Mineração de Dados Educacionais para Aperfeiçoamento da Gestão do E-learning: uma Revisão Sistemática de Literatura

Abstract

Purpose: Since the mining of educational data helps to analyze the large amount of data generated by e-learning systems, improving the teaching-learning systems, the present study seeks, through a systematic literature review, to check how the topic has been, in recent years, researched. Approach: Once this context is new, emerging and dynamic and that needs analysis of its structure to understand its dynamics, difficulties and potential, this study was developed to analyze the existing structures of elearning systems, as well as to identify how the educational data mining process can be applied in elearning. Results: The results are divided into two parts: (i) descriptive analysis, in which the articles are presented from a bibliometric analysis, and (ii) semantic analysis, in which the articles are analyzed using the four-step model of the educational data mining process. Contributions: The results contribute with practical and academic recommendations, as they present as much as the process of data mining interferes in the management of e-learning, as well as an overview of the existing researches, in order to know the current research of the analyzed theme.