Promoting Gender Equity Through a STEM Kit and Visual Programming to Develop Computational Thinking in the Early Years of University Education

This article analyzes the development of computational thinking dimensions by gender among students from Industrial Engineering and Systems Engineering programs at universities in the Andean region of Peru. Two key dimensions were assessed: computational concepts (including sequence, events, conditionals, loops, operators, data, and parallelism) and computational practices (experimenting and interacting, testing and debugging, reusing previous projects, and abstracting and modularizing). The study employed a post-test quasi-experimental design with intentional non-probability sampling. Technological projects with a contextual and community-based focus—related to agriculture, livestock, environment and safety—were developed using a STEM Learning Kit with sensors, actuators, and the mBlock visual programming environment. Results showed no statistically significant differences between male and female students in overall computational thinking performance. However, when analyzing achievement levels, the researchers found that notable differences emerged: most women in Systems Engineering reached expected or outstanding conceptual levels, while most students in both programs and genders remained at the beginning level in computational practices. Women in Industrial Engineering exhibited greater variability in practical achievement, suggesting higher potential for progress. These findings confirm that integrating contextualized technological projects with visual programming is an effective pedagogical strategy to enhance computational thinking across genders and promote gender equity in STEM from the early years of university education.