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Enhancing Sustainable AI-Driven Language Learning: Location-Based Vocabulary Training for Learners of Japanese

Author

Listed:
  • Liuyi Yang

    (Graduate School of System Informatics, Kobe University, 1-1 Rokkodai-cho, Nada-ku, Kobe 657-8501, Japan)

  • Sinan Chen

    (Graduate School of System Informatics, Kobe University, 1-1 Rokkodai-cho, Nada-ku, Kobe 657-8501, Japan)

  • Jialong Li

    (Department of Computer Science and Engineering, Waseda University, 1-104 Totsukamachi, Shinjuku-ku, Tokyo 169-8050, Japan)

Abstract

With the rapid advancement of mobile technology, e-learning has expanded significantly, making language learning more accessible than ever. At the same time, the rise of artificial intelligence (AI) technologies has opened new avenues for adaptive and personalized e-learning experiences. However, traditional e-learning methods remain limited by their reliance on static, predefined materials, which restricts equitable access to learning resources and fails to fully support lifelong learning. To address this limitation, this study proposes a location-based AI-driven e-learning system that dynamically generates language learning materials tailored to real-world contexts by integrating location-awareness technology with AI. This approach enables learners to acquire language skills that are directly applicable to their physical surroundings, thereby enhancing engagement, comprehension, and retention. Both objective evaluation and user surveys confirm the reliability and effectiveness of AI-generated language learning materials. Specifically, user surveys indicate that the generated content achieves a content relevance score of 8.4/10, an accuracy score of 8.8/10, a motivation score of 7.9/10, and a learning efficiency score of 7.8/10. Our method can reduce reliance on predefined content, allowing learners to access location-relevant learning resources anytime and anywhere, thereby improving accessibility and fostering lifelong learning in the context of sustainable education.

Suggested Citation

  • Liuyi Yang & Sinan Chen & Jialong Li, 2025. "Enhancing Sustainable AI-Driven Language Learning: Location-Based Vocabulary Training for Learners of Japanese," Sustainability, MDPI, vol. 17(6), pages 1-24, March.
  • Handle: RePEc:gam:jsusta:v:17:y:2025:i:6:p:2592-:d:1612991
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    References listed on IDEAS

    as
    1. Hilal Uğraş & Mustafa Uğraş & Stamatios Papadakis & Michail Kalogiannakis, 2024. "ChatGPT-Supported Education in Primary Schools: The Potential of ChatGPT for Sustainable Practices," Sustainability, MDPI, vol. 16(22), pages 1-20, November.
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