用专家共识法评估AI生成游戏剧情质量，帮开发者优先优化关键环节。
Evaluating Quality of Gaming Narratives Co-created with AI
- 整合文献与专家意见构建评价维度
- 基于卡诺模型分析各维度对玩家满意度的影响
- 为AI共创叙事提供可操作的优化方向
本文提出一种结构化方法评估由AI生成的游戏叙事质量，采用德尔菲研究法召集叙事设计专家小组。通过融合文献中的故事质量维度与专家洞察，将这些维度映射至卡诺模型框架，以理解其对玩家满意度的影响。研究结果可帮助游戏开发者在与生成式AI协作创作叙事时，明确优先优化的质量方面。
原文摘要 · Abstract (English)
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.
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