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“AI+PAD”课堂教学模式创新与教学实践

张霞1, 桑晓光1, 王锦霞1, 孟皓1, 郑伟2, 薛志强2   

  1. 1 东北大学理学院化学系, 辽宁 沈阳 110819;
    2 北京慕华信息科技有限公司(学堂在线), 北京 100036
  • 收稿日期:2026-06-25 录用日期:2026-07-22
  • 通讯作者: 张霞 E-mail:xzhang@mail.neu.edu.cn Zhang Xia
  • 基金资助:
    辽宁省“兴辽英才计划”教学名师项目(XLYC2511066)；东北大学2026年度本科教育教学研究与改革项目(XJGYB2026004)

Innovation and teaching practice of the “AI+PAD” classroom teaching model

Zhang Xia1, Sang Xiaoguang1, Wang Jinxia1, Meng Hao1, Zheng Wei2, Xue Zhiqiang2   

  1. 1 Department of Chemistry, College of Sciences, Northeastern University, Shenyang 110819, Liaoning Province, China;
    2 Beijing Muhua Information Service Co Ltd (Xuetang X), Beijing 100036, China
  • Received:2026-06-25 Accepted:2026-07-22
  • Contact: Zhang Xia E-mail:xzhang@mail.neu.edu.cn

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摘要： 依托无机化学智慧课程教学平台，将人工智能(AI)技术深度融入PAD (Presentation-Assimilation-Discussion)对分课堂教学模式，创建“精准讲解-自适应内化吸收-智慧研讨”增效教学流程，形成“教师-AI-学生”三元协同育人新生态，是高等教育数字化转型背景下课堂教学模式创新性改革探索。文章聚焦“AI+PAD”融合创新，以无机化学实验课程中“Fe3O4过氧化纳米酶的合成及酶催化动力学实验”讨论课堂为实践案例，阐释了AI在课前学情诊断、课中实时互动、课后精准评价中的嵌入机制，验证了该模式在提升学生课堂参与度、促进深度学习方面的实效。教学实践表明，AI+PAD模式有效破解了传统课堂“满堂灌”、学生被动接受、师生互动不足等痛点问题，为理工类基础课程的课堂教学模式改革提供了可参考的实践样本。

关键词: 人工智能, PAD对分课堂, 智慧课程, 师生机协同, 无机化学实验课程

Abstract: In response to the digital transformation of university education, this study integrates Artificial Intelligence (AI) technology into the PAD (Presentation-Assimilation-Discussion) bisected classroom teaching model, leveraging an AI-empowered intelligent course platform of inorganic chemistry. A synergistic teaching workflow characterized by “Precision Instruction-Adaptive Assimilation-Intelligent Discussion” has been developed, giving rise to a novel Teacher-AI-Student triadic collaborative education ecosystem. This reform represents an innovative exploration of classroom teaching models under the context of digital transformation in education. Focusing on the “AI+PAD” integration, this paper takes the discussion session of “Synthesis of Fe3O4 peroxidase-like nanozymes and enzyme catalytic kinetics experiment” in the inorganic chemistry experiment course as a practical case. It elaborates on the embedding mechanisms of AI in pre-class learning analytics and diagnosis, in-class real-time interaction, and post-class precision evaluation, thereby validating the model’s effectiveness in enhancing student classroom participation and promoting deep learning. Teaching practice demonstrates that the AI+PAD model effectively addresses the pain points of traditional classrooms, such as instructor-dominated lecturing, passive student reception, and insufficient teacher-student interaction, offering a replicable practical paradigm for the reform of foundational science and engineering courses.

Key words: Artificial intelligence, PAD bisected classroom, Intelligent course, Teacher-AI-student triadic collaboration, Inorganic chemistry experiment course