Predicting factors affecting PISA 2015 mathematics literacy via radial basis function artificial neural network

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dc.authorid0000-0002-5272-4639en_US
dc.authorid0000-0002-5933-6444en_US
dc.authorid0000-0003-3745-0198en_US
dc.contributor.authorGüre Bezek, Özlem
dc.contributor.authorKayri, Murat
dc.contributor.authorErdoğan, Fevzi
dc.date.accessioned2019-08-15T09:16:05Z
dc.date.available2019-08-15T09:16:05Z
dc.date.issued2019-05-23en_US
dc.departmentBatman Üniversitesi Sağlık Hizmetleri Meslek Yüksekokulu Tıbbi Hizmetler ve Teknikler Bölümüen_US
dc.departmentBatman Üniversitesi Mühendislik - Mimarlık Fakültesi Bilgisayar Mühendisliği Bölümüen_US
dc.description.abstractIn 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.en_US
dc.identifier.citationBezek 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.en_US
dc.identifier.endpage11en_US
dc.identifier.issn2619-9483
dc.identifier.issue1en_US
dc.identifier.startpage1en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12402/2261
dc.identifier.volume3en_US
dc.language.isoenen_US
dc.publisherBatman Üniversitesien_US
dc.relation.journalJournal of Engineering and Technologyen_US
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.rightsAttribution-ShareAlike 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-sa/3.0/us/*
dc.subjectPISAen_US
dc.subjectData Miningen_US
dc.subjectRadial Basisen_US
dc.subjectArtificial Neural Networksen_US
dc.titlePredicting factors affecting PISA 2015 mathematics literacy via radial basis function artificial neural networken_US
dc.typeArticleen_US

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Cilt 3, Sayı 1
Mühendislik-Mimarlık Fakültesi Bilgisayar Mühendisliği Bölümü Makale Koleksiyonu
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