用自然语言让老师和AI共同设计教育游戏，明确教学目标与玩法匹配。
Bridging Pedagogy and Play: Introducing a Language Mapping Interface for Human-AI Co-Creation in Educational Game Design
- 以自然语言为接口，将教学目标与游戏机制通过四部分联动映射。
- 非专家用户可直接编辑教学意图，避免依赖黑箱AI建议。
- 适合教育工作者、课程设计师，提升教学与游戏的对齐性。
教育游戏能促进批判性思维、问题解决能力和学习动机，但教师常难以设计出能稳定达成特定学习目标的游戏。现有创作工具虽降低了编程门槛，但仍无法解决教育游戏设计的核心难题，且可能使非专家设计者过度依赖不可解释的AI建议。本文设计了一款基于受控自然语言框架的网页工具，将语言作为大模型辅助教育游戏设计的主要界面。在该工具中，用户与大模型助手协同构建一种结构化语言，通过四个相互关联的组件实现教学法向游戏机制的映射。我们认为，通过在界面中显式表达并可编辑教学意图，该工具有望降低非专家设计者的门槛，保留人类在关键决策中的主体性，并在共创过程中及之后实现教学与游戏之间的对齐与反思。
原文摘要 · Abstract (English)
Educational games can foster critical thinking, problem-solving, and motivation, yet instructors often find it difficult to design games that reliably achieve specific learning outcomes. Existing authoring environments reduce the need for programming expertise, but they do not eliminate the underlying challenges of educational game design, and they can leave non-expert designers reliant on opaque suggestions from AI systems. We designed a controlled natural language framework-based web tool that positions language as the primary interface for LLM-assisted educational game design. In the tool, users and an LLM assistant collaboratively develop a structured language that maps pedagogy to gameplay through four linked components. We argue that, by making pedagogical intent explicit and editable in the interface, the tool has the potential to lower design barriers for non-expert designers, preserves human agency in critical decisions, and enables alignment and reflections between pedagogy and gameplay during and after co-creation.
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