Educational data mining with machine learning

Authors

DOI:

https://doi.org/10.15536/reducarmais.5.2021.2417

Keywords:

Educational Data Mining, Performance Prediction, Machine Learning

Abstract

With the increase in the availability of data, especially in the educational context, specific areas have emerged for the extraction of relevant information, such as Educational Data Mining (MDE), which integrates numerous techniques that support the capture, processing and analysis of these sets of records. The main technique associated with MDE is Machine Learning, which has been used for decades in data processing in different contexts, but with the advent of Big Data there was an intensification in the application of this technique in order to extract relevant information from a huge amount of data. In this sense, this study aims to predict the performance of students, using a set of public data, and to compare which of the Machine Learning algorithms used was the most effective, in addition to indicating which are the main predictive attributes for student performance. For this, an EAW process based on 4 steps was implemented: 1) Data collection; 2) Extraction of resources and cleaning of data (Pre-Processing and Transformation); and 3) Analytical processing and algorithms; 4) analysis and / or interpretation of results. As a result, it was identified that for the data set used in this study, the Decision Trees algorithm was the most accurate - with an accuracy of 87% - as well as it was found that attributes related to school activities are more predictive of student performance than demographic and socioeconomic characteristics data.

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Author Biography

Vanessa Faria de Souza, Instituto Federal de Educação, Ciência e Tecnologia do Rio Grande do Sul

Doutoranda no PPGIE (Programa de Pós-Graduação em Informática na Educação) da Universidade Federal do Rio Grande do Sul (UFRGS). Mestre em Informática pelo PPGI (Programa de Pós-Graduação em Informática) da Universidade Tecnológica Federal do Paraná (UTFPR), na área de Computação Aplicada, e ênfase em Engenharia de Software. Possuo especialização em Educação Especial Inclusiva, com ênfase em Tecnologia Assistiva. Sou graduada em Sistemas de Informação pela Universidade Estadual do Norte do Paraná (2011). Completei a Licenciatura em Matemática, pela UTFPR. Atualmente sou docente dedicação exclusiva no Instituto Federal do Rio Grande do Sul, Campus Ibirubá, estou em afastamento para a realização do Doutorado. Ministro aulas nos Cursos de Ciência da Computação, Técnico em Informática Integrado do Ensino Médio, Licenciatura em Matemática e Especialização em Ensino de Linguagens e suas Tecnologias. Também já Atuei como Professora do Magistério Superior na Universidade Estadual do Norte do Paraná (UENP) nos cursos de Graduação Ciência da Computação e Sistemas de informação, nas disciplinas de Sistemas Digitais, Projeto e Análise de Algoritmo, Tópicos Avançados em Computação, Computação Simbólica e Numérica, Metodologia Científica. Assim como na UTFPR. Também já atuei como professora de Matemática no Ensino Básico.

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Published

2021-07-03

How to Cite

Faria de Souza, V. (2021). Educational data mining with machine learning. Educar Mais, 5(4), 766–787. https://doi.org/10.15536/reducarmais.5.2021.2417

Issue

Vol. 5 No. 4 (2021)

Section

Articles

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Copyright (c) 2021 Vanessa Faria de Souza

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