Assessing Teacher Competencies in Higher Education: A Sentiment Analysis of Student Feedback

Abstract

One of the most important issues concerning education nowadays is that of mapping the quality of teaching, and teacher competencies. Simultaneously, the need to exploit the huge amount of data derived from student feedback, and in particular the comments on open-ended questions, constitutes a huge challenge for both universities and researchers. In this study, we use sentiment analysis methods to measure teachers’ communication competencies. Utilizing the data of over 700 feedback comments from students of our university, we assessed specific competencies through the sentiment intensity that these comments contained. The model designed for the sentiment analysis, as well as the entire experimental phase, were implemented using an open source data mining and visualization platform. Our research revealed that certain competencies are highlighted by the nature of the course while others do not depend on it. In addition, findings indicate both a homogeneous and convergent view among students, thus strengthening the validity of the students’ opinion and their valuable contribution to the mapping of teaching quality in general with the ultimate goal of enhancing education.