用AI把编程视频变互动课，能根据学习情况自动调整教学。
CogGen: A Learner-Centered Generative AI Architecture for Intelligent Tutoring with Programming Video
- 按学习目标分割视频，结合认知导师策略生成对话辅导
- 学生模型用贝叶斯知识追踪，实现个性化教学路径
- 三组件协同提升教学效果，适合想改进编程视频课的教育者
我们提出CogGen，一种以学习者为中心的生成式AI架构，通过将编程视频转化为交互式、自适应的学习体验，融合学生建模与基于认知导师框架的生成式辅导。该架构包含三个部分：（1）按学习目标对视频进行分段；（2）采用认知导师策略的对话式辅导引擎；（3）利用贝叶斯知识追踪的学生模型以动态调整教学内容。技术评估显示视频分段准确率高，且在知识、方法、行为和互动四个层面具有强教学契合度。消融实验证实各组件对生成有效指导至关重要。本工作通过将结构化学生建模与交互式AI对话结合，推动了智能辅导系统的进展，为提升编程视频教育提供了可扩展方案。
原文摘要 · Abstract (English)
We introduce CogGen, a learner-centered AI architecture that transforms programming videos into interactive, adaptive learning experiences by integrating student modeling with generative AI tutoring based on the Cognitive Apprenticeship framework. The architecture consists of three components: (1) video segmentation by learning goals, (2) a conversational tutoring engine applying Cognitive Apprenticeship strategies, and (3) a student model using Bayesian Knowledge Tracing to adapt instruction. Our technical evaluation demonstrates effective video segmentation accuracy and strong pedagogical alignment across knowledge, method, action, and interaction layers. Ablation studies confirm the necessity of each component in generating effective guidance. This work advances AI-powered tutoring by bridging structured student modeling with interactive AI conversations, offering a scalable approach to enhancing video-based programming education.
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