Análisis del perfil vocacional de estudiantes de bachillerato para carreras de STEAM

Abstract

Abstract: In the present data science work, a survey was conducted to collect information and carry out an exploratory univariate analysis and a bivariate correlational analysis, with the objective of analyzing the vocational profile of high school students in relation to STEAM careers. In this process, several data exploration, cleaning and tabulation techniques were used to guarantee the quality and reliability of the data for processing. The OSEMN methodology was used, which is used for data science and has several stages, collection, cleaning, exploration, modeling and interpretation. To analyze data and discover patterns of influence on students when selecting STEAM careers. In addition, tools and techniques were used to clean and carefully select the most relevant data and transform the results into interactive dashboards using technological visualization tools, allowing a clear and understandable representation of the findings. The dashboards not only present the results in a comprehensive manner but also allow identifying trends and relationships between variables that determine the causes of student dropout in terms of STEAM careers, providing a solid basis for educational decision making and future projects to drive interest towards students.