Extended reality in language learning: A cognitive affective model of immersive learning perspective

Abstract

A surge in the interest and implementation of extended reality (XR)-based lessons in language learning has resulted in many related studies. Recent reviews that summarized these studies and the previous studies focus on the technologies used in language-learning settings or the different ways of incorporating XR tools in language-learning activities. However, less work has been done to synthesize XR-based language-learning studies from a language-learning theory perspective. Thus, this study delineates the contour of scholarly literature on XR in language learning using the Cognitive Affective Model of Immersive Learning (CAMIL). The model contains six affective and cognitive factors that lead to XR-based learning: interest, motivation, self-efficacy, embodiment, cognitive load, and self-regulation. This model was adopted in the current study to systematically synthesize the findings from primary studies published between 2017 and 2022 to construct XR explanations on language learning from a cognitive theory perspective. Studies published in 12 indexed privileged journals in the language education and technology field on XR in language learning were reviewed. The results showed that the factors in the CAMIL led to factual, conceptual, and procedural knowledge acquisition and transfer. This study provides some insights into understanding the cognitive outcomes of XR-based language learning by analyzing the findings from previous studies. Suggestions for future studies are proposed in this study.