ANALYSIS OF THE CORRELATION BETWEEN BASIC MATHEMATICAL SKILLS AND SUCCESS IN LEARNING INTRODUCTORY PROGRAMMING AMONG FIRST-SEMESTER INDUSTRIAL ENGINEERING STUDENTS

Abstract

Introductory programming is a vital course for Industrial Engineering students, as it supports data analysis, simulation, and systems modeling. However, students' understanding of programming is significantly influenced by basic mathematical skills, particularly logic, algebra, and arithmetic. This study aims to analyze the relationship between basic mathematical skills and success in learning introductory programming among first-semester Industrial Engineering students. The research employs a quantitative approach, using basic mathematics tests and programming learning evaluations as instruments. Data analysis was conducted using Pearson’s correlation to determine the degree of relationship between the two variables. The results indicate a significant positive correlation between basic mathematical skills and programming success. Students with better mathematical skills tend to grasp algorithms, control structures, and debugging more quickly. These findings underscore the importance of strengthening basic mathematics as a foundation for programming and provide recommendations for educational institutions to offer math reinforcement modules for freshmen.