MRGEN: A Conceptual Framework for LLM-Powered Mixed Reality Authoring Tools for Education
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arXiv
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| Auteurs principaux: | , , , |
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| Format: | Preprint |
| Publié: |
2026
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| _version_ | 1866917414340395008 |
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| author | Seddini, Mohammed Oussama Ez-Zaouia, Mohamed Le, Ngoc Luyen Marfisi, Iza |
| author_facet | Seddini, Mohammed Oussama Ez-Zaouia, Mohamed Le, Ngoc Luyen Marfisi, Iza |
| contents | Mixed Reality (MR) offers immersive and multimodal opportunities for education but remains difficult for teachers to author without technical expertise. We propose MRGEN, a conceptual framework for LLM-powered authoring tools to support teachers in creating MR learning activities that work on mobile devices (tablets and smartphones). MRGEN articulates three axes: Learning Objectives, MR Modality, and GAI Assistance. To validate our framework, we implemented a prototype based on the open-source MIXAP authoring platform and conducted a user study with 24 participants. Results show that LLM-powered authoring reduced task duration by 36% on average, and that over 90% of participants found the AI support helpful for brainstorming, structuring, and aligning content with their learning goals. These findings yielded very promising results for future AI-assisted MR authoring tools. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_15341 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | MRGEN: A Conceptual Framework for LLM-Powered Mixed Reality Authoring Tools for Education Seddini, Mohammed Oussama Ez-Zaouia, Mohamed Le, Ngoc Luyen Marfisi, Iza Human-Computer Interaction Artificial Intelligence Mixed Reality (MR) offers immersive and multimodal opportunities for education but remains difficult for teachers to author without technical expertise. We propose MRGEN, a conceptual framework for LLM-powered authoring tools to support teachers in creating MR learning activities that work on mobile devices (tablets and smartphones). MRGEN articulates three axes: Learning Objectives, MR Modality, and GAI Assistance. To validate our framework, we implemented a prototype based on the open-source MIXAP authoring platform and conducted a user study with 24 participants. Results show that LLM-powered authoring reduced task duration by 36% on average, and that over 90% of participants found the AI support helpful for brainstorming, structuring, and aligning content with their learning goals. These findings yielded very promising results for future AI-assisted MR authoring tools. |
| title | MRGEN: A Conceptual Framework for LLM-Powered Mixed Reality Authoring Tools for Education |
| topic | Human-Computer Interaction Artificial Intelligence |
| url | https://arxiv.org/abs/2604.15341 |