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USING MACHINE LEARNING TO CLASSIFY KNOWLEDGE FROM STUDENTS FEEDBACK AND PREDICT PERFORMANCE OF STAFF IN EDUCATION LEARNING MANAGEMENT

Abstract

Abstract: Sentiment analysis (SA) is the process of identifying and classifying users’ opinions from a piece of text intodifferent sentiments—for example, positive, negative, or neutral or emotions such as happy, sad, angry, or disgusted todetermine the user’s attitude toward a particular subject or entity. SA plays an important role in many fields includingeducation, where student feedback is essential to assess the effectiveness of learning technologies. Many universities obtainsuch feedback via a student response system (SRS) during or at the end of a course to analyze the teacher’s performance.Student feedback about teacher performance, the learning experience, and other course attributes can also be gatheredthrough social media. In recent years, online learning portals like Courser have attracted many students by providing freecourses from a growing number of selected institutions.2 Millions of students join these massive open online courses eachyear and share their opinions about the course content and quality of teaching on the course’s discussion forum. Studentsalso comment about their educational experiences in blogs.Keywords: Educational Data Mining, Classification

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