A Case Study of Computational Thinking Analysis Using SOLO Taxonomy in Scientific–Mathematical Learning

Education nowadays requires a certain variety of resources that allow for the acquisition of 21st-century skills, including computational thinking. Educational robotics emerges as a digital resource that supports the development of these skills in both male and female students across different educational stages. However, it is necessary to investigate in depth evaluations that analyze the acquisition of Computational Thinking skills in pre-service teachers, especially when scientific and mathematical content learning programs are designed. This study aims to analyze Computational Thinking skills using the SOLO taxonomy, with an approach to science and mathematics learning, through an intervention based on programming and Educational Robotics. A quasi-experimental design was used on a total sample of 116 pre-service teachers. The SOLO taxonomy categorization was used to associate each level of the taxonomy with the computational concepts analyzed through a quantitative questionnaire. The taxonomy levels associated with Computational Thinking skills correspond to uni-structural and multi-structural levels. Males presented better results before the intervention, while subsequently, females presented better levels of Computational Thinking, as well as a greater association with the higher complexity level of learning analyzed. In turn, there was a trend between the levels of the SOLO taxonomy and computational concepts, so that an increase in skill for a concept occurs similarly at both the uni-structural level and the multi-structural level. The SOLO taxonomy is presented as a proper tool for learning assessment since it allows for a more detailed understanding of the quality of students’ learning. Therefore, the SOLO taxonomy serves as a valuable resource in the evaluation of Computational Thinking skills.