The content analysis and bibliometric mapping of <i>CALL</i> journal

The primary aim of this study was to investigate the methodological trends of the articles published in the Computer Assisted Language Learning (CALL) journal between 2014 and 2019 via content analysis. The secondary aim was to analyze the CALL journal with the bibliometric mapping method to reveal the keyword trend and identify the countries, universities, and authors that made the highest contribution to the journal between 2008 and 2019. Full texts of 310 articles were analyzed by content analysis and a meta-data set of 469 articles from the Clarivate Analytics Web of Science (WoS) database was evaluated by bibliometric mapping. According to the results, most of the studies published in the CALL journal employed a quantitative research design and were conducted at higher education level. Additionally, most of the studies focused on language skills when compared to other educational factors such as motivation and perception. 'English as a foreign language', 'communication', 'motivation', 'telecollaboration', 'mobile learning', 'writing', and 'blended learning' were revealed as the most common keywords used in the studies. Countries that had the largest contribution to the CALL journal included Taiwan, USA, and China, respectively. Moreover, Taiwan-based universities contributed the highest number of publications and the authors including Wu-Yuin Hwang, Siew Ming Thang, Greg Kessler, Rustam Shadiev, Chun Lai, Mark Peterson, Jai Li, Liwei Hsu, and Wen-Chi Vivian Wu had the highest numbers of publications.

Dergi

COMPUTER ASSISTED LANGUAGE LEARNING

Yıl

2022

Cilt

35

Sayı

8

Sayfa

2018-2048

ISSN

0958-8221

eISSN

1744-3210

DOI

10.1080/09588221.2020.1857409

WoS UID

WOS:000598937300001