better understanding of the course material and has provided them with access to quality learning.