Analyzing Student Achievement in Statistics: A Cross-Disciplinary Perspective

Abstract

The field of statistics has transformed into an essential knowledge for decision making and addressing complex issues across various domains. The objective of this research is to reveal the challenges confronting students, proffer strategies for refining pedagogy and underscore the profound transformative potential of statistical insight across both academic and professional realms. Through a comprehensive analysis of existing literature. Our studies assesses student performance in two statistics quizzes, encompassing fundamental and advanced concepts across diverse academic backgrounds. It successfully achieves its objectives by comprehensively analyzing quiz results, student’s statistical concepts and informing educational improvements. The research evaluates student performance in specific quiz sections, equipping educators for informed teaching adjustments. Furthermore, it identifies the influence of course content on student’s question responses, enriching our understanding of learning outcomes. Additionally, through Structural Equation Modeling (SEM), the study uncovers relationships between latent variables and quiz responses, illuminating factors contributing to performance. Rigorous analyses results, including summary statistics, odds ratios and SEM ensure question reliability with Cronbach's Alpha. Visual tools effectively present findings, empowering educators and curriculum designers with actionable insights to improve statistical education and support students across disciplines.