A Study on the Exploring Strategies for the Construction of a Language Laboratory Based on AI & VR: Focusing on Improving L2 Learners' Speaking Proficiency

This study proposes a framework for a language laboratory that integrates Artificial Intelligence (AI) and Virtual Reality (VR) to improve learners' speaking abilities. Literature analysis identified key challenges in speaking proficiency, including insufficient skills, lack of real-life context, and language anxiety. Based on these findings, this study developed an AI- and VR-integrated speaking output training system framework. A qualitative method was used, with expert interviews to validate the framework’s theoretical rationale and technical feasibility. Expert feedback indicated that the framework is innovative and valuable, particularly in emotional regulation, personalized learning paths, and immersive interactions. However, further studies are suggested to focus on empirical research, technological costs, emotion recognition accuracy, and privacy protection.

Authors

Publication Details

Journal
Journal of Fisheries and Marine Sciences Education
Published
2025-04-27
DOI
https://doi.org/10.13000/jfmse.2025.4.37.2.309
Primary Topic
Diverse Approaches in Healthcare and Education Studies
Type
article
Field-Weighted Citation Impact
0.00
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article

A Study on the Exploring Strategies for the Construction of a Language Laboratory Based on AI & VR: Focusing on Improving L2 Learners' Speaking Proficiency

Yuan Feng, Gyun Heo
Journal of Fisheries and Marine Sciences Education
Diverse Approaches in Healthcare and Education Studies
article

A Study on the Exploring Strategies for the Construction of a Language Laboratory Based on AI & VR: Focusing on Improving L2 Learners' Speaking Proficiency

Yuan Feng, Gyun Heo
article en

Abstract

This study proposes a framework for a language laboratory that integrates Artificial Intelligence (AI) and Virtual Reality (VR) to improve learners' speaking abilities. Literature analysis identified key challenges in speaking proficiency, including insufficient skills, lack of real-life context, and language anxiety. Based on these findings, this study developed an AI- and VR-integrated speaking output training system framework. A qualitative method was used, with expert interviews to validate the framework’s theoretical rationale and technical feasibility. Expert feedback indicated that the framework is innovative and valuable, particularly in emotional regulation, personalized learning paths, and immersive interactions. However, further studies are suggested to focus on empirical research, technological costs, emotion recognition accuracy, and privacy protection.

Journal of Fisheries and Marine Sciences EducationVol. 37(2)
Quality Education
Openalex Percentile: Top 88%
Diverse Approaches in Healthcare and Education Studies
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