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Early strategic guidance for higher vocational school students using support vector machines

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dc.contributor.author Tokat, Sezai
dc.contributor.author Karagül, Kenan
dc.contributor.author Aydemir, Erdal
dc.date.accessioned 2019-10-01T08:32:24Z
dc.date.available 2019-10-01T08:32:24Z
dc.date.issued 2014-07-15
dc.identifier.citation Tokat, S., Karagül, K., Aydemir, E. (2014). EARLY STRATEGIC GUIDANCE FOR HIGHER VOCATIONAL SCHOOL STUDENTS USING SUPPORT VECTOR MACHINES. International Journal on New Trends in Education and Their Implications. 5(3), pp. 166-175. tr_TR
dc.identifier.issn 1309-6249
dc.identifier.uri http://acikerisim.pau.edu.tr:8080/xmlui/handle/11499/26464
dc.description.abstract Academic guidance and orientation is important for vocational schools. In this study, data set of vocational school students are obtained from student affairs central database. The data is filtered and gender, age, geographical region student came from, high-school type, a special high school score of vocational high school student that is used for entering vocational school without exam, and school registration type are taken as six inputs. Academic success and graduation length are the two outputs that are aimed to be predicted. Based on these chosen input and output information, a model is aimed to be developed in order to help advisors in improving academic success and shortening graduation length of their students. Support vector machinesbased artificial intelligence technique is used. Input sensitivity analyses are also conducted. It is seen from the analyses that academic success and graduation length are both highly affected by gender. Also, academic background has also effect on two outputs in different manners. From the analyses, it can be concluded that the advisors can orient or guide students based on the SVM outputs. tr_TR
dc.language.iso en tr_TR
dc.rights info:eu-repo/semantics/openAccess tr_TR
dc.subject Vocational schools, academic guidance, academic success, graduation length, support vector machines, input sensitivity. tr_TR
dc.title Early strategic guidance for higher vocational school students using support vector machines tr_TR
dc.type article tr_TR
dc.identifier.volume 5 tr_TR
dc.identifier.issue 3 tr_TR
dc.identifier.startpage 166 tr_TR
dc.identifier.endpage 175 tr_TR
dc.source.title International Journal on New Trends in Education and Their Implications (IJONTE) tr_TR
dc.relation.publicationCategory Uluslararası Hakemli Dergi tr_TR


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