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Optimizing Foreign Language Learning in Virtual Reality: A Comprehensive Theoretical Framework Based on Constructivism and Cognitive Load Theory (VR-CCL)
Song, C.; Shin, S.-Y.; Shin, K.-S. Optimizing Foreign Language Learning in Virtual Reality: A Comprehensive Theoretical Framework Based on Constructivism and Cognitive Load Theory (VR-CCL). Appl. Sci.2023, 13, 12557.
Song, C.; Shin, S.-Y.; Shin, K.-S. Optimizing Foreign Language Learning in Virtual Reality: A Comprehensive Theoretical Framework Based on Constructivism and Cognitive Load Theory (VR-CCL). Appl. Sci. 2023, 13, 12557.
Song, C.; Shin, S.-Y.; Shin, K.-S. Optimizing Foreign Language Learning in Virtual Reality: A Comprehensive Theoretical Framework Based on Constructivism and Cognitive Load Theory (VR-CCL). Appl. Sci.2023, 13, 12557.
Song, C.; Shin, S.-Y.; Shin, K.-S. Optimizing Foreign Language Learning in Virtual Reality: A Comprehensive Theoretical Framework Based on Constructivism and Cognitive Load Theory (VR-CCL). Appl. Sci. 2023, 13, 12557.
Abstract
With the widespread Application of Virtual Reality (VR) in education, optimizing foreign language learning in VR has become a focal point of research. This paper introduces a comprehensive theoretical framework (VR-CCL) based on constructivism and cognitive load theory to enhance foreign language learning in VR. Through a literature review, we explore the applications of VR in education, foreign language learning theories, and prior works on technology-assisted language learning. We further detail the three main components of the VR-CCL framework and validate its effectiveness through two case studies: Duolingo VR and Rosetta Stone VR. Finally, we discuss the strengths and limitations of the framework and its implications for educators and developers.
Computer Science and Mathematics, Computer Science
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
