Socioeconomic Data Mining and Student Dropout (original) (raw)

International Journal for Innovation Education and Research

This paper aims to analyze the student dropout from a higher education course, in the city of Guarapari, Espírito Santo, Brazil, through the use of the computational tool known as data mining. The objective was to investigate the possible scenarios for the early identification of students with higher risk of dropping out by analyzing socioeconomic data from business school graduates between 2014 and 2018 with the use of information extracted from the academic system. The methodology used was the experimental research, from a quantitative approach through a comparative analysis of data resulting from the processing of computational algorithms. After the analysis, it was concluded that computational techniques can be used to help administrators to plan pedagogical and administrative actions and that the combination of socioeconomic data with school performance information, using the tool, can yield advantageous results, allowing the fight against evasion to be seen as an early and con...

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