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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2509.04239 |
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| _version_ | 1866909770599890944 |
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| author | Valdivia, Arturo Burelli, Paolo |
| author_facet | Valdivia, Arturo Burelli, Paolo |
| contents | This paper proposes a structured methodology to evaluate AI-generated game narratives, leveraging the Delphi study structure with a panel of narrative design experts. Our approach synthesizes story quality dimensions from literature and expert insights, mapping them into the Kano model framework to understand their impact on player satisfaction. The results can inform game developers on prioritizing quality aspects when co-creating game narratives with generative AI. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_04239 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Evaluating Quality of Gaming Narratives Co-created with AI Valdivia, Arturo Burelli, Paolo Artificial Intelligence This paper proposes a structured methodology to evaluate AI-generated game narratives, leveraging the Delphi study structure with a panel of narrative design experts. Our approach synthesizes story quality dimensions from literature and expert insights, mapping them into the Kano model framework to understand their impact on player satisfaction. The results can inform game developers on prioritizing quality aspects when co-creating game narratives with generative AI. |
| title | Evaluating Quality of Gaming Narratives Co-created with AI |
| topic | Artificial Intelligence |
| url | https://arxiv.org/abs/2509.04239 |