Sentiment Analysis for Distance Education Course Materials: A Machine Learning Approach

Authors : Usame Ömer OSMANOĞLU, Osman Nuri ATAK, Kerim ÇAĞLAR, Hüseyin KAYHAN, Talat CAN

Pages : 31-48

Doi:10.31681/jetol.663733

View : 20 | Download : 7

Publication Date : 2020-01-22

Article Type : Research Paper

Abstract :Nowadays many companies and institutions are interested in learning what do people think and want. Many studies are conducted to answer these questions. That’s why, emotions of people are significant in terms of instructional design. However, processing and analysis of many people`s ideas and emotions is a challenging task. That is where the `sentiment analysis` through machine learning techniques steps in. Recently a fast digitalization process is witnessed. Anadolu university, that serves 1 million distant students, is trying to find its place in this digital era. A learning management system insert ignore into journalissuearticles values(LMS); that distant students of the Open Education Faculty insert ignore into journalissuearticles values(Açıköğretim Fakültesi); is developed at the Anadolu University.  Interaction with students is the clear advantage of LMS`s when compared to the hard copy materials. Book, audio book insert ignore into journalissuearticles values(mp3);, video and interactive tests are examples of these materials. 6059 feedbacks for those online materials was scaled using the triple Likert method and using machine learning techniques sentiment analysis was performed in this study. 0.775 correctness ratio was achieved via the Logistic regression algorithm. The research concludes that machine learning techniques can be used to better understand learners and how they feel.
Keywords : Emotion Analysis, Machine Learning, Application Feedbacks, Deep Learning, Estimation