Does technology assist to continue learning during pandemic? A sentiment analysis and topic modeling on online learning in south asian region

Abstract

Online mode of education has been identified as the subtle solution to continue learning during the pandemic. However, the accessibility to online platforms, suitable devices, and connections are not equal across the globe thus raising the question of whether the opinion of the public in the South Asian region where the technology is not comparatively higher as in the western world would be the same as that to the global perspective. This study involves the sentiment analysis of natural language processing on recently tweeted data and concludes that the sentiment of the South Asian public remains positive as online education is the most suitable approach to overcome the learning difficulties during a pandemic. The study performs a ternary classification based on the polarity scores obtained from two robust lexicon-based sentiment analyzer tools namely VADER and TextBlob and observes that 63.2% of the tweets were positive, 30.5% of the tweets were neutral and around 6.3% of them were negative. Finally, topic modeling was also performed using the Latent Dirichlet Allocation method to gain insight into each of the classes.

Reasons for Undergraduates’ Attitudes toward Online Learning

“…Although the forced or continuance desire might not equal a normative desire, in a critical time a forced commitment may help substantially to continue in online learning. This finding aligns with a previous study that found the positive view of the general public of the South Asian region toward online learning in a difficult time of continuing education without disruption (Shafana & Safnas, 2022).…”

Assessing Teacher Competencies in Higher Education: A Sentiment Analysis of Student Feedback

“…It is worth noting that, from a technical point of view, the platform allows us to choose the preferred language for data entry and processing. For our purposes, we judged that we should rely on the VADER lexicon which is fully opensourced under the MIT License, in the English language, fully validated and widely accepted across multiple distinct domains including the field of education [35,36]. Furthermore, the VADER sentiment lexicon has been compared to many other well-established sentiment analysis lexicons such as Linguistic Inquiry Word Count (LIWC), General Inquirer (GI), Affective Norms for English Words (ANEW), SentiWordNet (SWN), SenticNet (SCN), WordNet and the Hu-Liu, and the results were indeed quite remarkable.…”

Evaluation of Online Learning Platforms in Latin America

“…Regarding previous research on online learning platforms, it has been found that: (a) virtual platforms can be used in favor of deep learning [6], (b) online learning can generate significant learning in times of pandemic [7], (c) there is a positive psychological response in favor of the use of the online learning platform [8], (d) virtual platforms are effective for learning a second language such as English [9], ( e) they are successful in the educational process of classical sciences, such as medicine [10,11], (f) virtual platforms increase educational performance, student engagement, evaluation methods, and collaborative learning [12,13]; and (g) the contribution of the metaverse and augmented reality in student satisfaction and interaction in favor of the learning process [14].…”