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Examining the influence of pre-service teachers’ digital native traits on their technology acceptance: A Serbian perspective

Many seem to believe that today’s pre-service teachers as born after 1980 are digital natives, or that they are “native speakers” of the digital language. Nevertheless, there is no evidence that their digital native characteristics determine whether or not they would use technology in the classroom....

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Autor principal: Milutinović, Verica
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8755974/
https://www.ncbi.nlm.nih.gov/pubmed/35039745
http://dx.doi.org/10.1007/s10639-022-10887-y
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author Milutinović, Verica
author_facet Milutinović, Verica
author_sort Milutinović, Verica
collection PubMed
description Many seem to believe that today’s pre-service teachers as born after 1980 are digital natives, or that they are “native speakers” of the digital language. Nevertheless, there is no evidence that their digital native characteristics determine whether or not they would use technology in the classroom. Although not widely evaluated, the four-factor, 21-item Digital Nativity Assessment Scale (DNAS) was one of the first instruments to assess digital nativeness (DN). This study aim is to explore the influence of pre-service teachers’ DN on their intention to use technology in the future classroom in Serbia, by evaluating the DNAS on Serbian sample and using it for measuring the DN. Six variables were incorporated to examine their mutual relationships based on technology acceptance model: digital nativeness, behavioral intention (BI), perceived usefulness (PU), perceived ease of use (PEU), subjective norm (SN), and technological complexity (TC). Data were collected from 688 pre-service teachers in Serbia. Exploratory factor analysis confirmed a four-factor model for the DNAS, and Serbian pre-service teachers demonstrated a high level of DN. To evaluate the hypothesized model structural equation modeling was utilized. The suggested model had a good fit for describing the BI of Serbian pre-service teachers, accounting for 27.1% of the variance in BI. It was found that direct dominant predictors of BI are digital native traits, perceived usefulness, and perceived ease of use. Significant influence of digital native traits on all other variables in the model was also confirmed. The implications for theory and practice are discussed.
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spelling pubmed-87559742022-01-13 Examining the influence of pre-service teachers’ digital native traits on their technology acceptance: A Serbian perspective Milutinović, Verica Educ Inf Technol (Dordr) Article Many seem to believe that today’s pre-service teachers as born after 1980 are digital natives, or that they are “native speakers” of the digital language. Nevertheless, there is no evidence that their digital native characteristics determine whether or not they would use technology in the classroom. Although not widely evaluated, the four-factor, 21-item Digital Nativity Assessment Scale (DNAS) was one of the first instruments to assess digital nativeness (DN). This study aim is to explore the influence of pre-service teachers’ DN on their intention to use technology in the future classroom in Serbia, by evaluating the DNAS on Serbian sample and using it for measuring the DN. Six variables were incorporated to examine their mutual relationships based on technology acceptance model: digital nativeness, behavioral intention (BI), perceived usefulness (PU), perceived ease of use (PEU), subjective norm (SN), and technological complexity (TC). Data were collected from 688 pre-service teachers in Serbia. Exploratory factor analysis confirmed a four-factor model for the DNAS, and Serbian pre-service teachers demonstrated a high level of DN. To evaluate the hypothesized model structural equation modeling was utilized. The suggested model had a good fit for describing the BI of Serbian pre-service teachers, accounting for 27.1% of the variance in BI. It was found that direct dominant predictors of BI are digital native traits, perceived usefulness, and perceived ease of use. Significant influence of digital native traits on all other variables in the model was also confirmed. The implications for theory and practice are discussed. Springer US 2022-01-12 2022 /pmc/articles/PMC8755974/ /pubmed/35039745 http://dx.doi.org/10.1007/s10639-022-10887-y Text en © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Milutinović, Verica
Examining the influence of pre-service teachers’ digital native traits on their technology acceptance: A Serbian perspective
title Examining the influence of pre-service teachers’ digital native traits on their technology acceptance: A Serbian perspective
title_full Examining the influence of pre-service teachers’ digital native traits on their technology acceptance: A Serbian perspective
title_fullStr Examining the influence of pre-service teachers’ digital native traits on their technology acceptance: A Serbian perspective
title_full_unstemmed Examining the influence of pre-service teachers’ digital native traits on their technology acceptance: A Serbian perspective
title_short Examining the influence of pre-service teachers’ digital native traits on their technology acceptance: A Serbian perspective
title_sort examining the influence of pre-service teachers’ digital native traits on their technology acceptance: a serbian perspective
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8755974/
https://www.ncbi.nlm.nih.gov/pubmed/35039745
http://dx.doi.org/10.1007/s10639-022-10887-y
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