Exploring the Use of Data Science in Predicting Student Performance in Secondary Schools in Lafia Local Government Area, Nasarawa State
- Project Research
- 1-5 Chapters
- Abstract : Available
- Table of Content: Available
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- NGN 5000
Background of the Study
Data science is a rapidly growing field that leverages data analysis, statistical modeling, and machine learning algorithms to extract valuable insights from large datasets. In education, data science has been used to predict student performance, identify at-risk students, and provide personalized learning experiences. By analyzing patterns in students' grades, attendance, participation, and other factors, data science tools can help educators make data-driven decisions that improve teaching and learning outcomes. In secondary schools, the use of data science can significantly enhance the ability to monitor and predict student performance, enabling early intervention and support for students who may be struggling.
In Lafia Local Government Area, Nasarawa State, secondary schools face challenges in tracking student performance and identifying students who require additional assistance. Traditional methods of performance tracking, such as manual records and assessments, may not provide timely or comprehensive insights. This study will explore how data science techniques can be applied to predict student performance in secondary schools, potentially improving academic outcomes by identifying trends and factors that influence success.
Statement of the Problem
Secondary schools in Lafia Local Government Area struggle with tracking and predicting student performance due to a lack of advanced data analysis tools. Teachers often rely on subjective assessments and traditional grading methods, which may not capture the full range of factors affecting student achievement. By exploring the potential of data science in predicting student performance, this study seeks to identify how data-driven insights can support decision-making in education, improve performance monitoring, and provide targeted interventions for struggling students.
Objectives of the Study
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To explore the use of data science techniques in predicting student performance in secondary schools in Lafia Local Government Area.
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To assess the accuracy of data science models in predicting student academic performance.
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To identify the factors that most significantly influence student performance in secondary schools.
Research Questions
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How can data science techniques be applied to predict student performance in secondary schools in Lafia Local Government Area?
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What is the accuracy of data science models in predicting student academic performance?
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What factors most significantly influence student performance in secondary schools?
Research Hypotheses
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Data science techniques can accurately predict student performance in secondary schools in Lafia Local Government Area.
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The use of data science models improves the accuracy of performance predictions compared to traditional methods.
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Specific factors, such as attendance, participation, and past performance, significantly influence student performance.
Significance of the Study
This study will provide valuable insights into how data science can enhance student performance prediction in secondary schools. The findings could help educators and policymakers in Lafia Local Government Area make informed decisions based on data, improving academic outcomes and supporting at-risk students.
Scope and Limitations of the Study
The study will focus on the use of data science techniques for predicting student performance in secondary schools within Lafia Local Government Area, Nasarawa State. Limitations include the availability and quality of data for analysis, as well as the capacity of schools to implement data science models.
Definitions of Terms
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Data Science: The field of study that combines statistics, data analysis, and machine learning to extract meaningful insights from large datasets.
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Student Performance: A measure of a student's academic achievement, typically assessed through grades, test scores, and overall academic progress.
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Secondary Schools: Educational institutions that serve students typically between the ages of 12 and 18, covering both junior and senior secondary levels.
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