Abstract
Educational data mining facilitates educational institutions to discover useful patterns and apply them to improve the overall quality of education. Analysing student feedback may help institutions to enhance student’s learning capabilities in the classroom. We propose a student feedback analysis system that helps in identifying sentiments from student reviews, and it further helps in generating the summary of feedback. It is implemented using sentiment analysis and text summarization techniques. Based on our evaluation, the lexicon-based approach did better than traditional machine learning-based techniques. Finally, we were able to generate a precise summary of student feedback.
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Sharma, N., Jain, V. (2021). Evaluation and Summarization of Student Feedback Using Sentiment Analysis. In: Hassanien, A., Bhatnagar, R., Darwish, A. (eds) Advanced Machine Learning Technologies and Applications. AMLTA 2020. Advances in Intelligent Systems and Computing, vol 1141. Springer, Singapore. https://doi.org/10.1007/978-981-15-3383-9_35
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DOI: https://doi.org/10.1007/978-981-15-3383-9_35
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