LS-LAB: A Framework for Comparing Curriculum Sequencing Algorithms

C. Limongelli, F. Sciarrone, Giulia Vaste
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引用次数: 6

Abstract

Curriculum Sequencing is one of the most appealing challenges in Web-based learning environments: the success of a course mainly depends on the system capability to automatically adapt the learning material to the student’s educational needs. Here we address the problem of how to compare and to test different Curriculum Sequencing algorithms in order to reason about them in a self-contained and homogeneous environment. We propose LS-LAB, a framework especially designed for comparing and testing different Curriculum Sequencing algorithms. LS-LAB has been designed to run different algorithms, each of them provided with its own Student Model representation: a Super Student Model is able to incrementally include all of them. In this framework, the Learning Node has to be compliant to the IEEE LOM specifications, while, through a suitable GUI, one can insert new algorithms or run already available ones. We are carrying out the implementation by using a 3-tier Java application technology, in order to make this environment available on the Internet. Finally we show an application example.
LS-LAB:一个比较课程排序算法的框架
课程排序是网络学习环境中最具吸引力的挑战之一:课程的成功主要取决于系统自动调整学习材料以适应学生教育需求的能力。在这里,我们解决了如何比较和测试不同的课程排序算法的问题,以便在一个自包含和同质的环境中对它们进行推理。我们提出LS-LAB,一个专门用于比较和测试不同课程排序算法的框架。LS-LAB被设计为运行不同的算法,每个算法都提供了自己的学生模型表示:超级学生模型能够增量地包括所有这些算法。在这个框架中,学习节点必须符合IEEE LOM规范,同时,通过一个合适的GUI,可以插入新的算法或运行已有的算法。我们通过使用三层Java应用程序技术来实现,以便使这个环境在Internet上可用。最后,我们展示了一个应用程序示例。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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