Dataset on the Impact of Programming Platforms with Simulated Robotics on Computational Thinking and Gender Analysis in Secondary Education

This dataset was collected during a quasi-experimental study involving 161 secondary school students (aged 14) from Madrid, Spain. The objective was to evaluate the impact of three programming environments—Scratch (2D), Scratch with Kibotics (3D robotics simulation), and Python with Kibotics—on the development of Computational Thinking (CT) skills. The data includes pre-test and post-test scores based on a validated CT assessment instrument, as well as programming exam scores and item-level data related to CT subskills (loops, conditionals, functions, etc.). Gender, platform, and programming language are also included as independent variables for analysis. The study also explores the effect of these tools on reducing gender gaps in CT education.

The dataset is anonymized and includes both raw scores and normalized results (0–10 scale). It can be used to reproduce the statistical analysis of the study, to conduct further research in STEM education, or to test machine learning models for educational data mining.