Recent studies showed that emotions can affect the e-learning experience. E-classrooms are often composed by students inattentive or appearing bored and wondered. In a face-to-face class instructors can detect facial expressions of students but, in an online environment, students need to establish an online presence and the instructors need to be able to pick up on this. In this scenario, a promising approach is sentiment analysis – the computational study of opinions, sentiments and emotions expressed in a text.
Many researchers are investigating the adoption of Sentiment Analysis in E-Learning field. A promising approach uses Conditional Random Fields for identifying and extracting the opinions. The proposed approach has been applied to a real case: the blended course of Software Technologies for the Web held in the University of Salerno’s Computer Science school. The results support the idea of using non-intrusive emotion detection for providing feedback to students.
In literature, there are many approaches to the sentiment analysis. In particular, some approaches attempt to classify the sentiment at a document level. Artificial intelligence and probabilistic approaches have been adopted for the sentiment mining.
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https://www.researchgate.net/publication/324812324_E-learning_and_sentiment_analysis_a_case_study