Bibliographic Details
| Title: |
The content analysis and bibliometric mapping of CALL journal. |
| Authors: |
Goksu, Idris1, Ozkaya, Ebru2, Gunduz, Ali3 |
| Source: |
Computer Assisted Language Learning. Dec2022, Vol. 35 Issue 8, p2018-2048. 31p. |
| Subject Terms: |
*Bibliometrics, *Computer assisted language instruction, *Higher education, *Adults, *English as a foreign language |
| Abstract: |
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. [ABSTRACT FROM AUTHOR] |
|
Copyright of Computer Assisted Language Learning is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| Database: |
Education Research Complete |
