Gender Differences in Computational Thinking Skills Among Elementary School Students

This study explores gender-based differences in the mastery of Computational Thinking (CT) skills among elementary school students, emphasizing the influence of social, cultural, and educational factors. Understanding these disparities is essential for promoting inclusive and equitable 21st-century skill development in early education. A descriptive qualitative design was utilized, involving 40 fourth-grade students (20 male, 20 female) from two elementary schools in Bangkinang: SD Negeri 006 Langgini and SD Negeri 004 Langgini. Data were collected through in-depth interviews, classroom observations, and documentation. Thematic analysis was conducted to identify patterns and factors contributing to gender differences in CT competencies. Findings revealed distinct gender-based variations in CT components—decomposition, pattern recognition, abstraction, and algorithmic thinking. Male students displayed higher self-confidence and active participation in technology-oriented tasks, particularly in decomposition and abstraction. In contrast, female students demonstrated more cautious, structured thinking and excelled in collaborative algorithm design. These differences were influenced by external factors, including gender stereotypes, teacher interactions, and familial support, shaping students’ engagement with CT tasks. The observed gender differences are not innate but are shaped by contextual influences. The study underscores the need for educators to adopt gender-sensitive pedagogical strategies to ensure equitable CT learning experiences. Social and educational environments significantly shape CT skill development across genders. Implementing inclusive, gender-responsive teaching methods is essential to support equal opportunities for all students in acquiring foundational digital competencies.