ChEdBot: Designing a Domain-Specific Conversational Agent in a Simulational Learning Environment Using LLMs

Andreas Martin, Charuta Pande, Hans Friedrich Witschel, Judith Mathez
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Abstract

We propose conversational agents as a means to simulate expert interviews, integrated into a simulational learning environment: ChEdventure. Designing and developing conversational agents using the existing tools and frameworks requires technical knowledge and a considerable learning curve. Recently, LLMs are being leveraged for their adaptability to different domains and their ability to perform various tasks in a natural, human-like conversational style. In this work, we explore if LLMs can help educators easily create conversational agents for their individual teaching goals. We propose a generalized template-based approach using LLMs that can instantiate conversational agents as an integrable component of teaching and learning activities. We evaluate our approach using prototypes generated from this template and identify guidelines to improve the experience of educators.
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ChEdBot:使用 LLM 在模拟学习环境中设计特定领域的对话代理
我们建议将对话代理作为模拟专家访谈的一种手段,并将其集成到模拟学习环境中:ChEdventure。使用现有工具和框架设计和开发会话代理需要技术知识和相当长的学习曲线。最近,LLM 因其对不同领域的适应性以及以自然、类似人类的对话方式执行各种任务的能力而受到了人们的青睐。在这项工作中,我们将探讨 LLM 能否帮助教育工作者轻松创建对话式代理,以实现各自的教学目标。我们利用 LLMs 提出了一种基于模板的通用方法,这种方法可以将对话代理实例化,使其成为教学活动中可整合的组成部分。我们使用从该模板生成的原型对我们的方法进行了评估,并确定了改善教育者体验的指导原则。
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