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This study explores the integration of Large Language Models (LLMs) into the learning design process of Education for Sustainable Development within Project-Based Learning (PBL) frameworks. Using the ABPxODS platform as the experimental setting, Mirai AI, a conversational agent providing educators with context-aware scaffolding, real-time feedback, and adaptive support for designing sustainability-aligned learning scenarios, was designed and evaluated. A controlled experiment involving 16 educators was conducted to assess the impact of artificial intelligence assistance on project design efficiency and quality. The results indicate that such assistance improves alignment with the United Nations Sustainable Development Goals and enhances design quality, particularly for educators with intermediate experience in PBL. However, novice educators encountered usability challenges, and automated evaluations performed by artificial intelligence demonstrated reliability limitations. This work reveals that AI effectiveness depends critically on educator experience levels while highlighting significant limitations in AI-based educational assessment reliability.

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Supporting Learning Design for Sustainable Development Using Large Language Models

  • 会议论文

  • 发表日期：

    2026年

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  • Patrick Ocheja,
  • Shatha N. Alkhasawneh,
  • Emily Theophilou,
  • Hiroaki Ogata,
  • Davinia Hernández-Leo

摘要

This study explores the integration of Large Language Models (LLMs) into the learning design process of Education for Sustainable Development within Project-Based Learning (PBL) frameworks. Using the ABPxODS platform as the experimental setting, Mirai AI, a conversational agent providing educators with context-aware scaffolding, real-time feedback, and adaptive support for designing sustainability-aligned learning scenarios, was designed and evaluated. A controlled experiment involving 16 educators was conducted to assess the impact of artificial intelligence assistance on project design efficiency and quality. The results indicate that such assistance improves alignment with the United Nations Sustainable Development Goals and enhances design quality, particularly for educators with intermediate experience in PBL. However, novice educators encountered usability challenges, and automated evaluations performed by artificial intelligence demonstrated reliability limitations. This work reveals that AI effectiveness depends critically on educator experience levels while highlighting significant limitations in AI-based educational assessment reliability.