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Evolutionary computation approaches to the Curriculum Sequencing problem

机译:课程排序问题的进化计算方法

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Within the field of e-Learning, a learning path represents a match between a learner profile and his preferences from one side, and the learning content presentation and the pedagogical requirements from the other side. The Curriculum Sequencing problem (CS) concerns the dynamic generation of a personal optimal learning path for a learner. This problem has gained an increased research interest in the last decade, as it is not possible to have a single learning path that suits every learner in the widely heterogeneous e-Learning environment. Since this problem is NP-hard, heuristics and meta-heuristics are usually used to approximate its solutions, in particular Evolutionary Computation approaches (EC). In this paper, a review of recent developments in the application of EC approaches to the CS problem is presented. A classification of these approaches is provided with emphasis on the tools necessary for facilitating learning content reusability and automated sequencing.
机译:在电子学习领域中,学习路径表示从一侧看学习者的个人资料和他的喜好,从另一侧表示学习内容的介绍和教学要求之间的匹配。课程排序问题(CS)与学习者个人最佳学习路径的动态生成有关。在过去的十年中,这个问题已经引起了越来越多的研究兴趣,因为在广泛的异构电子学习环境中,不可能有一条适合每个学习者的单一学习道路。由于此问题是NP难题,因此通常使用启发式和元启发式方法来近似解决方案,尤其是进化计算方法(EC)。在本文中,对EC方法在CS问题中的应用的最新进展进行了综述。这些方法的分类重点放在促进学习内容可重用性和自动排序所需的工具上。

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