Enhancing Secondary School Student Retention with AI-Based Early Warning Systems in Ganye LGA, Adamawa State
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- NGN 5000
Background of the study
Student retention in secondary schools is a significant concern in many parts of Nigeria, including Ganye Local Government Area (LGA) in Adamawa State. Factors such as poor academic performance, socio-economic challenges, and lack of student engagement contribute to high dropout rates in secondary schools. AI-based early warning systems (EWS) have been increasingly adopted to predict students at risk of dropping out by analyzing various data points such as academic performance, attendance patterns, and behavioral trends. These systems use machine learning and predictive analytics to identify students who may need additional support and intervention before they disengage from their education. This study aims to explore how AI-based early warning systems can be used to enhance student retention in secondary schools in Ganye LGA, Adamawa State, by providing timely support to at-risk students.
Statement of the problem
Secondary school dropout rates in Ganye LGA, Adamawa State, remain a significant issue, with many students failing to complete their education due to a variety of personal, academic, and socio-economic factors. Traditional methods of identifying at-risk students are often reactive and may come too late for effective intervention. AI-based early warning systems could provide proactive solutions by predicting students' risk levels and enabling timely interventions. However, the effectiveness of such systems in improving student retention in the specific context of Ganye LGA remains to be fully explored. This research will investigate the feasibility of implementing AI-based early warning systems to enhance retention rates and improve educational outcomes for students in Ganye LGA.
Objectives of the study
1. To design and implement an AI-based early warning system to predict at-risk students in secondary schools in Ganye LGA.
2. To assess the effectiveness of the AI-based system in improving student retention rates in secondary schools.
3. To explore the impact of early interventions on students' academic performance, attendance, and overall engagement.
Research questions
1. How effective is the AI-based early warning system in identifying students at risk of dropping out in Ganye LGA?
2. What impact does the implementation of an AI-based early warning system have on student retention rates in secondary schools?
3. How does early intervention based on AI predictions influence students' academic performance and engagement?
Research hypotheses
1. AI-based early warning systems will significantly reduce dropout rates in secondary schools in Ganye LGA.
2. The implementation of AI-driven interventions will improve students' academic performance and engagement.
3. Students identified by the AI system will show improved retention rates due to timely intervention.
Significance of the study
This research will provide critical insights into the use of AI-based early warning systems to improve student retention in secondary schools in Ganye LGA, Adamawa State. The findings will be valuable for educational policymakers, school administrators, and educators in designing more effective retention strategies and enhancing student outcomes in the region.
Scope and limitations of the study
The study focuses on the implementation of AI-based early warning systems in secondary schools in Ganye LGA, Adamawa State. It will assess the system's ability to predict dropout risks and its impact on student retention. Limitations include challenges in data availability, the need for school staff training, and resistance to new technologies.
Definitions of terms
• Artificial Intelligence (AI): The use of algorithms and machine learning techniques to analyze data and make predictions or decisions.
• Early Warning System (EWS): A system designed to identify students at risk of failing or dropping out based on various indicators such as academic performance and attendance.
• Student Retention: The ability of educational institutions to keep students enrolled and engaged until they complete their studies.
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