2018
DOI: 10.18326/rgt.v11i2.121-138
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Digital Native(ness), Mobile Technologies and Language Proficiency in Underdeveloped Countries

Abstract: Various studies have elaborated on the concept of ‘digital native(ness)’, i.e. (an identity of) the generation of students who were born during the digital technology era, i.e. from the 1980s onwards (Prensky 2001). Those studies claim that digital natives have been exposed to modern technologies, and thus are familiar with using them in their everyday activities (Dang 2013; Jacobson & Turner 2010). Those studies do not go beyond the access to and the general use of technologies. They ignore the fact that … Show more

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Cited by 3 publications
(2 citation statements)
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“…Grigoryan [22] argues that the advancement of digital software tools nowadays is able to help students practice much more to write. The access and use of mobile technologies for doing interaction, communication, and getting and share information are spread out [23]. It is possible for a lecturer to lead pre-service teachers in doing writing activities.…”
Section: Introductionmentioning
confidence: 99%
“…Grigoryan [22] argues that the advancement of digital software tools nowadays is able to help students practice much more to write. The access and use of mobile technologies for doing interaction, communication, and getting and share information are spread out [23]. It is possible for a lecturer to lead pre-service teachers in doing writing activities.…”
Section: Introductionmentioning
confidence: 99%
“…Thus, training teachers and students in the practical application of ICT is crucial to ensuring that both sides become engaged in the teaching and learning process, allowing students to be more autonomous and motivated to learn a language. This also occurred in an English-language school in Rwanda, where technology used to promote language competency had little direct effect until teachers provided advice and assistance to the students (Uwizeyimana, 2018).…”
Section: Integrated Language Learning In the Digital Context Modelmentioning
confidence: 99%