Mineração de Dados Educacionais para Predição de Desempenho Profissional
uma revisão sistemática
DOI:
https://doi.org/10.22491/1982-1654.137608Abstract
The component considered one of the most crucial for academic success is professional achievement, and correct career guidance enhances students' performance and increases their level of motivation. In this study, a systematic review was conducted to assess the state of the art regarding the possibility of automating a system for predicting students' professional performance. Based on a systematic literature review model encompassing planning, implementation, and results phases, the article search process was carried out using major scientific databases. After establishing inclusion, exclusion, and quality criteria, 455 articles were identified, and among these, 5 were selected based on the guiding questions. The studies selected in this systematic review highlight variables necessary for predicting professional performance, such as grades, absences, parents' education, school, private lessons; and the Weka framework emerged as the predominant tool in these studies.
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Published 2024-06-30
