Conference Agenda

This paper addresses the need for diagnostic tools with a gender perspective in higher education, focusing on the field of architecture. It proposes the design of a structured questionnaire to explore the self-perception of female university students in three key areas: academic equality, psychological well-being, and career expectations. The instrument is based on consolidated theoretical frameworks and aims to generate quantitative data that can identify gaps, burnout risks, and resilience levels. This article details the instrument's construction, its theoretical foundations, and its potential applications as a diagnostic tool for academic institutions. It is concluded that the implementation of this instrument can catalyze actions for more equitable and inclusive education, laying the groundwork for future larger-scale research to validate its findings in broader populations

In this work, we explore the perceptions and self-perceptions of the role of women in the Systems Engineering program at Universidad de San Buenaventura, Cali. Based on an open-ended survey applied to 33 participants, female and male narratives were analyzed using natural language processing techniques supported by artificial intelligence. The results reveal tensions that affect women’s educational experience, such as low female representation in the classroom and the need for constant validation. At the same time, discourses of recognition and leadership emerge, although in some cases mediated by positive stereotypes. From the male perspective, a spectrum can be observed ranging from active recognition to resistance against inclusion policies, reflecting the persistence of meritocratic views. These findings highlight the importance of designing pedagogical strategies that promote gender equity, make female role models visible, and create safe spaces to strengthen women’s participation and retention in engineering environments.

This article presents the initial findings of the STEM without Gender Boundaries project, developed by three Colombian universities. Through a survey of 1,860 undergraduate students in STEM programs, key constructs such as academic self-efficacy, gender-identity-career compatibility, sense of belonging, and intention to drop out were evaluated.
The results show significant gender gaps: women report lower belonging and identification with the STEM environment, which is related to a higher intention to drop out. Patterns are observed that point to a possible mediating role of the sense of belonging and the perceived value of STEM work. These findings guide institutional recommendations to promote inclusive trajectories from a gender perspective.

This article aims to explore the perceptions of university students enrolled in STEM programs regarding fourteen sociocognitive constructs, with an emphasis on gender differences. The research addresses the persistent gap in female participation in STEM fields, documented both nationally and internationally, which calls for rigorous analytical approaches.

The study was conducted at EAFIT University (Medellín, Colombia), based on a sample of 1,007 undergraduate engineering students, from which 665 valid records were analyzed. A structured questionnaire was used, consisting of 97 variables, 67 of which employed Likert-type scales associated with constructs such as self-efficacy, self-regulation, sense of belonging, motivation, among others.

The CRISP-DM methodology was applied for the analysis process, including data cleaning and transformation, internal consistency evaluation, inferential statistics, dimensionality reduction through principal component analysis (PCA), and modeling using unsupervised clustering algorithms (K-means and DBSCAN). Evaluation was performed using the silhouette index.

The clustering models did not identify well-defined subgroups, showing a concentration of data in a single cluster and low silhouette values (<0.5), suggesting high perceptual homogeneity. However, inferential statistics revealed significant gender differences in 9 out of the 14 constructs. These findings provide a foundation for developing more equitable education policies, based on evidence and focused on the dimensions that reflect actual gaps.

This research indicates how the incorporation of STEAM (Science, Technology, Engineering, Arts, Mathematics) in academic, professional, and vocational contexts, together with the use of Artificial Intelligence (AI) as an innovative tool, improves the performance of female engineers in maintenance. There should be activities that allow more women to be incorporated into the field of technical maintenance, ensuring their inclusion in different productive sectors through technologies such as AI. To this end, cultural changes must be made in inclusion laws with legal frameworks that encourage women in these areas, especially those who are attracted to this sector. Professional organizations can be created to promote STEAM training programs with scholarships or grants and personalized advice that connect interested young women with companies. It is also recommended to hold scientific forums on projects, job offers, and training in STEAM and AI applied to maintenance, as well as a directory of women leaders in this sector. This would increase the positioning of women engineers in maintenance, enhancing their role through approaches that foster creativity and AI tools that facilitate process prediction and optimization.