Review Article
Open Access
A Comprehensive Review on Techniques in Sentiment Analysis for Improving Teaching and Learning through Students’ Feedback
1
Department of Computer Science, S.I.V.E.T. College, Chennai 600073, Tamil Nadu, India
* Corresponding Author:
Sowmiya Baskar,
[email protected]
Volume 1, Issue 1
2025
Received: 02 September 2025
Accepted: 08 September 2025
Published: 11 October 2025
Article Information
Published in
Next-Generation Computing Systems and Technologies
Volume/Issue
Volume 1, Issue 1, 2025
Pages
11-17
Cited by
1 (Crossref)
Abstract
Getting feedback from the students in education is the key to improving the learning experience in education, but reading through hundreds of feedback forms can be overwhelming. Sentiment Analysis (SA), which is a NLP (Natural Language Processing) technique, comes in interprets the emotions and opinions behind their feedback. This review explores how various technologies like machine learning and NLP are being used to understand student opinions about teaching quality, course materials, assignments, exams, instructional behavior and overall learning experience. Sentiment analysis helps educators understand student concerns, thereby improving the learning experience and promoting a student-centered learning environment. The challenges in these technologies are discussed with future directions. This review would serve as a guide to researchers in the same domain.
Graphical Abstract
Keywords
sentimental analysis
student feedback
machine learning
natural language processing
bias
Data Availability Statement
Not applicable.
Funding
This work was supported without any funding.
Conflicts of Interest
The author declares no conflicts of interest.
Ethical Approval and Consent to Participate
Not applicable.
References
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Cited By (1)
-
Parvathy S, Neha Jhadav, Niteesha Varamballi S, Mohammed Mustafa, Marilingappanavara Tejas, Manish R. .
2026 IEEE International Conference on Emerging Computing and Intelligent Technologies (ICoECIT), 2026 .
[CrossRef]
* Citation data provided by Crossref Cited-by.
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APA Style
Baskar, S (2025). A Comprehensive Review on Techniques in Sentiment Analysis for Improving Teaching and Learning through Students’ Feedback. Next-Generation Computing Systems and Technologies, 1(1), 11–17. https://doi.org/10.62762/NGCST.2025.927566
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TY - JOUR AU - Baskar, Sowmiya PY - 2025 DA - 2025/10/11 TI - A Comprehensive Review on Techniques in Sentiment Analysis for Improving Teaching and Learning through Students’ Feedback JO - Next-Generation Computing Systems and Technologies T2 - Next-Generation Computing Systems and Technologies JF - Next-Generation Computing Systems and Technologies VL - 1 IS - 1 SP - 11 EP - 17 DO - 10.62762/NGCST.2025.927566 UR - https://www.icck.org/article/abs/NGCST.2025.927566 KW - sentimental analysis KW - student feedback KW - machine learning KW - natural language processing KW - bias AB - Getting feedback from the students in education is the key to improving the learning experience in education, but reading through hundreds of feedback forms can be overwhelming. Sentiment Analysis (SA), which is a NLP (Natural Language Processing) technique, comes in interprets the emotions and opinions behind their feedback. This review explores how various technologies like machine learning and NLP are being used to understand student opinions about teaching quality, course materials, assignments, exams, instructional behavior and overall learning experience. Sentiment analysis helps educators understand student concerns, thereby improving the learning experience and promoting a student-centered learning environment. The challenges in these technologies are discussed with future directions. This review would serve as a guide to researchers in the same domain. SN - 3070-3328 PB - Institute of Central Computation and Knowledge LA - English ER -
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@article{Baskar2025A,
author = {Sowmiya Baskar},
title = {A Comprehensive Review on Techniques in Sentiment Analysis for Improving Teaching and Learning through Students’ Feedback},
journal = {Next-Generation Computing Systems and Technologies},
year = {2025},
volume = {1},
number = {1},
pages = {11-17},
doi = {10.62762/NGCST.2025.927566},
url = {https://www.icck.org/article/abs/NGCST.2025.927566},
abstract = {Getting feedback from the students in education is the key to improving the learning experience in education, but reading through hundreds of feedback forms can be overwhelming. Sentiment Analysis (SA), which is a NLP (Natural Language Processing) technique, comes in interprets the emotions and opinions behind their feedback. This review explores how various technologies like machine learning and NLP are being used to understand student opinions about teaching quality, course materials, assignments, exams, instructional behavior and overall learning experience. Sentiment analysis helps educators understand student concerns, thereby improving the learning experience and promoting a student-centered learning environment. The challenges in these technologies are discussed with future directions. This review would serve as a guide to researchers in the same domain.},
keywords = {sentimental analysis, student feedback, machine learning, natural language processing, bias},
issn = {3070-3328},
publisher = {Institute of Central Computation and Knowledge}
}
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