Sentiment Analysis in EdTech: A Study on Course Review Feedback Using NLP

Authors

  • Vaibhav Mahale Student, Department of Computer Engineering, Sardar Patel Institute of Technology, Mumbai, India
  • Ronak Matolia Student, Department of Computer Engineering, Sardar Patel Institute of Technology, Mumbai, India
  • Deep Mehta Student, Department of Computer Engineering, Sardar Patel Institute of Technology, Mumbai, India
  • Anand Godbole Professor, Department of Computer Engineering, Sardar Patel Institute of Technology, Mumbai, India

Abstract

This paper presents an EdTech platform prototype that enables users to create, edit, and consume educational content while providing sentiment analysis of course reviews. By employing Natural Language Processing (NLP) techniques, the system categorizes reviews into positive, negative, and neutral sentiments to offer educators actionable insights on course quality. We implement various NLP models, including traditional machine learning and transformer-based models, to analyze student feedback effectively. Results demonstrate that this system can accurately identify sentiment trends, supporting continuous course improvements and enhancing the educational experience.

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Published

05-02-2025

Issue

Vol. 8 No. 2 (2025)

Section

Articles

License

Copyright (c) 2025 Vaibhav Mahale, Ronak Matolia, Deep Mehta, Anand Godbole

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
V. Mahale, R. Matolia, D. Mehta, and A. Godbole, “Sentiment Analysis in EdTech: A Study on Course Review Feedback Using NLP”, IJRESM, vol. 8, no. 2, pp. 10–14, Feb. 2025, Accessed: Feb. 22, 2025. [Online]. Available: https://journal.ijresm.com/index.php/ijresm/article/view/3210