Machine Learning and Data Visualization to Evaluate a Robotics and Programming Project Targeted for Women

Around the world women end up being less interested in areas related to the sciences, technology, engineering and mathematics, or shortly STEM. Therefore, it is important that governments around the world maintain an active interest in getting women to continue in STEM careers. In this context, this work was divided into three main phases, the first was to conduct a search through a related works that were published involving the development of projects aimed at the engagement of girls students or female teachers/professionals within the context of STEM or Robotics, between the years 2018 and 2020. In this case, seven works were found within these criteria, including one Brazilian project. Subsequently, analyzes were carried out of the 85 projects that are being financed by the federal government of Brazil within STEM. The last analysis was a case study to evaluate the engagement of female teachers and students in a medium-sized city in the interior of the southeastern region of Brazil. In this case, we carried out the analysis with the teachers and students, as well as with an external audience. We carry out our analyzes through statistics and analysis of feelings and opinions, in addition to data visualizations. In the end, we conducted through data mining of unsupervised machine learning, analyzes of the groups of people we are interested in engaging, which are groups of young people, especially girls who are interested in STEM, but with little knowledge in Robotics. This strategy was put on the schedule, because we will aim to increase the knowledge of these girls in STEM, especially in robotics, which is the focus of our study and research group. Finally, results have shown that this project has improved a major social and encouraging role for these girls in the field of exact sciences, computing and engineering.