首页> 外文会议>Innovative Computing, Information and Control (ICICIC-2009), 2009 >Integrating IRT to Clustering Student's Ability with K-Means
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Integrating IRT to Clustering Student's Ability with K-Means

机译:将IRT与K-Means整合以聚集学生的能力

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Examination plays a role to judge learner's learning behavior and achievement in evaluation. In most cases, good grade means good learner. Teachers do not realize what learners know and how much they understand. Learners with poor grades are becoming giving up them easily. Modern evaluation, diagnoses students with learning ability not grade. There are two assumptions. First, the difficulty level of materials is suitable for the students. Second, the difficulty level of question matches the teaching material. The main purpose is diagnosing the student's ability. This research calculates the student's ability from online-test system with item response theory (IRT). We integrate K-means to cluster learner's ability which is calculated from item response theory. Teachers can modify the learning material adaptively and teach students in accordance with their aptitude in their courses.
机译:考试在评估学习者的学习行为和学习成绩方面起着重要的作用。在大多数情况下,良好的成绩意味着好的学习者。老师没有意识到学习者知道什么以及他们了解多少。成绩差的学习者正变得容易放弃他们。现代评估,诊断学生的学习能力不及格。有两个假设。首先,材料的难易程度适合学生。第二,问题的难度等级与教材相匹配。主要目的是诊断学生的能力。这项研究使用项目反应理论(IRT)从在线测试系统计算学生的能力。我们将K均值整合到聚类学习者的能力,这是根据项目反应理论计算得出的。教师可以适应性地修改学习材料,并根据他们在课程中的能力来教给学生。

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