Programming Skill Development in Computer Science Education: An Analysis of Gender, GPA, and Project Domain Influence - Yogi Yunefri; Reno Renaldi; Muhammad Luthfi Hamzah; Rizki Novendra (STAI Hubbulwathan Duri, 2024)
This study examines the influence of gender, age, and academic performance (GPA) on proficiency in Python, SQL, and Java among computer science students, aiming to inform more inclusive and effective programming curricula. A quantitative approach was employed, with t-tests and ANOVA used to analyze differences in programming skills based on gender and age. Data were collected from undergraduate computer science students and evaluated using standardized programming assessments. The t-test results revealed a significant gender disparity in Python proficiency, with males scoring higher (M=2.8) than females (M=2.4; t=2.19, p=0.03). No significant gender differences were observed for SQL (t=-1.46, p=0.145) or Java (t=-1.21, p=0.227). ANOVA results indicated no significant differences in programming skills across age groups for Python (F=0.48, p=0.487), SQL (F=0.012, p=0.914), or Java (F=0.062, p=0.804). The findings suggest that gender influences Python proficiency, highlighting the need for targeted educational interventions to support female students. Conversely, instruction in SQL and Java may proceed without specific gender-based adjustments. This study underscores the importance of inclusive curricula and targeted support, such as mentorship programs and specialized training, to address gender disparities in programming education. By fostering equity, these efforts can better prepare students for success in the technology sector. Further research should explore additional factors influencing programming proficiency to refine educational strategies.