Exploring AI-Based Emotion Recognition for Improving University Student Mental Health Support: A Case Study of Modibbo Adama University, Yola (Yola North LGA, Adamawa State)
- Project Research
- 1-5 Chapters
- Abstract : Available
- Table of Content: Available
- Reference Style:
- Recommended for :
- NGN 5000
Background of the Study
Mental health has become an increasing concern in university settings, with many students experiencing emotional distress due to academic pressures, personal issues, or social challenges (Williams & Roberts, 2024). AI-based emotion recognition systems, which analyze facial expressions, vocal tone, and other physiological indicators, have shown potential in identifying students who may require mental health support (Lee & Zhang, 2025). Modibbo Adama University in Yola, Adamawa State, is an ideal case study for exploring the role of such AI technologies in improving mental health services for students.
Emotion recognition AI can provide real-time insights into a student's emotional state, enabling timely interventions and support from counselors or university mental health services (Morris et al., 2023). The technology can also help bridge gaps in traditional mental health services, where students may be reluctant to seek help or may not be able to access support quickly enough (Roberts & Thompson, 2024). Despite its promise, AI-based emotion recognition raises questions about privacy, consent, and the potential for misinterpretation of emotional data (Nguyen & Cho, 2024). This study aims to explore how AI can be leveraged to enhance mental health support services for students at Modibbo Adama University.
Statement of the Problem
Despite the growing recognition of mental health challenges in universities, many students at Modibbo Adama University struggle to access timely support due to stigma, lack of awareness, and resource constraints (Baker & Liu, 2023). AI-based emotion recognition offers a potential solution, but its effectiveness and acceptance in the university context remain unclear. There is a need to explore whether AI can truly enhance mental health services by accurately identifying students who need support and if students are willing to embrace such technology (Thompson et al., 2024). This research will examine the feasibility of AI-based emotion recognition in improving student mental health support at Modibbo Adama University.
Objectives of the Study
-
To evaluate the effectiveness of AI-based emotion recognition in identifying students in need of mental health support at Modibbo Adama University.
-
To assess the acceptance of AI-based emotion recognition technology among students and mental health professionals.
-
To investigate the ethical and privacy implications of using AI for emotion recognition in university mental health services.
Research Questions
-
How effective is AI-based emotion recognition in identifying students requiring mental health support at Modibbo Adama University?
-
What is the level of acceptance among students and mental health professionals regarding the use of AI for emotion recognition?
-
What are the ethical and privacy concerns related to the use of AI-based emotion recognition in university mental health services?
Research Hypotheses
-
AI-based emotion recognition is effective in identifying students who require mental health support at Modibbo Adama University.
-
Students and mental health professionals at Modibbo Adama University will show a positive attitude towards the use of AI-based emotion recognition for improving mental health support.
-
The use of AI-based emotion recognition in mental health services raises significant ethical and privacy concerns among students and faculty.
Significance of the Study
This study will contribute to the field of mental health and AI by providing insights into how AI can be used to improve support systems for university students. It will help universities understand the practical implications, benefits, and challenges of incorporating AI into their mental health strategies, potentially influencing policy decisions and technological investments in this area.
Scope and Limitations of the Study
This research will focus on Modibbo Adama University, Yola, Adamawa State, specifically examining the AI-based emotion recognition system's use in the context of student mental health support. It will involve students and mental health professionals who are directly engaged in this process. Limitations include the potential biases in student and faculty perceptions, as well as technological limitations of the emotion recognition system.
Definitions of Terms
-
AI-Based Emotion Recognition: The use of artificial intelligence algorithms to identify and analyze human emotions through facial expressions, voice tone, and other indicators.
-
Mental Health Support: Services provided by universities to assist students in managing mental health issues, including counseling, therapy, and wellness programs.
-
Privacy Concerns: Issues related to the protection of personal data and the potential misuse of information collected through AI technologies.
Related Project Materials
A CRITICAL ANALYSIS OF THE IMPACT OF TWITTER’S BAN ON GOVERNMENT TRANSPARENCY AND ACCOUNTABILITY
ABSTRACT
This study was carried out tocritically analyze the impact of t...
ASSESSMENT OF SUPPORTING TRANSITIONS STRATEGIES IN EARLY CHILDHOOD EDUCATION FROM HOME TO SCHOOL ENVIRONMENTS
Abstract: This research explores effective strategies to support transitions in early childhood education (E...
The Impact of Working Capital Management on the Financial Performance of Nasarawa Transport Company
Background of the Study
Effective working capital management (WCM) is critical for the financial success and sustainability of businesses...
An examination of the admissibility of forensic accounting reports in Nigerian courts: A case study of tax fraud cases
Background of the Study
The admissibility of forensic accounting reports in Nigerian courts has become a significant are...
Evaluation of AI-Based Smart Course Registration Assistance Systems in Federal University, Gusau, Zamfara State
Background of the Study
The course registration process in universities often involves complex procedures that can be time-consuming for...
An evaluation of geopolitical trends affecting child nutrition programs in Damboa Local Government Area, Borno State
Background of the Study
Damboa Local Government Area (LGA) in Borno State, located in the northeastern region of Nigeria, has faced signific...
An Assessment of Public Sector Accounting in Revenue Management in Kaltungo LGA, Gombe State
Background of the Study
Revenue management in the public sector is critical for the sustainability of local governments and the execution...
INFLUENCE OF WORLD BANK ASSISTED FADAMA II PROJECT IN PROMOTING RUMINANT PRODUCTION AMONG FARMERS IN KADUNA STATE, NIGERIA
ABSTRACT
The study was conducted to determine the influence of World Bank Assisted Fadama II in promoting ruminant production among farme...
The impact of coastal climate on the physical adaptability of residents in Brass Local Government Area, Bayelsa State
Background of the Study
Coastal climates present unique environmental challenges that shape the physical adaptability of l...
CHALLENGES FACED BY VOCATIONAL STUDENTS IN TRANSITIONING TO THE WORKFORCE
Abstract: This research investigates the challenges faced by vocational students in Nigeria...
