Analysis of the Use of Big Data Analytics in Educational Decision-Making in Secondary Schools in Lafia Local Government Area, Nasarawa State
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- NGN 5000
Background of the study
Big data analytics has revolutionized multiple sectors, including education, by providing decision-makers with insightful, data-driven strategies. In the context of secondary schools in Lafia Local Government Area, Nasarawa State, big data analytics can be utilized to improve educational outcomes by analyzing large datasets from various school activities. These datasets include student performance, attendance, demographic information, and behavioral patterns. By leveraging big data, educational administrators can make informed decisions regarding curriculum development, resource allocation, student support systems, and teaching methodologies (Khalid et al., 2023).
The application of big data in education can help schools identify trends and patterns that might otherwise go unnoticed, allowing for timely interventions and targeted improvements. For instance, by analyzing student performance data over time, educators can predict which students may require additional support, thus improving retention rates and academic success. However, the use of big data in secondary schools in Lafia presents challenges, such as data privacy concerns, the need for skilled data analysts, and the cost of implementing data collection systems. This study will explore how big data analytics is currently used in the decision-making processes of secondary schools in Lafia and evaluate the effectiveness of its application.
Statement of the problem
Despite the potential benefits of big data analytics in educational decision-making, secondary schools in Lafia Local Government Area face several obstacles in utilizing this technology. These include insufficient infrastructure, lack of trained personnel to analyze the data, and concerns about student data privacy. The study will investigate how big data is currently being used in educational decisions and explore the barriers that hinder its full integration into school management practices.
Objectives of the study
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To assess the extent to which big data analytics is used in educational decision-making in secondary schools in Lafia.
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To identify the challenges faced by secondary schools in Lafia when integrating big data analytics into their decision-making processes.
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To evaluate the impact of big data analytics on student performance, resource allocation, and administrative decisions in Lafia secondary schools.
Research questions
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How is big data analytics currently being used in educational decision-making in secondary schools in Lafia?
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What challenges do secondary schools in Lafia face in integrating big data analytics into their decision-making processes?
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What impact does big data analytics have on educational outcomes and administrative decisions in secondary schools in Lafia?
Significance of the study
This study will provide valuable insights into how big data analytics can enhance educational decision-making in secondary schools, offering strategies for overcoming implementation challenges and maximizing its potential. The findings will be instrumental for policymakers, educators, and school administrators in improving educational practices and outcomes.
Scope and limitations of the study
The study focuses on secondary schools in Lafia Local Government Area, Nasarawa State, and specifically investigates the role of big data analytics in educational decision-making. It does not extend to other areas or education levels beyond secondary schools.
Definitions of terms
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Big data analytics: The process of examining large and complex datasets to uncover hidden patterns, correlations, and trends.
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Educational decision-making: The process by which school administrators and educators make informed decisions regarding teaching methods, resource allocation, and student support.
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Data privacy: The protection of personal information, such as student data, from unauthorized access or disclosure.
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