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Particle Swarms for Competency-Based CurriculumSequencing

机译:基于胜任力的课程排序的粒子群

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In e-learning initiatives content creators are usually required to arrange a set of learning resources in order to present them in a comprehensive way to the learner. Course materials are usually divided into reusable chunks called Learning Objects (LOs) and the ordered set of LOs is called sequence, so the process is called LO sequencing. In this paper an intelligent agent that performs the LO sequencing process is presented. Metadata and competencies are used to define relations between LOs so that the sequencing problem can be characterized as a Constraint Satisfaction Problem (CSP) and artificial intelligent techniques can be used to solve it. A Particle Swarm Optimization (PSO) agent is proposed, built, tuned and tested. Results show that the agent succeeds in solving the problem and that it handles reasonably combinatorial explosion inherent to this kind of problems.
机译:在电子学习计划中,通常要求内容创建者安排一套学习资源,以便以全面的方式向学习者展示。课程材料通常分为称为学习对象(LO)的可重用块,LO的有序集合称为序列,因此该过程称为LO排序。在本文中,介绍了执行LO排序过程的智能代理。使用元数据和能力来定义LO之间的关系,以便可以将排序问题表征为约束满足问题(CSP),并可以使用人工智能技术来解决该问题。提出,构建,调整和测试了粒子群优化(PSO)代理。结果表明,该代理成功解决了该问题,并且可以合理地处理此类问题固有的组合爆炸。

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