Spatial analysis of academic performance in the areas of systems and telematics in the Saber Pro tests in the Colombian Caribbean

Abstract

Objective: To conduct a study based on spatial data analysis to characterize academic performance in the five competencies of the Saber Pro tests, carried out by students of Systems Engineering and related programs in the departments of the Colombian Caribbean. Methodology: For the development of this research, a four-phase adaptation of the CRISP-DM methodology was utilized: F1. Business and data understanding, F2. Data preparation, F3. Modeling, F4. Evaluation and analysis. Results: As a result, the analysis of quantiles identified the departments in the Caribbean coast with the highest and lowest performance across the five areas of the test. Additionally, spatial regression analysis was used to determine the correlation among the five competencies of the test. Finally, spatial clustering analysis identified groups of departments that collectively achieved the best and worst results. Conclusions: the results obtained in this study are intended to guide strategic decision-making aimed at improving the quality of education in the Colombian Caribbean coast. Furthermore, the proposed study serves as a foundation for extrapolating spatial data analysis to other regions and specific levels of the Saber tests.