Summarizing University Students? Qualitative Feedback on Online Exams: A Microservice-Oriented Approach

This study deals with the analysis of data resulting from the qualitative feedback given by university students through written comments on an online questionnaire for online examinations. The research took place at the Hellenic Open University (HOU) and was implemented through a micro-services-oriented approach that automates the summarization of large volumes of open feedback through the combination of Text Mining (TM) and Natural Language Processing (NLP) techniques. The methodology includes data preparation (sentence extraction, anonymization, and lemmatization) and the implementation of a hybrid summarization process that combines extractive and abstractive summarization techniques. The study findings stress positive aspects of e-exams from students' open-ended responses, such as flexibility, convenience, accessibility, saving money, and reducing stress, but also issues related to time constraints, technical problems, and stress. The study further shows the effectiveness of microservices as a method that enhances the scalability and efficiency of qualitative data collection, processing, and analysis, thus providing a framework adaptable to future research in educational evaluation.