From the Perspective of Loneliness and Cognitive Absorption Internet Addiction as Predictor and Predicted

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dc.contributor.authorCelik, Vehbi
dc.contributor.authorYesilyurt, Etem
dc.contributor.authorKorkmaz, Ozgen
dc.contributor.authorUsta, Ertugrul
dc.date.accessioned2024-02-23T14:45:55Z
dc.date.available2024-02-23T14:45:55Z
dc.date.issued2014
dc.departmentNEÜen_US
dc.description.abstractIn this research internet addiction has been dealt with as predictor and predicted variable, this situation has been analyzed from the perspectives of loneliness and cognitive absorption and a tangible model has been put forth. Participant group has been constituted by 338 teacher candidates. Research data were collected using loneliness scale (alpha=.96), cognitive absorption scale (alpha=.90) and internet addiction scale (alpha=.95). On the data that was obtained; structural equation model were used. As a result: Loneliness levels of candidate teachers have significant and positive direction effect on internet addiction. On the other hand internet addiction of teacher candidates affects their loneliness levels in positive direction and significantly.en_US
dc.identifier.endpage594en_US
dc.identifier.issn1305-8215
dc.identifier.issn1305-8223
dc.identifier.issue6en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.startpage581en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12452/17693
dc.identifier.volume10en_US
dc.identifier.wosWOS:000352005600008en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.language.isoenen_US
dc.publisherModestum Ltden_US
dc.relation.ispartofEurasia Journal Of Mathematics Science And Technology Educationen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectLonelinessen_US
dc.subjectCognitive Absorptionen_US
dc.subjectInternet Addictionen_US
dc.subjectTeacher Trainingen_US
dc.titleFrom the Perspective of Loneliness and Cognitive Absorption Internet Addiction as Predictor and Predicteden_US
dc.typeArticleen_US

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