Desarrollo de modelos para predecir el rendimiento académico mediante inteligencia artificial
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2022
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Abstract
El desarrollo de la inteligencia artificial está consiguiendo mejoras en todos los campos de aplicación. Una de las funciones más utilizadas en inteligencia artificial es el análisis de datos y la generación de modelos predictivos. Gracias al análisis de datos con inteligencia artificial se obtienen resultados reveladores que ayudan a mejorar los servicios en muchas instituciones. Como no podía ser menos, el campo de la educación también se puede beneficiar de esta tecnología. Es gracias a la educación que se consigue desarrollar a las personas y, por lo tanto, cualquier mejora en este ámbito es provechoso para la sociedad. En este trabajo de fin de grado se ha diseñado una herramienta web capaz de realizar predicciones de rendimiento académico sobre alumnos universitarios. Estas predicciones nos pueden brindar información muy valiosa acerca de los factores que afectan al rendimiento de los estudiantes. No solo analiza las calificaciones del alumno sino, también, los datos socioeconómicos, lo que permite obtener conclusiones que de otra manera no habrían sido posibles con un análisis convencional. A parte de dar otra perspectiva, esta herramienta tiene otra ventaja y es que puede analizar gran cantidad de datos de una forma muy rápida, y, ya que se puede aplicar en cualquier titulación universitaria, se espera que este software pueda aportar su granito de arena a la mejora en la educación.
The development of artificial intelligence is a leading to improvements in all fields of application. One of the most widely used functions in artificial itelligence is data analysis and generating predictive models. Thanks to data analysis with artificial intelligence, revealing results are obtained that help improve services in many institutions. Of course, the field of education can also benefit from this technology. It is thanks to education that people are able to develop and, therefore, any improvement in this field is beneficial to society. In this final degree project, a web tool has been designed that is capable of making academic performance predictions for university students. These predictions can provide us with valuable information about the factors that affect student performance. It analyses not only the student's grades but also socio-economic data, which allows conclusions to be drawn that would not otherwise have been possible with conventional analysis. Apart from giving another perspective, this tool has another advantage in that it can analyse large amounts of data very quickly, and since it can be applied to any university degree, it is hoped that this software cancontribute to the improvement of education.
The development of artificial intelligence is a leading to improvements in all fields of application. One of the most widely used functions in artificial itelligence is data analysis and generating predictive models. Thanks to data analysis with artificial intelligence, revealing results are obtained that help improve services in many institutions. Of course, the field of education can also benefit from this technology. It is thanks to education that people are able to develop and, therefore, any improvement in this field is beneficial to society. In this final degree project, a web tool has been designed that is capable of making academic performance predictions for university students. These predictions can provide us with valuable information about the factors that affect student performance. It analyses not only the student's grades but also socio-economic data, which allows conclusions to be drawn that would not otherwise have been possible with conventional analysis. Apart from giving another perspective, this tool has another advantage in that it can analyse large amounts of data very quickly, and since it can be applied to any university degree, it is hoped that this software cancontribute to the improvement of education.
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Trabajo Fin de Grado en Ingeniería Informática, Facultad de Informática UCM, Departamento de Arquitectura de Computadores y Automática, Curso 2021/2022.