Publication: Técnicas de análisis para la mejora y predicción del rendimiento académico
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2017
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Abstract
Desde hace varias décadas, profesores y pedagogos han mostrado un fuerte interés en la posibilidad de predecir cuál va a ser el desempeño académico de los estudiantes. Por ello, se han realizado multitud de estudios teniendo en cuenta variables socioeconómicas y de carácter académico. Sin embargo, apenas hay herramientas que permitan a educadores y alumnos hacer una predicción real de cuáles pueden ser los resultados a final de curso.
Por otro lado, los docentes pueden encontrarse con mucha información de cada uno de sus alumnos que sea difícil de gestionar o analizar de forma conjunta. Hay herramientas que les permiten hacer estadísticas simples con facilidad, pero pocas que permitan combinar más de tres variables distintas. Este proyecto pretende hacer una primera aproximación a estos problemas. El objetivo es desarrollar una herramienta que permita al profesor analizar el desempeño actual de sus alumnos, así como tener una visión previa de cuáles pueden ser los resultados a final de curso.
Para hacer esto, el proyecto consta de tres funcionalidades principales que intentarán ayudar a los profesores a hacer un seguimiento de sus clases: la primera se trata de un analizador estadístico, cuya función es dar forma a todos los datos de los que disponga el sistema para hacerlos más comprensibles. La segunda es un agrupador de información. El objetivo de esta funcionalidad es proporcionar al profesor grupos de alumnos que presentan un determinado patrón de comportamiento. Por último, está la funcionalidad de predicción. Esta parte se encarga de predecir la potencial nota de cada estudiante basándose en experiencia adquirida de cursos anteriores.
For several decades, teachers and pedagogues have shown an interest in the possibility of predicting their students future performance. For this reason there have been several studies taking into account socioeconomic and academic variables. However, there are few tools that allow educators and students to make a real prediction of their likeky final marks. What’s more, teachers can find themselves with a lot of information about their pupils, but this info could be difficult to process or analyze as a whole. There are tools that allow them to do simple statistics easily, but very few of them allow combinations of more than three different variables. This project aims to make a first approach to these problems. Our objective is developing a tool that anables the teacher to analyze their pupils present performance, as well as have a preliminary view of their probable results at the end of the school year. To achieve this, the project consist of three main functionalities with the aim of helping teachers to track their classes: The first one is an statistical analyzer. Its function is giving shape to all the data avaliable to the system, to make them easier to understand. The second one is an information cluster. Its function is showing the teacher groups of students with a given behavioral pattern. The last functionality is prediction. This section function is predicting the potential grade of any student based on the experience from previous years.
For several decades, teachers and pedagogues have shown an interest in the possibility of predicting their students future performance. For this reason there have been several studies taking into account socioeconomic and academic variables. However, there are few tools that allow educators and students to make a real prediction of their likeky final marks. What’s more, teachers can find themselves with a lot of information about their pupils, but this info could be difficult to process or analyze as a whole. There are tools that allow them to do simple statistics easily, but very few of them allow combinations of more than three different variables. This project aims to make a first approach to these problems. Our objective is developing a tool that anables the teacher to analyze their pupils present performance, as well as have a preliminary view of their probable results at the end of the school year. To achieve this, the project consist of three main functionalities with the aim of helping teachers to track their classes: The first one is an statistical analyzer. Its function is giving shape to all the data avaliable to the system, to make them easier to understand. The second one is an information cluster. Its function is showing the teacher groups of students with a given behavioral pattern. The last functionality is prediction. This section function is predicting the potential grade of any student based on the experience from previous years.
Description
Trabajo de Fin de Grado en Ingeniería Informática (Universidad Complutense, Facultad de Informática, curso 2016/2017)