AI in Education: Early Detection of Mental Health Challenges for Inclusive and Supportive Learning

Document Type

Article

Source of Publication

AI in Learning Educational Leadership and Special Education Innovations and Ethical Dilemmas

Publication Date

8-6-2025

Abstract

As schools confront an escalating mental health crisis among students, artificial intelligence (AI) emerges as both a solution and a complex ethical challenge. The ability of AI to analyze vast amounts of data through natural language processing, sentiment analysis, and behavioral pattern recognition provides a proactive approach to identifying early signs of emotional distress. By monitoring shifts in academic engagement, social interactions, and behavioral trends, AI moves beyond traditional, reactive mental health interventions, enabling earlier and more targeted support. However, while AI-driven detection is compelling, its implications raise urgent questions about its role in education and student well-being. Beyond technical feasibility, the long-term psychological, academic, and social impact of AI-driven mental health detection remains unexplored. While AI nurtures more inclusive and supportive learning environments, it becomes a tool of surveillance, reinforcing biases, or enabling dependency on automated decision-making.

ISBN

[9798337305738, 9798337305752]

ISSN

2327-0411

Publisher

IGI Global Scientific Publishing

First Page

247

Last Page

290

Disciplines

Computer Sciences | Education

Keywords

AI in Education, Mental Health, Early Detection, Inclusive Learning, Supportive Learning

Scopus ID

105017839266

Indexed in Scopus

yes

Open Access

no

Link to Full Text

Share

COinS