Gender Performance and Attitudes in Learning Programming

Abstract

This study examined the gender differences, academic performance, and attitudes towards programming among students, employing a mixed-methods approach. The study sample consists of male and female students enrolled in programming courses, with data collected through surveys and academic records. Statistical analyses include descriptive statistics, Mann-Whitney tests, Spearman's rank correlation, and coefficient of concordance to examine differences in performance and attitudes between genders and the relationship between academic performance and attitudes towards programming. Descriptive statistics reveal subtle gender disparities, with female students achieving slightly higher grades on average and exhibiting marginally more positive attitudes towards programming across various dimensions, including interest/enthusiasm, comfort/ease, outlook on utility, and importance of programming in future jobs. Mann-Whitney tests confirm significant differences in performance between male and female students, highlighting the need to address gender disparities in programming education. Spearman's rank correlation helps examine how academic performance and attitudes are connected, showing detailed patterns. While the overall correlation between performance and attitudes towards programming is weak, specific dimensions, such as comfort/ease and outlook on utility, show notable negative correlations with grades, suggesting potential areas for intervention. The study's findings underscore the interconnected nature of attitudes toward programming and the complex interplay between academic performance and attitudes. By fostering an inclusive learning environment and implementing evidence-based strategies, educators and policymakers can work towards ensuring equitable learning outcomes and promoting positive engagement in programming education for all students, regardless of gender or perceived academic aptitude.