عنوان انگلیسی مقاله:
Educational data mining: Predictive analysis of academic performance of public school students in the capital of Brazil
ترجمه فارسی عنوان مقاله:
داده کاوی آموزشی: تجزیه و تحلیل پیش بینی کننده عملکرد علمی دانش آموزان مدارس دولتی در پایتخت برزیل
Sciencedirect - Elsevier - Journal of Business Research, 94 (2019) 335-343: doi:10:1016/j:jbusres:2018:02:012
Eduardo Fernandesa,b,*, Maristela Holandaa, Marcio Victorinoa, Vinicius Borgesa, Rommel Carvalhoa, Gustavo Van Ervena
In this article, we present a predictive analysis of the academic performance of students in public schools of the
Federal District of Brazil during the school terms of 2015 and 2016. Initially, we performed a descriptive statistical
analysis to gain insight from data. Subsequently, two datasets were obtained. The first dataset contains
variables obtained prior to the start of the school year, and the second included academic variables collected two
months after the semester began. Classification models based on the Gradient Boosting Machine (GBM) were
created to predict academic outcomes of student performance at the end of the school year for each dataset.
Results showed that, though the attributes ‘grades and ‘absences were the most relevant for predicting the end
of the year academic outcomes of student performance, the analysis of demographic attributes reveals that
‘neighborhood’, ‘school’ and ‘age’ are also potential indicators of a students academic success or failure.
Keywords: Educational data mining | Academic performance | Predictive analysis | Decision tree | Gradient boosting machine | H2O