What Do the Data Reveal About Women and Men in Technology?

In recent years, persistent disparities in compensation and representation between genders have been revealed in various sectors, most notably in computer science and engineering. This ongoing issue accentuates a critical inequality that necessitates comprehensive and systematic actions. A significant contributing factor is women's relative lack of interest in technology and computing domains. This topic has not received ad-equate investigation in broader discussions surrounding Science, Technology, Engineering, and Mathematics (STEM) fields. As an incentive for the retention and entrance of women in the field, initiatives have emerged in Brazil, such as the Meninas Digitais program, an extension project to encourage and support women in information technology and the sciences. These initiatives aim to combat stigmas and promote gender equality in STEM. This research aims to thoroughly analyze women's participation and performance within computing and technology programmes. The present investigation concerns the low enrollment rates of women in technology-related higher education programs, which contributes to a predominantly male workforce and exacer-bates existing gender disparities, potentially stifling technological advancement. Utilizing a decade's data from undergraduate affiliates at the Universidade Federal de Santa Catarina (UFSC), this study employed machine learning techniques to examine trends surrounding dropout rates, admissions, retention, and academic performance of female students in technology and engineering. The findings reveal that women often achieve strong academic results but remain significantly underrepresented in these fields. This scenario underscores an urgent need for targeted educational policies that foster gender equality and inclusivity. Additionally, the research identifies potential shortcomings within the Brazilian primary education system and highlights specific challenges female students face in transitioning to university life, particularly those linked to socioeconomic factors.