An Approach for Examining Student Satisfaction in an Indian University

Abstract

Student Satisfaction is a measure to know the contentment levels of the students. Universities nowadays strive to be the best in the global market. The techniques followed for computing student satisfaction vary for each University. In general, a few factors are considered for determining the satisfaction levels. These factors include technology, admin support, co-curricular activities in the University, hostel facilities, library and safety at the campus etc. Higher the satisfaction levels, higher is the retention of the students at the University. Students are treated as customers and happy customers are always beneficial. A lot of study and research has been done in this area in the foreign Universities. Analysis of the data has been done using various tools but none of the approaches used prediction models for satisfaction levels. This research work includes the analysis and prediction of student satisfaction rate using machine learning on the data gathered from the University. Various machine learning models are applied and an ensemble approach is opted for prediction. Feedback from the University students, reviews from social media are collected and analyzed. Sentiment analysis is applied on the reviews and the results conclude that a more positive response is received through the reviews on social media.