The sentiment of user and knowledge are used for teaching, knowledge about students and address problems like confusion and boredom which affects student’s engagement. To overcome such problem, we looked at several methods that could be used for learning sentiment from student’s feedback. Now-a-days Sentiment Analysis (SA) is used for training computer to identify the sentiment within the content through NLP (Natural Language Processing) technique. SA specify the task of NLP to determine whether a piece of text contains some subjective information which express the attitude behind the text is positive, negative or neutral or emotions such as happy, sad, angry, or disgusted and which determine the user’s attitude toward a particular subject or entity. SA plays an important role in many fields including education, where student feedback is essential to assess the effectiveness of learning technologies. Collecting feedback in real-time has numerous benefits for the lecturer and their students, such as improvement in teaching and understanding students learning behaviour. Moreover, student’s feedback improves communication between the teacher and the student which allow the teacher to have an overall summary of the student’s opinion through Student Response System (SRS).
Volume 11 | 01-Special Issue