人机协同：“对分课堂”与AI智能体深度融合的教学模式研究

Research on the Teaching Mode of Deep Integration of the “Presentation-Assimilation-Discussion Class” and AI Agents in Human-Machine Collaboration

摘要: 本研究聚焦“对分课堂”(PAD Class)这一本土原创教学模式，针对其在实际应用中面临的“内化质量难监控、讨论深度难保障、个性化指导难实现”三大痛点，创新性地提出AI智能体作为教学协同者的融合路径。研究系统设计了AI智能体嵌入对分课堂“讲授–内化–讨论–总结”四环节的具体方案：讲授阶段通过历史数据分析精准把握学生认知起点；内化阶段以“一对一智能学伴”身份实现“测–讲–练”自适应学习闭环，全程记录行为数据并提炼共性难题；讨论阶段基于内化数据推送差异化议题，并通过“小组共答一套题”机制强化协作巩固；总结阶段整合全流程数据提炼Top 3共性问题，辅助教师靶向讲解。本成果致力于形成可借鉴、可推广的智能化教学改革范例，推动对分课堂从“经验型操作”向“精准化、智能化、个性化”转型，为人工智能赋能高等教育提供实践路径。

Abstract: This research focuses on the local original teaching model of the “PAD Class”. In response to the three major pain points it encounters in practical application, namely “difficulty in monitoring quality, difficulty in ensuring the depth of discussion, and difficulty in implementing personalized guidance”, it innovatively proposes an integration path of AI agents as teaching collaborators. The research systematically designed a specific plan for embedding AI agents into the four stages of the PAD Class: “lecture-internalization-discussion-summary”: in the lecture stage, historical data analysis is used to accurately grasp the students’ cognitive starting point; in the internalization stage, as an “intelligent learning companion” identity, the “test-lecture-practice” adaptive learning loop is realized, and behavioral data is recorded throughout the process and common problems are extracted; in the discussion stage, differentiated topics are pushed based on the internalization data, and the “group answering the same set of questions” mechanism is used to strengthen collaboration and consolidation; in the summary stage, the top 3 common problems are integrated from the entire process data and used to assist teachers in targeted explanations. This achievement aims to form a replicable and scalable example of intelligent teaching reform, promoting the transformation of the PAD Class from “experiential operation” to “precision, intelligence, and personalization”, and providing a practical path for the empowerment of higher education by artificial intelligence.