Integrating Sentiment Analysis with Learning Analytics for Improved Student

Authors

  • B. Paulchamy Hindusthan Institute of Technology, Coimbatore
  • Vairaprakash Selvaraj Electronics and Communication Engineering Ramco Institute of Technology Rajapalayam
  • N.M. Indumathi
  • K. Ananthi Department of Information Technology, Karpagam College of Engineering, Coimbatore
  • V.V. Teresa Associate Professor, Department of Electronics and Communication Engineering, Sri Eshwar College of Engineering, Coimbatore-641202.

DOI:

https://doi.org/10.22399/ijcesen.781

Keywords:

Sentiment analysis, Learning analytics, Emotional intelligence, Adaptive learning systems, Personalized learning, At-risk students

Abstract

The integration of sentiment analysis with learning analytics offers a novel approach to improving student outcomes by providing deeper insights into the emotional and cognitive states of learners. This research explores the use of sentiment analysis on student interactions, such as online discussions, assignments, and feedback, to assess the emotional tone of student engagement. By combining these sentiment insights with traditional learning analytics, which track academic progress and behavior patterns, this study aims to create a comprehensive model that enhances the identification of students at risk, tailor educational interventions, and fosters personalized learning experiences. The proposed approach not only improves the monitoring of student well-being and engagement but also supports the development of adaptive learning systems that respond to students’ emotional states. Results show that sentiment analysis integrated with learning analytics can provide real-time feedback for educators, enhancing student support and improving overall academic performance

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Published

2024-12-21

How to Cite

B. Paulchamy, Vairaprakash Selvaraj, N.M. Indumathi, K. Ananthi, & V.V. Teresa. (2024). Integrating Sentiment Analysis with Learning Analytics for Improved Student. International Journal of Computational and Experimental Science and Engineering, 10(4). https://doi.org/10.22399/ijcesen.781

Issue

Vol. 10 No. 4 (2024): IJCESEN

Section

Research Article

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