Context, method, and theory in CALL research articles

Author:

Choubsaz Yazdan1ORCID,Jalilifar Alireza2ORCID,Boulton Alex3ORCID

Affiliation:

1. Shahid Chamran University of Ahvaz, Ahvaz, Iran / Sultan Qaboos University, Muscat, Oman

2. Shahid Chamran University of Ahvaz, Ahvaz, Iran

3. ATILF, CNRS & University of Lorraine, Nancy, France

Abstract

This paper is an initial report of the data analysis phase of a larger study that traces the evolution of Computer Assisted Language Learning (CALL). All published Research Articles (RAs) from four major CALL journals – ReCALL, CALL, Language Learning & Technology (LL&T) and CALICO Journal – from the very first issues to the end of 2019 were downloaded, sorted, and checked to form the final corpus of 426 highly cited RAs. The trends and themes (research contexts, research participants, and theoretical and methodological considerations of the RAs) were all recorded to see how CALL has evolved over time. Primary findings indicate that empirical studies where learners are physically or virtually involved in the process of technology-mediated language instruction dominate the field of CALL research. Authors resort to both quantitative and qualitative methodologies for data collection and analysis, though mixed-methods has gained more weight in the past two decades. Sociocultural theory stands over and above other theories in Second Language Acquisition (SLA) to frame CALL studies. The paper discusses these issues, and problems detected.

Publisher

Research-publishing.net

Reference4 articles.

1. Laying the groundwork for a historical overview of high-impact CALL papers

2. CALL research: Where are we now?

3. A scientometric review of research trends in computer-assisted language learning (1977 – 2020)

4. Yim, S., & Warschauer, M. (2017). Web-based collaborative writing in L2 contexts: methodological insights from text mining. Language Learning & Technology, 21(1), 146-165. https://doi.org/10125/44599

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Building the future by looking to the past: the evolution of research strands in influential CALL papers;Intelligent CALL, granular systems and learner data: short papers from EUROCALL 2022;2022-12-12

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