Design and Implementation of a Student Mental Health Monitoring System Using AI in Secondary Schools in Zaria Local Government Area, Kaduna State
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- NGN 5000
Background of the study
Mental health is a critical aspect of students' well-being, yet it often remains overlooked in the academic environment. Secondary school students in Zaria Local Government Area, Kaduna State, like their counterparts across the country, face various challenges that may adversely affect their mental health. Factors such as academic pressure, social anxiety, family issues, and the transition to adolescence contribute to mental health struggles that are not always visible to teachers or school administrators (Ibrahim & Ali, 2023). Mental health disorders such as depression, anxiety, and stress have been linked to poor academic performance, lower engagement, and higher dropout rates among students (Usman & Abubakar, 2023).
Traditional approaches to monitoring student well-being, such as periodic counseling or surveys, are often reactive rather than proactive. Artificial intelligence (AI) has the potential to offer real-time, data-driven insights into students’ mental health, enabling early intervention and personalized support (Gambo & Lawal, 2023). This study aims to design and implement an AI-powered mental health monitoring system to track and assess the mental well-being of students in secondary schools in Zaria, providing timely support and interventions.
Statement of the problem
Secondary schools in Zaria lack an efficient and proactive system for monitoring and supporting students' mental health. The absence of such a system may lead to undiagnosed mental health issues, which can negatively impact academic performance, social relationships, and overall student well-being. This study seeks to address these issues by developing an AI-powered student mental health monitoring system.
Objectives of the study
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To design an AI-based system for monitoring and assessing the mental health of secondary school students in Zaria, Kaduna State.
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To implement the mental health monitoring system in selected secondary schools in Zaria.
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To evaluate the effectiveness of the system in identifying students at risk and facilitating timely interventions.
Research questions
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How effective is the AI-based mental health monitoring system in identifying students with mental health challenges?
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What impact does the AI system have on the overall mental health awareness and intervention strategies within secondary schools in Zaria?
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How do students, teachers, and counselors perceive the usability and impact of the AI-powered mental health monitoring system?
Significance of the study
This study will contribute to the development of innovative solutions for addressing mental health issues in secondary schools, providing a proactive approach to student well-being. The findings will enhance mental health awareness, early detection, and intervention, fostering a supportive school environment and improving academic outcomes.
Scope and limitations of the study
The study will focus on the design and implementation of an AI-powered student mental health monitoring system in secondary schools within Zaria Local Government Area, Kaduna State. It will not include other regions or educational levels. The study will also not extend to the long-term effectiveness of the system beyond the duration of the research.
Definitions of terms
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AI-powered mental health monitoring system: A system that uses artificial intelligence algorithms to monitor and assess students' mental health based on behavioral data and patterns.
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Mental health: A state of well-being in which an individual can cope with the normal stresses of life, work productively, and contribute to the community.
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Early intervention: Actions taken to address mental health issues before they worsen, typically through counseling, support, or treatment.
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Real-time monitoring: The continuous tracking of a student's mental health status using automated systems that provide instant feedback.
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