AI助教可切换教师与学生角色,支持希腊中学教育。
Beyond the Chatbot: Co-Learning and Co-Teaching through a Dual-Persona Generative-AI Assistant
- 双模型架构让AI在教学与学习角色间自动切换。
- 基于希腊课程的RAG系统精准匹配教材内容。
- 适合教育科技研究者与一线教师参考使用。
本文提出一种生成式AI应用,旨在支持希腊中等教育中的教师与学生。系统集成两个大语言模型(Gemini、DeepSeek)与一个小语言模型(Gemma),在检索增强生成(RAG)框架下构建,具备基于用户角色自适应推理与沟通风格的能力。不同于传统聊天机器人,该系统引入教学角色切换机制,使同一AI模型可扮演教学伙伴与学习引导者双重角色。通过专为希腊教育领域定制的RAG架构,将官方教材按教学单元拆分并添加元数据,保留课程结构与教学语境,体现生成式AI对现代教学设计的优化潜力。初始案例研究聚焦于希腊初中家政课——一门融合经济学、健康教育与社会责任的跨学科课程。该助手可协助学生理解财务素养、资源管理与健康生活等核心概念,同时帮助教师设计符合官方课程标准的真实教学材料、形成性评估及课堂活动。本研究突破了简单聊天机器人的局限,提出一种结构化、情境自适应的教学生成式助手框架,有效连接技术、课程与人类学习。
原文摘要 · Abstract (English)
In this paper we present a generative AI application developed to support both teachers and students in secondary education. The system employs two Large Language Models-LLMs, Gemini and DeepSeek, and a Small Language Model-SLM, Gemma, integrated within a Retrieval Augmented Generation - RAG framework, creating a pedagogically grounded, Greek-language assistant capable of adapting its reasoning and communication style to the user role. Unlike conventional chatbots, the assistant introduces pedagogical persona switching, a dual-role mechanism that enables the same AI model to act as both a teaching companion and a learning guide. Utilizing a RAG paradigm tailored to the Greek educational domain, the architecture segments official textbooks into coherent units. Enriched with specific metadata, these units preserve curricular structure and instructional context, demonstrating how generative AI optimizes modern instructional design. The initial case study focuses on home economics in Greek lower secondary education, a cross-disciplinary subject that integrates elements of economics, health education, and social responsibility. The assistant has been developed to support both learners and educators in complementary ways. In future classroom implementations, students will be able to use it to clarify key concepts such as financial literacy, resource management, and healthy living, while teachers could employ it to design authentic instructional materials, formative assessments, and classroom activities aligned with the official curriculum. The study elevates the concept beyond a simple chatbot, proposing a structured, contextually adaptive framework for pedagogical generative assistants that effectively bridge technology, curriculum, and human learning.
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