Recommending a personalized lesson plan based on constraint satisfaction and negotiation

Chiao-Ching Huang, T. Huang, Chia-Hung Shih, V. Soo, Yao-Chen Lin
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引用次数: 3

Abstract

An appropriate lesson plan is important in teaching and learning. A traditional lesson plan is constructed manually by a teacher with great efforts and difficult to be generated automatically. In this research, we proposed an intelligent agent system able to recommend a personalized lesson plan by using methods in constraint satisfaction problems and negotiation. The constraints consist of teaching goals, teaching time, student abilities, classroom resources and teacher's preference, whereas the recommendation by negotiation system can assist a teacher user to find the coordinated solution under minimum constraint relaxation when no exact solution can be found.
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推荐基于约束满足和协商的个性化课程计划
适当的教案对教与学都很重要。传统的教案是由教师手工编制的,需要付出很大的努力,难以自动生成。在这项研究中,我们提出了一个智能代理系统,可以使用约束满足问题和协商的方法来推荐个性化的课程计划。约束条件包括教学目标、教学时间、学生能力、课堂资源和教师偏好,而协商系统的推荐可以在无法找到精确解的情况下,帮助教师用户在约束放松最小的情况下找到协调的解决方案。
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