用写作认知过程理论指导智能写作助手主动提建议。
Towards Cognitive Process-Aware Proactive Writing Support
- 基于写作认知理论识别用户写作状态，推断所需支持类型。
- 实验证明该方法提升表达力与想法探索，增强对建议的接受度。
- 适合需要主动辅助的创意写作场景，尤其适合意图模糊时。
大型语言模型可辅助写作，但现有工具需用户明确提出提示，这在创意写作中尤为负担，因意图常不清晰。主动支持通过分析写作交互推断需求可减轻负担，但面临两大挑战：提供何种支持、何时干预。本文聚焦前者，假设花尔和海耶斯的写作认知过程理论（将写作分为六种认知过程）能建立可观测行为与合适支持之间的可解释桥梁。通过前期研究与文献综述，我们识别出14类与这些过程相关的写作支持类型，并关联其特征交互行为。随后构建了AToM CoWriter系统，基于写作交互与文档上下文推断支持需求。两组被试实验（N=21）初步证明该方法提升了表达丰富性与想法探索广度，且认知过程推断增强了用户对主动建议的参与度。结果表明，认知过程可作为主动写作系统中支持选择的有力基础。
原文摘要 · Abstract (English)
Large language models can support writing, but existing tools require users to explicitly articulate prompts-particularly burdensome in creative writing, where intentions are often ambiguous. Proactive support that infers users' needs from writing interactions could alleviate this burden, but raises two challenges: determining what support to provide and when to intervene. This work focuses on the former. We hypothesize that Flower and Hayes' cognitive process theory of writing-which characterizes writing through six cognitive processes-offers an interpretable bridge between observable writing behavior and appropriate support types. Through a formative study and literature review, we identify 14 writing support types associated with these cognitive processes, along with characteristic interaction behaviors linked to each process. We then instantiate this framework in AToM CoWriter, which infers support needs from writing interactions and document context. Two within-subjects studies (N = 21) provide initial evidence that this approach improves expressiveness and idea exploration, and that cognitive process inference increases engagement with proactive suggestions. These findings suggest that cognitive processes can provide a promising basis for support selection in proactive writing systems.
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