the Characterization of high school students in the department of Risaralda using the Chi-Square metric
Caracterización de los estudiantes de educación media en el departamento de Risaralda usando la métrica Chi-Square
DOI:
https://doi.org/10.22517/23447214.24587Keywords:
Education, Machine Learning, relevance analysis, Big Data, ICFES, Chi-square.Abstract
The education is a fundamental law that promotes the social and economic development of a nation. Also, it is how a country can achieve its sustainable development objectives. Because of this, various international organizations (Unicef-UNESCO- Banco Mundial -OECD) are promoting the coverage of education in underdeveloped countries. On the other hand, projects such as PISA that aim to carry out annual evaluations in more than 30 countries that serve as a reference of the educational level and encourages nations to improve the quality of education. Therefore, the objective of this work is to implement a methodology to predict the results of ICFES tests SABER 11 °. that can correct the educational problems that Colombia has presented in secondary education. For the development of this methodology, the ICFES repository database was used. Data were pre-processed using MATLAB software. Also, combined tests were carried out with the new Chi-Square metric developed by the researchers of the automation group of the Technological University of Pereira, obtaining results that were 20% higher compared with conventional classification techniques. In this project, the most influential characteristics were found in the students, who are responsible for the loss of the ICFES SABER 11° exam in Risaralda.
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