ARCHIVES
VOL. 10, ISSUE 3 (2025)
AI-Powered Emotional Intelligence analysis for student Mental Health monitoring in Schools
Authors
Mahendra Vishwanath Thakare, Mahesh Ramesh Kandekar
Abstract
AI-powered emotional intelligence (EI) analysis is revolutionizing
student mental health monitoring in schools by leveraging machine learning and
natural language processing to assess emotional well-being in real-time. This
research explores an innovative framework that integrates AI-driven sentiment
analysis, facial expression recognition, and behavioral pattern tracking to
identify early signs of psychological distress, anxiety, or depression among
students. By utilizing multimodal data sources such as voice tone, textual
responses, and facial cues, the system ensures a holistic understanding of
students' emotional states while maintaining ethical considerations like data
privacy and consent. The proposed approach enhances the ability of educators
and counselors to intervene proactively, offering timely support and
personalized interventions tailored to individual student needs. This paper
also discusses the implementation challenges, including algorithmic bias, data
security, and integration with existing school systems, while emphasizing the
potential of AI in fostering a healthier and more supportive learning
environment. Through empirical evaluation and case studies, the study
demonstrates the effectiveness of AI-powered EI analysis in improving mental
health awareness and support within educational institutions, ultimately
contributing to students' overall academic and personal development.
Download
Pages:143-146
How to cite this article:
Mahendra Vishwanath Thakare, Mahesh Ramesh Kandekar "AI-Powered Emotional Intelligence analysis for student Mental Health monitoring in Schools ". International Journal of Advanced Scientific Research, Vol 10, Issue 3, 2025, Pages 143-146
Download Author Certificate
Please enter the email address corresponding to this article submission to download your certificate.