Comparison of MATLAB and SPSS software in the prediction of academic achievement with artificial neural networks: modeling for elementary school students

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dc.authorid0000-0001-5064-6983en_US
dc.authorid0000-0002-4152-4324en_US
dc.contributor.authorÇevik, Mustafa
dc.contributor.authorÖrnek Tabaru, Gizem
dc.date.accessioned2021-09-22T11:44:51Z
dc.date.available2021-09-22T11:44:51Z
dc.date.issued2020en_US
dc.departmentKMÜ, Eğitim Fakültesi, Matematik ve Fen Bilimleri Eğitimi Bölümüen_US
dc.description.abstractIn this study, it was aimed to compare the predictions of the academic achievement of the artificial neural networks (ANN) run in MATLAB and SPSS software and to determine the factors related to their academic achievement. Sample consisted of 465 students who were studying at Grade 4 in primary schools in the Central Anatolian Region of Turkey in 2017. A 12-questions questionnaire was used as the collection tool. For the content validity of the questionnaire, expert opinions were received. The KR20 reliability coefficient was calculated as .60. An exploratory factor analysis was run for the construct validity. In the ANN model, the items related to the academic achievement in the questionnaire were considered as independent variables / inputs, and the academic achievements of the previous year as the dependent variables / outputs. The predictions of the academic achievement of the ANN models were analyzed in MATLAB R2013a and SPSS 24.0 software and the regression coefficients of the independent variables were examined. It was found that MATLAB software had a higher rate of the correct prediction compared to SPSS. In the regression coefficients of the independent variables, some differences and similarities between the results of MATLAB and SPSS were found.en_US
dc.identifier.citationÇevik, M., & Tabaru-Örnek, G. (2020). Comparison of MATLAB and SPSS software in the prediction of academic achievement with artificial neural networks: Modeling for elementary school students. International Online Journal of Education and Teaching (IOJET), 7(4). 1689-1707.en_US
dc.identifier.endpage1707en_US
dc.identifier.issn2148-225X
dc.identifier.issue4en_US
dc.identifier.startpage1689en_US
dc.identifier.trdizinidtrdiziniyok
dc.identifier.urihttps://hdl.handle.net/11492/5311
dc.identifier.volume7en_US
dc.indekslendigikaynakTR-Dizin
dc.institutionauthorÇevik, Mustafa
dc.institutionauthorÖrnek Tabaru, Gizem
dc.language.isoen
dc.relation.journalIOJETen_US
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectArtificial Neural Networken_US
dc.subjectAcademic Achievement Predictionen_US
dc.subjectMATLABen_US
dc.subjectSPSSen_US
dc.titleComparison of MATLAB and SPSS software in the prediction of academic achievement with artificial neural networks: modeling for elementary school studentsen_US
dc.typeArticle

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