ACIS 2024 Proceedings

Abstract

Student satisfaction is a critical metric for universities, directly impacting retention rates, academic performance, and institutional reputation. Traditionally, universities have relied on end-of-semester surveys to measure student satisfaction. While these surveys provide structured insights, they have limitations, including predefined questions, potential response bias and confidentiality concerns. An alternative approach to gauging student satisfaction involves analyzing student reviews and opinions on social media platforms like RateMyProfessor. These platforms offer dynamic, unfiltered feedback characterized by greater freedom of expression, anonymity, and continuous input. By leveraging this unstructured feedback, we can explore the various aspects that contribute to student satisfaction and gain a comprehensive understanding of their students' experiences. Our research focuses on utilizing this valuable student data to identify key aspects related to satisfaction and dissatisfaction through topic modelling techniques. This approach enables detailed analysis of student opinions, tracks changes over time, and examines correlations with traditional end-of-semester survey results.

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