Building the future by looking to the past: the evolution of research strands in influential CALL papers

Yazdan Choubsaz, Alireza Jalilifar, Alex Boulton

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

To trace the evolution of research strands in published Computer Assisted
Language Learning (CALL) papers over time, a corpus of 426 highly-cited papers
in four major CALL journals (ReCALL, CALL, LL&T, and CALICO Journal) was
compiled and coded using NVivo 12. All identified aspects of technology-mediated
language learning and teaching were collected to produce a comprehensive list of
690 recurring research strands and then, by adopting a constant comparison method,
were merged to form 119 unique research strands. The top 10 alone represent almost
half of all research strands: Computer-Mediated Communication (CMC), writing,
vocabulary, feedback, evaluation, learning environment, telecollaboration, design,
speaking, and grammar. This paper provides the rationale for the study along with
the methodology for data collection and analysis, with a particular focus on the
dominant and intermediary strands to inform future CALL publications.
Original languageEnglish
Title of host publicationIntelligent CALL, granular systems and learner data: short papers from EUROCALL 2022
Place of PublicationFrance
PublisherResearch-publishing.net
Pages65-70
Number of pages6
ISBN (Print)978-2-38372-015-7
DOIs
Publication statusPublished - Dec 12 2022

Keywords

  • CALL research, CALL evolution, research strands, corpus analysis

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