Abstract
The educational data mining enables the discovery of factors that make it possible to improve educational proposals, as well as to predict student performance and factors that influence learning. In view of this, the present work uses the database provided by INEP, with the purpose of explaining better which socioeconomic variables influence the grades that the students obtained in the test of the ENEM 2016, one of the examinations of major importance and with an elavada quantity untapped data. The PCA technique was applied and the Bayesian networks were generated to analyze the performance. The results show that income, parental schooling and school type are strong influencing factors.
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Thanks to CAPES and the CNPQ for their financial assistance to carry out the research.
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Santos, A.T.B., Paulino, J., Silva, M.S., Rego, L. (2020). Educational Data Mining: A Study on Socioeconomic Indicators in Education in INEP Database. In: Borah, S., Emilia Balas, V., Polkowski, Z. (eds) Advances in Data Science and Management. Lecture Notes on Data Engineering and Communications Technologies, vol 37. Springer, Singapore. https://doi.org/10.1007/978-981-15-0978-0_5
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DOI: https://doi.org/10.1007/978-981-15-0978-0_5
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