Does gender influence the learning process of computational thinking in secondary education?

Abstract

The gender gap in STEM disciplines both in the workplace and in university education is still a reality. Computational thinking (CT) is deeply related to these disciplines. CT is fundamental to problem-solving and critical thinking, skills that are core to STEM disciplines. CT involves skills like algorithmic thinking, pattern recognition, and abstraction, all of which are necessary for tasks in fields such as engineering, computer science, mathematics, and science. It is important to understand gender differences, if any, in the acquisition of CT skills, so that we can develop more effective teaching strategies for all. This study analyses the gender differences in the development of CT skills (measured with a standard test) in 149 students of a Spanish secondary school, in three courses between 12 and 14 years old, before and after classroom work sessions with a 3D robotics simulator. In the empirical evidence a relevant a priori gender difference was detected in the first course, likely related with prior experiences on computer programming, but boys and girls finish the first year with similar CT levels. Disparate results appear for second year (male students improve more) and third year (female students improve more) which demands further study.