Extended Reality in Computer-Assisted Language Learning

Extended reality (XR), including Augmented, Virtual, and Mixed/Merged Realities, has widely grown in popularity over the past decade and is in line with the growing advances in smart and portable technologies. This tempted many Computer-Assisted Language Learning (CALL) researchers to benefit from the potential of extended reality for developing language educational applications and materials and exploring the effectiveness of these advanced technologies on language learning. Along this line, various literature reviews have analyzed and synthesized the applications of extended reality in language education separately. Nevertheless, CALL scholarships lack a comprehensive systematic review, including various types of XR. A systematic review would assist in reaching a better understanding of the status of XR in language education. Therefore, this paper reports a systematic review of extended reality research published (n = 28) in the leading Q1-ranked CALL journals in Scopus, including Language Learning & Technology, System, Computer Assisted Language Learning, ReCALL, CALICO, JALTCALL, CALL-EJ, and Teaching English with Technology in the period of 2010 to 2022. Drawing on the PRISMA model as the focal analysis procedure, this systematic review presents the contemporaneous state-of-the-art picture of extended reality aiming at (1) mapping the research trends and (2) determining the affordances of using extended reality as a CALL tool.