Software de análisis de rendimiento académico basado en asignaturas

Abstract

The primary objective of this project is to centralize general and final information on the subjects corresponding to the curriculum of the curricular project in Data Systematization Technology and Telematics Engineering pursued by students at Universidad Distrital Francisco José de Caldas - Faculty of Technology. The project aims to provide a conclusive visualization, through graphs, of the failure rates and retaking of each subject by students, ultimately enabling an analysis of the possible reasons and variables affecting behaviors such as continuity and retention in the educational program. To achieve this project, a system was developed using tools such as Python, SQL Server, and Power BI, which were integrated to effectively manage, process, and present the data. This proposal is integrated under the CRISP-DM (Cross-Industry Standard Process for Data Mining) methodology, which guided the process from understanding the problem to implementing the solution. The students' data and grades were stored in SQL Server, where detailed information on subjects, grades, and other relevant indicators was collected. Python was used to develop scripts for the extraction, transformation, and loading (ETL) of data, as well as to conduct preliminary analyses that calculated the percentage of students who failed each subject and identified patterns. Finally, Power BI was utilized to create an interactive graph that displays the distribution of students who failed subjects, providing teachers and the academic council with a useful tool to explore the data from different perspectives and make informed decisions. This system allows for the identification of subjects with higher failure rates, facilitating the implementation of academic support strategies to improve overall student performance.