AI辅助情绪反思原型，引导用户从识别情绪到制定行动方案。
Narrative-Centered Emotional Reflection: An Early Prototype for AI-Supported Emotional Self-Reflection
- 分层提示+隐喻叙事，推动情绪从表面识别走向深层反思。
- 基于表达性写作与自我决定理论，构建渐进式反思路径。
- 适合对心理自省或情感计算感兴趣的开发者与研究者。
Reflexion 是一个由 AI 驱动的原型系统，旨在探索结构化的情绪自我反思。通过整合情绪检测、分层反思提示和隐喻性故事生成，该系统致力于支持用户在超越基础情感分类的基础上进行自主情绪探索。其设计以表达性写作、认知重构和自我决定理论为基础，将反思过程组织为从表层情绪识别逐步过渡到价值一致的行动规划的路径。最终的行动规划层还引入了关于自主性与赋能的深层问题，但这些仍属于未来方向，当前原型中未完全实现。非正式的设计反馈表明，部分评审者认为该分层交互模型易于理解且可能有用；本文不作任何实证有效性声明。作为早期原型，Reflexion 记录了理论驱动的情感计算的一个发展方向。
原文摘要 · Abstract (English)
Reflexion is an AI-powered prototype designed to explore structured emotional self-reflection. By integrating emotion detection, layered reflective prompting, and metaphorical storytelling generation, Reflexion was intended to support users in autonomous emotional exploration beyond basic sentiment categorization. Grounded primarily in expressive writing, cognitive restructuring, and self-determination theory, the system was designed to organize reflection as a progressive pathway from surface-level emotional recognition toward value-aligned action planning. Its final action-planning layer is additionally informed by broader questions of agency and empowerment, which remain future directions rather than fully implemented mechanisms in the current prototype. Informal design feedback indicated that some reviewers found the layered interaction model understandable and potentially useful; no empirical efficacy claims are made. As an early prototype, Reflexion documents one direction in theory-informed affective computing.
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