Review of research on mobile language learning in authentic environments

Rustam Shadiev, Wu Yuin Hwang, Yueh-Min Huang

Research output: Contribution to journalArticlepeer-review

156 Citations (Scopus)

Abstract

We reviewed literature from 2007 to 2016 (March) on mobile language learning in authentic environments. We aimed to understand publications’ trend, research focus, technology used, methodology, and current issues. Our results showed that there was increasing trend in the publications. Students’ perceptions towards mobile learning technologies and language proficiency were the most common research topics. The most frequently used technologies were smartphones, mobile phones, and personal digital assistants, whereas the most common target language was English as a foreign language. In addition, university and elementary school students were the most common participants. We found that learning activities in most studies were carried out in classroom and specified locations outside of campus. Authentic learning environments in most studies were familiar to students and learning activities were designed using instructor-centered approach. Most studies collected and analyzed qualitative and quantitative data. We also discovered some issues associated with earlier studies, e.g. many studies did not focus on applying newly learned knowledge by students to solve their real-life problems or recently developed intelligent technologies for language learning were overlooked. Based on our results, we discuss some implications and make suggestions over mobile language learning in authentic environments for the educators and researchers.

Original languageEnglish
Pages (from-to)284-303
Number of pages20
JournalComputer Assisted Language Learning
Volume30
Issue number3-4
DOIs
Publication statusPublished - 2017 May 19

All Science Journal Classification (ASJC) codes

  • Language and Linguistics
  • Linguistics and Language
  • Computer Science Applications

Fingerprint

Dive into the research topics of 'Review of research on mobile language learning in authentic environments'. Together they form a unique fingerprint.

Cite this