Proceedings of the International Conference on Smart Systems and Social Management (ICSSSM 2025)

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Inspecting the Paradigm of Artificial Intelligence in Sentiment Analysis of Learners’ Pursuance in Higher Education: A Review

Authors
Dillip Rout1, *, Jeebanlata Salam2, Deepshikha Routray3, P. H. Alex Khang4, Pulakala Prithvi Raj1, Pankaj Biswas1, Pritisha Goswami1
1Dept. of Computer Science and Engineering, Royal Global University, Guwahati, India
2Dept. of Sociology, Royal Global University, Guwahati, India
3Dept. of Humanities, S.C.S Autonomus College, Puri, India
4Dept. of Information Technology, Global Research Institute of Technology and Engineering, Raleigh, North Carolina, United States
*Corresponding author. Email: dillip.rout.iitb@gmail.com
Corresponding Author
Dillip Rout
Available Online 29 December 2025.
DOI
10.2991/978-94-6463-950-6_22How to use a DOI?
Keywords
Perception; GenAI; NLP; Transformers
Abstract

This paper presents a comprehensive overview of sentiment analysis among learners in higher education. It takes into account students’ perceptions both individually and collectively, evaluating the effectiveness of teaching through the lens of sentiment analysis. Specifically, it examines students’ understanding of subject delivery and their engagement during classes. Additionally, it assesses the adaptability of online learning environments in higher education, aiming to evaluate their effectiveness, identify challenges, and highlight benefits. Qualitative and quantitative measures are employed to gauge the performance of courses, which refers to both the instructor’s credibility and the students’ pursuit of knowledge. The research also delves into the sentiments of students enrolled in programming language and related software engineering courses. This study outlines the impact of emerging technology trends on higher education. It reveals that the existing dataset of course feedback may be biased, potentially skewed in favor of positive opinions over negative ones, or influenced by gender disparities. Moreover, such datasets are often scarce and may raise concerns about privacy. Nevertheless, real-time sentiment analysis of learners facilitates more effective curation of online courses. The study emphasizes the importance of integrating longitudinal and multimodal data to enhance analysis. However, challenges such as the cross-lingual mixed dataset can hinder model efficiency, despite their significance for improving explainability. Ultimately, this research emphasizes the importance of domain-specific studies and the temporal aspects of sentiment in the educational landscape. It aims to establish a solid foundation for both theory and practice in sentiment analysis within higher education, serving as a valuable resource for assessing and enhancing the higher education system.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International Conference on Smart Systems and Social Management (ICSSSM 2025)
Series
Advances in Intelligent Systems Research
Publication Date
29 December 2025
ISBN
978-94-6463-950-6
ISSN
1951-6851
DOI
10.2991/978-94-6463-950-6_22How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Dillip Rout
AU  - Jeebanlata Salam
AU  - Deepshikha Routray
AU  - P. H. Alex Khang
AU  - Pulakala Prithvi Raj
AU  - Pankaj Biswas
AU  - Pritisha Goswami
PY  - 2025
DA  - 2025/12/29
TI  - Inspecting the Paradigm of Artificial Intelligence in Sentiment Analysis of Learners’ Pursuance in Higher Education: A Review
BT  - Proceedings of the International Conference on Smart Systems and Social Management (ICSSSM 2025)
PB  - Atlantis Press
SP  - 326
EP  - 343
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-950-6_22
DO  - 10.2991/978-94-6463-950-6_22
ID  - Rout2025
ER  -