Citation

Hon, Yong Lok and Chua, Fang Fang and Lim, Amy Hui Lan (2025) Emotion Analysis Tool for Insightful Student Feedback. In: 2025 16th International Conference on Software Engineering and Service Science (ICSESS), 16-17 December 2025, Macau, China.

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Abstract

In modern education, understanding student emotions is essential for enhancing engagement and learning outcomes, as emotional states have a significant impact on cognitive processes and classroom dynamics. An emotional analysis tool is designed to analyze student feedback and track emotional trends over time, addressing the limitations of traditional end-of-term teaching evaluations. By leveraging Hugging Face’s pre-trained emotion and sentiment analysis models, the system classifies student feedback into emotional categories such as joy, sadness, anger, and surprise. The resulting data is visualized to help lecturers identify emotional patterns across courses or trimesters, enabling them to enhance the overall student learning experience. Built using the Spiral Model, the tool features a web-based, multi-layered architecture leveraging Svelte for the frontend, Python/Flask for the backend, and MySQL for data management. This project holds potential for future enhancements, such as cloud deployment, to further support advancements in the education sector.

Item Type:	Conference or Workshop Item (Paper)
Uncontrolled Keywords:	Emotion analysis, sentiment analysis, educational technology, real-time systems, multimodal data, natural language processing, machine learning, student feedback, web-based applications.
Subjects:	Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science > QA76.75-76.765 Computer software
Divisions:	Faculty of Computing and Informatics (FCI)
Depositing User:	Ms Suzilawati Abu Samah
Date Deposited:	20 Apr 2026 04:09
Last Modified:	20 Apr 2026 04:09
URII:	http://shdl.mmu.edu.my/id/eprint/15783

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