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dc.contributor.authorİslamoğlu, Hakan
dc.contributor.authorKabakçı Yurdakul, Işıl
dc.contributor.authorUrsavaş, Ömer Faruk
dc.date.accessioned2022-10-04T06:53:50Z
dc.date.available2022-10-04T06:53:50Z
dc.date.issued2021en_US
dc.identifier.citationIslamoglu, H., Yurdakul, I.K.. & Ursavas, O.M. (2021). Pre-service teachers' acceptance of mobile-technology-supported learning activities. Educational Technology Research and Development , 69(2), 1025-1054. https://doi.org/10.1007/s11423-021-09973-8en_US
dc.identifier.issn1042-1629
dc.identifier.issn1556-6501
dc.identifier.urihttps://doi.org/10.1007/s11423-021-09973-8
dc.identifier.urihttps://hdl.handle.net/11436/6637
dc.description.abstractThe purpose of this study was to develop a mobile learning acceptance model for pre-service teachers and to examine the relationships among technology acceptance factors. The literature on mobile learning acceptance lacks studies on pre-service teachers and studies that include concrete mobile learning scenarios. To overcome these problems, we have developed and implemented a mobile-technology-enabled information technology course. The data collection and analysis were conducted in two separate studies. First, we developed a mobile learning acceptance scale and applied confirmatory factor analysis with 408 participants. The final instrument included 28 items measuring eight technology acceptance factors, namely behavioral intention, attitude towards use, perceived usefulness, perceived ease of use, social influence, facilitating conditions, self-efficacy, and anxiety. After this, we collected a new set of data from 316 participants to examine the relationships among the factors using structural equation modeling. In both studies, we investigated the respective models' invariance across gender and discipline groups, and both models fulfilled invariance requirements. The results indicated that perceived ease of use and social influence have direct effects on behavioral intention, whereas self-efficacy has an indirect effect. Depending on the group, the explained variance of behavioral intention ranged between 18.1% and 60.6%.en_US
dc.language.isoengen_US
dc.publisherSpringeren_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectMobile learningen_US
dc.subjectTechnology acceptance modelen_US
dc.subjectUnified theory of use and acceptance of technologyen_US
dc.subjectPre-service teachersen_US
dc.subjectGender differencesen_US
dc.subjectDiscipline differencesen_US
dc.titlePre-service teachers' acceptance of mobile-technology-supported learning activitiesen_US
dc.typearticleen_US
dc.contributor.departmentRTEÜ, Eğitim Fakültesi, Bilgisayar ve Öğretim Teknolojileri Eğitimi Bölümüen_US
dc.contributor.institutionauthorİslamoğlu, Hakan
dc.contributor.institutionauthorUrsavaş, Ömer Faruk
dc.identifier.doi10.1007/s11423-021-09973-8en_US
dc.identifier.volume69en_US
dc.identifier.issue2en_US
dc.identifier.startpage1025en_US
dc.identifier.endpage1054en_US
dc.relation.journalEducational Technology Research and Developmenten_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US


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