Utilizing Data Science to Analyze Student Performance Trends in STEM Education: Insights for Enhancing Curriculum Design

Abstract

The performance of students in STEM courses at higher education institutions is examined in depth in this research. The fields of science, technology, engineering, and mathematics (STEM) are becoming increasingly important, and creating effective teaching practices requires an awareness of the elements that affect student success. This research uses a data-driven methodology to analyze performance trends in various STEM fields, finding essential trends and insights that can guide the creation of curricula, teaching strategies, and student support programs. This paper identifies the areas where students' achievements and their inability to understand basic STEM courses. The results provide insight into how introductory courses affect students' academic performance. This paper presents higher education professionals and policymakers with practical insights that help improve student achievements, refine pedagogical approaches, and strengthen STEM education initiatives.