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Personalized Content Sequencing Based on Choquet Fuzzy Integral and Item Response Theory

机译：基于Choquet模糊积分和项目响应理论的个性化内容排序

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摘要

Personalization of learning path is an important research issue in current E-learning systems because learners differ from various aspects such as knowledge level, experience, and ability.Therefore, most personalized systems focus on learner preferences, and browsing behavior for providing adaptive learning path guidance.However, these systems usually neglect to consider the dependence among the learning concept difficulty and the learner model.Generally, a learning concept has varied difficulty for learners with different levels of knowledge.Considered the importance of learning path with learning concepts difficulty that are highly matched to the leiarner's knowledge and ability, this paper proposes a system based on Choquet Fuzzy Integral and Item Response Theory.This system recommends appropriate learning contents to learner during the learning process.
机译：学习路径的个性化是当前电子学习系统中一个重要的研究问题，因为学习者在知识水平，经验和能力等各个方面都有所不同，因此，大多数个性化系统都专注于学习者的偏好和浏览行为，以提供自适应的学习路径指导但是，这些系统通常忽略了学习概念难度和学习者模型之间的依赖关系。通常，学习概念对于知识水平不同的学习者而言具有不同的难度。结合学习者的知识和能力，提出一种基于Choquet模糊积分和项目反应理论的系统。该系统在学习过程中向学习者推荐合适的学习内容。

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