Sentiment Analysis in Education Domain: A Systematic Literature Review

Abstract

E-learning is the delivery of education through digital or electronic methods allowing students to acquire new knowledge and develop new skills. E-learning allows students to expand their knowledge whenever and wherever. Several authors consider sentiment analysis as an alternative to improve the learning process in an e-learning environment since it allows analyzing the opinions of the students in order to better understand their opinion and take more effective, better-targeted actions. In this sense, this work presents a systematic literature review about sentiment analysis in education domain. This review aims to detect the approaches and digital educational resources used in sentiment analysis as well as to identify what are the main benefits of using sentiment analysis on education domain. The results show that Naive Bayes is the most used technique for sentiment analysis and that forums of MOOCs and social networks are the most used digital education resources to collect data needed to perform the sentiment analysis process. Finally, some of the main benefits of using sentiment analysis in education domain are the improvement of the teaching-learning process and students’ performance, as well as the reduction in course abandonment.