SWAYAM MOOC Reviews: Assessing Acceptability through Sentiment Analysis using Machine Learning
Ishteyaaq Ahmad, Sonal Sharma, Mahesh Kumar Chaubey, Saurabh Dhyani, Sikha Ahmad, Ajay Kumar · 2023
Massive Open Online Courses (MOOCs) have been granted a place in pedagogy as a result of the paradigm change occurring in higher education. The user base of the Indian MOOC platform SWAYAM has grown to over 18 million in only a few years, making it third only to Coursera and edX in terms of total users. This study gathered 4029 reviews from participants in 247 SWAYAM MOOCs and applied sentiment analysis with machine learning approaches to measure student acceptability of MOOCs on the SWAYAM platform. The Orange tool and the rule-based sentiment analysis method VADER were used to analyze the user reviews. Box plots of compound scores and chi-square tests of independence were calculated to identify patterns and trends in user sentiment toward MOOCs. The study found that overall user sentiment towards SWAYAM MOOCs was positive, with users expressing appreciation for the course content and delivery quality. Additionally, the study suggests that sentiment analysis may be a helpful tool for determining the quality and acceptance of MOOCs, and it can also be used to develop courses, advise policy, and assist in decision-making. The research also emphasizes the use of machine learning approaches in sentiment analysis.