Two-phase Blue-Red tree of rule-space model for the cognitive assessment evaluation and analysis — A case study of MTA course

Yung-Hui Chen, Chun-Hsiung Tseng, Wei-Chun Lee, L. Deng, Jing-De Weng
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引用次数: 1

Abstract

In Taiwan, it is one of the diverse indicators for the Ministry of Education to promote and evaluate their competencies that the vocational education system students have more than one professional certification. They also are one way to find the ideal jobs that enhance their competitiveness for vocational students on-the-job. Therefore, it is very important to obtain professional certification for students in vocational education systems. In particular, the more professional licenses, the more jobs students can easily get. Therefore, we propose an online learning and testing system that combines two-phase Blue-Red trees of Rule-Space Model, and it is used to remedy and analyze the learning situation of MTA courses and enhance the pass rate of MTA licenses for students. We can classify three SGs(Skill Groups) from the Certiport of Microsoft certification center in the phase one, and the three SGs(Skill Groups) can be produced as a concept map and Blue-Red trees. In the phase two, The ten chapters of MTA course are classified within the three SGs(Skill Groups) of the phase one according to the most similarity in contents between ten chapters and three SGs(Skill Groups). That is, it will be created three groups of a MTA course from previous ten chapters. The three groups can produce three concept maps and three groups of Blue-Red trees. The correction rate of each skill group can not only help improving learners own learning direction, but also help the improvement of the system itself. Our experiment results supports our methodology well.
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认知评估的两阶段蓝-红树规则空间模型评价与分析——以MTA课程为例
在台湾,职业教育系统学生拥有一个以上的专业认证是教育部促进和评估其能力的多种指标之一。对于在职的中职学生来说,它们也是找到理想工作的一种方式,可以增强他们的竞争力。因此,对于职业教育系统的学生来说,获得专业认证是非常重要的。特别是,专业执照越多,学生就越容易找到工作。因此,我们提出了一种结合规则空间模型的两阶段蓝-红树的在线学习和测试系统,用于纠正和分析MTA课程的学习情况,提高学生的MTA执照通过率。我们可以在第一阶段从Microsoft认证中心的Certiport中对三个SGs(Skill group)进行分类,并将这三个SGs(Skill group)生成概念图和蓝-红树。在第二阶段,根据10章课程内容与3个技能组内容最相似的程度,将MTA课程的10章课程划分为第一阶段的3个技能组。也就是说,它将根据前十章创建三组MTA课程。这三个小组可以制作三张概念图和三组蓝-红树。每个技能组的正确率不仅可以帮助学习者提高自己的学习方向,还可以帮助系统本身的改进。实验结果很好地支持了我们的方法。
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