DATAVIEW: Data Analysis Tool and its Impacts on Education 4.0
Education 4.0, Educational Data Mining, Data Science
The purpose of this research is to propose a data analysis tool to transform data into useful information for the teaching and learning process, through the use of educational data mining (EDM). Aiming at personalizing the educational context and offering knowledge for making pedagogical decisions in a strategic way, contributing to education 4.0. For this, the ideation process of the platform began, being carried out based on the literature
review and meetings with teachers. Then, the requirements gathering process began, being materialized through prototyping and beginning the implementation of the solution. Throughout the process, the Cross-Industry Standard Process of Data Mining (CRISP-DM) method was used. The results showed that with the EDM it is possible to identify the profiles and predict the students’ performance, with good reliability, before applying the evaluation of the first unit. In addition, through the platform, it will be possible to make knowledge available according to the objective of the different educational actors, allow the optimization of the teachers’ time, and assist in the evaluation method, especially if it is continuous. With this, it will be possible to create improvements in educational
practices that encourage learning, motivation, and retention of students in the subjects, mitigating failure, and dropout rates.