Thesis Abstract

Abstract
This thesis explores the analysis of factors influencing student performance in higher education using statistical modeling. The study aims to investigate the various elements that have an impact on student academic achievement in higher education institutions. The research is motivated by the importance of understanding the factors that contribute to student success, as this knowledge can inform educational practices and policies to enhance student outcomes. The research methodology employed in this study involves the collection and analysis of data from multiple sources, including academic records, student surveys, and institutional databases. Statistical modeling techniques, such as regression analysis and data mining, are used to identify and examine the relationships between different factors and student performance. The findings of this study reveal several key factors that significantly influence student performance in higher education. These include variables such as prior academic achievement, study habits, socio-economic background, and access to support services. The analysis also highlights the importance of factors like class attendance, engagement in extracurricular activities, and time management skills in predicting student success. The implications of these findings are discussed in relation to educational practices and policies aimed at improving student performance in higher education. Recommendations are provided for institutions to enhance student outcomes through targeted interventions and support programs based on the identified influential factors. Overall, this thesis contributes to the existing body of knowledge on factors influencing student performance in higher education and provides valuable insights for educators, policymakers, and researchers. By understanding and addressing these factors, institutions can better support students in achieving their academic goals and enhancing their overall educational experience. Keywords Student performance, Higher education, Statistical modeling, Factors, Academic achievement, Educational practices, Support services

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