Predicting factors affecting PISA 2015 mathematics literacy via radial basis function artificial neural network
Yükleniyor...
Tarih
2019-05-23
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Batman Üniversitesi
Erişim Hakkı
info:eu-repo/semantics/openAccess
Attribution-ShareAlike 3.0 United States
Attribution-ShareAlike 3.0 United States
Özet
In this study, radial basis function artificial neural network (RBFN), which
is one of the of data mining methods, was employed to determine the
factors affecting PISA 2015 (Programme for International Student
Assessment - PISA), Mathematics literacy. Mathematics literacy scores,
which were made in categorical form with three level dependent variables,
25 independent variables, and considered to have affected the dependent
variables, were employed in evaluating and validating the proposed
method. Also, in order to determine factors affecting PISA 2015
Mathematics literacy, information obtained from a total of 4422 students
(2165 (49%) of whom were males and 2257 (51%) of whom were females)
who participated the exam was used. According to the obtained results, the
correct classification rate of mathematics achievement in the radial based
artificial neural network model was found to be 85.2%. In addition, it is
seen that the most important factor that were affecting Mathematics literacy
was Turkish language success status and the other variables that were
setting significance are targeted point in school life, father education level
and mother education level.
Açıklama
Anahtar Kelimeler
PISA, Data Mining, Radial Basis, Artificial Neural Networks
Kaynak
WoS Q Değeri
Scopus Q Değeri
Cilt
3
Sayı
1
Künye
Bezek Güre, Ö , Kayri, M , Erdoğan, F . (2019). Predicting factors affecting PISA 2015 mathematics literacy via radial basis function artificial neural network. Journal of Engineering and Technology, 3 (1), 1-11.
