StoryLensEdu: 通过叙事驱动的多智能体系统生成个性化学习报告
StoryLensEdu: Personalized Learning Report Generation through Narrative-Driven Multi-Agent Systems
AI总结：
StoryLensEdu通过叙事驱动的多智能体系统生成个性化学习报告，提升学习过程的参与度和理解深度。
摘要：
个性化反馈在自我调节学习（SRL）中起着重要作用，帮助学生跟踪进度并优化其策略。然而，当前常见的解决方案，如基于文本的报告或学习分析仪表盘，常常面临解释性差、表现单调和可解释性有限的问题。为了解决这些挑战，我们提出了StoryLensEdu，一种以叙事驱动的多智能体系统，能够自动生成直观、吸引人且交互式的学习报告。StoryLensEdu集成了三个智能体：一个数据分析师，基于以学习目标为中心的结构提取数据洞察；一个教师，确保教育相关性并提供可操作的建议；一个叙述者，利用英雄旅程叙事框架组织这些洞察。StoryLensEdu支持生成后的交互式问答以提高可解释性和用户参与度。我们在一个真实高中进行了形成性研究，并与一个电子学习团队合作，迭代开发StoryLensEdu以指导我们的设计。与真实用户的评估显示，StoryLensEdu增强了参与度并促进了对学习过程的更深入理解。
英文摘要：
Personalized feedback plays an important role in self-regulated learning (SRL), helping students track progress and refine their strategies. However, current common solutions, such as text-based reports or learning analytics dashboards, often suffer from poor interpretability, monotonous presentation, and limited explainability. To overcome these challenges, we present StoryLensEdu, a narrative-driven multi-agent system that automatically generates intuitive, engaging, and interactive learning reports. StoryLensEdu integrates three agents: a Data Analyst that extracts data insights based on a learning objective centered structure, a Teacher that ensures educational relevance and offers actionable suggestions, and a Storyteller that organizes these insights using the Heroes Journey narrative framework. StoryLensEdu supports post-generation interactive question answering to improve explainability and user engagement. We conducted a formative study in a real high school and iteratively developed StoryLensEdu in collaboration with an e-learning team to inform our design. Evaluation with real users shows that StoryLensEdu enhances engagement and promotes a deeper understanding of the learning process.
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。
