Evaluation of the Impact of Data-Driven Decision-Making on Secondary School Management in Jalingo Local Government, Taraba State
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- NGN 5000
Background of the Study
Effective management of secondary schools is crucial for ensuring high-quality education and optimal resource utilization. In Jalingo Local Government, Taraba State, traditional management practices often rely on historical data and manual decision-making processes, which may not accurately reflect the current needs and challenges of schools. Data-driven decision-making leverages advanced analytics and big data techniques to inform strategic decisions by analyzing real-time data on student performance, attendance, teacher effectiveness, and resource allocation (Chinwe, 2023). By integrating data from multiple sources, administrators can gain a comprehensive understanding of school operations, identify bottlenecks, and implement targeted interventions to improve educational outcomes. Data-driven approaches facilitate transparent and evidence-based decision-making, thereby increasing accountability and fostering continuous improvement within the educational system. Additionally, predictive analytics can forecast future trends and challenges, enabling proactive measures that mitigate risks and enhance academic performance (Ibrahim, 2024). Visualization tools and dashboards further empower school leaders to monitor key performance indicators and adjust policies dynamically. Despite these advantages, challenges such as data quality issues, limited technical expertise, and resistance to change among staff remain significant obstacles. This study aims to evaluate the impact of data-driven decision-making on secondary school management in Jalingo Local Government by examining how data analytics can transform administrative practices, optimize resource allocation, and improve overall school performance (Olufemi, 2025). The research seeks to provide actionable insights that can be used to develop a more responsive and efficient management system, ultimately enhancing the quality of education.
Statement of the Problem
Secondary schools in Jalingo Local Government currently face numerous management challenges, including inefficient resource allocation, delayed responses to performance issues, and a lack of transparency in decision-making processes. Traditional management practices rely on historical data and manual analysis, which often fail to capture the dynamic nature of educational environments and do not support proactive intervention strategies (Adebola, 2023). As a result, school administrators struggle to make timely and informed decisions that can address issues such as student underperformance, teacher absenteeism, and inadequate funding for critical programs. Furthermore, the fragmentation of data across different systems complicates the ability to develop a holistic view of school operations, leading to suboptimal outcomes and a decline in educational quality. The absence of a data-driven framework prevents the effective monitoring of key performance indicators, making it difficult to identify and address emerging challenges. This study seeks to address these issues by investigating the impact of data-driven decision-making on secondary school management. The research will develop a framework that integrates data from multiple sources, applies advanced analytics, and provides real-time insights to facilitate better decision-making. Ultimately, the goal is to enhance administrative efficiency, improve resource management, and promote a culture of continuous improvement in secondary schools.
Objectives of the Study:
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To develop a framework for data-driven decision-making in secondary school management.
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To evaluate the impact of data analytics on resource allocation and performance monitoring.
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To recommend strategies for enhancing administrative efficiency through data integration.
Research Questions:
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How does data-driven decision-making improve school management?
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What are the key benefits of using data analytics in secondary schools?
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What challenges must be addressed to implement a data-driven management system effectively?
Significance of the Study
This study is significant as it demonstrates the potential of data-driven decision-making to transform secondary school management in Jalingo Local Government. By leveraging advanced analytics, the research provides actionable insights to improve resource allocation, performance monitoring, and overall administrative efficiency. The findings will assist educators and policymakers in developing more effective management strategies, ultimately enhancing the quality of education and operational transparency in secondary schools (Chinwe, 2023).
Scope and Limitations of the Study:
The study is limited to the impact of data-driven decision-making on secondary school management in Jalingo Local Government, Taraba State, and does not extend to other educational levels or regions.
Definitions of Terms:
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Data-Driven Decision-Making: The process of making decisions based on the analysis of quantitative data.
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Resource Allocation: The distribution of available resources to various functions or departments.
Performance Monitoring: The continuous assessment of institutional outcomes using key performance indicators.
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