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A Case Study Empirical Comparison of Three Methods to Evaluate Tutorial Behaviors

机译:一种案例研究三种方法评价教程行为的实证比较

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Researchers have used various methods to evaluate the fine-grained interactions of intelligent tutors with their students. We present a case study comparing three such methods on the same data set, logged by Project LISTEN's Reading Tutor from usage by 174 children in grades 2-4 (typically 7-10 years) over the course of the 2005-2006 school year. The Reading Tutor chooses randomly between two different types of reading practice. In assisted oral reading, the child reads aloud and the tutor helps. In "Word Swap," the tutor reads aloud and the child identifies misread words. One method we use here to evaluate reading practice is conventional analysis of randomized controlled trials (RCTs), where the outcome is performance on the same words when encountered again later. The second method is learning decomposition, which estimates the impact of each practice type as a parameter in an exponential learning curve. The third method is knowledge tracing, which estimates the impact of practice as a probability in a dynamic Bayes net. The comparison shows qualitative agreement among the three methods, which is evidence for their validity.
机译:研究人员利用各种方法与学生评价的智能导师细粒度的相互作用。我们提出一个案例研究,对同一个数据集,比较了三种这样的方法,通过记录从项目174名儿童等级2-4(通常7-10岁)在2005-2006学年的过程中使用LISTEN的阅读导师。阅读导师选择两个随机之间的不同类型的阅读实践。在辅助朗读,孩子朗读和导师的帮助。在“字交换,”导师朗读和孩子识别误读的话。我们这里使用的评估阅读练习的方法是随机对照试验(RCT)的常规分析,在以后再次遇到时,结果是在相同的话性能。第二种方法是学习分解,其估计每次练习类型的如在一个指数的学习曲线的参数的影响。第三种方法是知识的跟踪,评价的实践作为一个动态贝叶斯网络概率的影响。比较结果显示定性的三种方法达成一致意见,这是其有效性的证据。

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