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Preliminary Results from Norway, Slovenia, Portugal, Turkey, Ukraine, and Jordan: Investigating Pre-Service Teachers’ Expected Use of Digital Technology When Becoming Teachers
Ist Teil von
Education sciences, 2023-08, Vol.13 (8), p.783
Ort / Verlag
Basel: MDPI AG
Erscheinungsjahr
2023
Quelle
Free E-Journal (出版社公開部分のみ)
Beschreibungen/Notizen
Digital technology has become an important part of society and deserves attention and in-depth research, which is still lacking. The study presented in this paper includes international perspectives from six countries and examines which factors influence the use of digital technologies in future pedagogical work in primary schools. Specifically, we investigated how pre-service teachers assess their attitudes, knowledge, and skills towards digital technology, and we determined these factors’ role in the pre-service teachers’ future use of digital technologies in pedagogical work. For the purpose of the research, an online questionnaire was used, which contained open-ended questions, optional questions, and five-point Likert-type scales, and Spearman correlation and Stepwise linear regression statistical methods were used in the data analysis. The sample consisted of 573 full-time and part-time undergraduate pre-service teachers from the Faculties of Education’s higher professional programmes in Norway, Slovenia, Portugal, Turkey, Ukraine, and Jordan. Data were collected between June 2021 and May 2022 and processed using IBM SPSS. The present research showed the significant importance of knowledge and skills about digital technologies and professional attitude towards digital tool factors for pre-service teachers’ future professional use of digital technologies. The demonstrated intention of the future use of digital technologies showed the readiness of pre-service teachers regarding the inclusion of digital technologies in pedagogical work. Opportunities for further research are in the implementation of focus groups after surveying pre-service teachers, as well as regular measurements and the inclusion of other important constructs in the regression model.