TY - GEN
T1 - Using Decision Trees for Predicting Academic Performance Based on Socio-Economic Factors
AU - Segura-Morales, Marco
AU - Loza-Aguirre, Edison
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2018/12/4
Y1 - 2018/12/4
N2 - The main objective of this research study is to determine how socio-economic factors affect the educational attainments of high-school students. For our study, we considered the socio-economic and academic data corresponding to more than ten years of records obtained from the leading university of an Andean country. Then, we used classification algorithms and machine learning techniques to determine which factors are the more influential on academic performance. We found that academic scholarship, age, county and high school degree influences academic performance of students. The results of this study constitute important information for academic directors and social workers involved in the task of improving the conditions of students and providing all of them the means to success.
AB - The main objective of this research study is to determine how socio-economic factors affect the educational attainments of high-school students. For our study, we considered the socio-economic and academic data corresponding to more than ten years of records obtained from the leading university of an Andean country. Then, we used classification algorithms and machine learning techniques to determine which factors are the more influential on academic performance. We found that academic scholarship, age, county and high school degree influences academic performance of students. The results of this study constitute important information for academic directors and social workers involved in the task of improving the conditions of students and providing all of them the means to success.
KW - academic performance
KW - data mining
KW - decision tree
KW - high-school students
KW - higher education
KW - socio-economic factors
UR - http://www.scopus.com/inward/record.url?scp=85060598828&partnerID=8YFLogxK
U2 - 10.1109/CSCI.2017.197
DO - 10.1109/CSCI.2017.197
M3 - Contribución a la conferencia
AN - SCOPUS:85060598828
T3 - Proceedings - 2017 International Conference on Computational Science and Computational Intelligence, CSCI 2017
SP - 1132
EP - 1136
BT - Proceedings - 2017 International Conference on Computational Science and Computational Intelligence, CSCI 2017
A2 - Tinetti, Fernando G.
A2 - Tran, Quoc-Nam
A2 - Deligiannidis, Leonidas
A2 - Yang, Mary Qu
A2 - Yang, Mary Qu
A2 - Arabnia, Hamid R.
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2017 International Conference on Computational Science and Computational Intelligence, CSCI 2017
Y2 - 14 December 2017 through 16 December 2017
ER -