GenQuest：一款面向语言学习者的基于大语言模型的文字冒险游戏
GenQuest: An LLM-based Text Adventure Game for Language Learners
AI总结：
本研究开发了基于LLMs的生成式文字冒险游戏GenQuest，通过定制化互动叙事与语境词汇辅助助力EFL学习，试点研究证实其词汇提升效果良好且用户评价积极。
摘要：
GenQuest是一款生成式文字冒险游戏，它利用大语言模型（Large Language Models, LLMs），通过沉浸式互动叙事促进第二语言学习。该系统让英语作为外语（English as a Foreign Language, EFL）的学习者参与协作式“自选冒险”风格的叙事，叙事会根据学习者的选择动态生成。系统融入了分支决策点、故事里程碑等游戏机制，在保持叙事连贯性的同时支持学习者主导的情节发展。其核心教学功能包括：为每位学习者的熟练度水平定制生成内容，以及词汇助手——可为学习者查询的从单词、短语到句子的文本字符串提供语境化解释。针对中国高校EFL学生开展的试点研究结果显示，该游戏在词汇提升方面效果可观，用户评价积极。研究还讨论了参与者关于叙事长度与质量的建议，以及他们对插图等多模态内容的需求。
英文摘要：
GenQuest is a generative text adventure game that leverages Large Language Models (LLMs) to facilitate second language learning through immersive, interactive storytelling. The system engages English as a Foreign Language (EFL) learners in a collaborative "choose-your-own-adventure" style narrative, dynamically generated in response to learner choices. Game mechanics such as branching decision points and story milestones are incorporated to maintain narrative coherence while allowing learner-driven plot development. Key pedagogical features include content generation tailored to each learner's proficiency level, and a vocabulary assistant that provides in-context explanations of learner-queried text strings, ranging from words and phrases to sentences. Findings from a pilot study with university EFL students in China indicate promising vocabulary gains and positive user perceptions. Also discussed are suggestions from participants regarding the narrative length and quality, and the request for multi-modal content such as illustrations.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
