首页> 外文会议>IFIP 204; IFIP(International Federation for Information Processing) Conference on Artificial Intelligence Applications and Innovations(AIAI); 20060607-09; Athens(GR) >Using Genetic Algorithms and Decision Trees for a posteriori Analysis and Evaluation of Tutoring Practices based on Student Failure Models
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Using Genetic Algorithms and Decision Trees for a posteriori Analysis and Evaluation of Tutoring Practices based on Student Failure Models

机译:基于学生失败模型的遗传算法和决策树的后验分析与评估

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摘要

Many students who enrol in the undergraduate program on informatics at the Hellenic Open University (HOU) fail the introductory course exams and drop out. We analyze their academic performance, derive short rules that explain success or failure in the exams and use the accuracy of these rules to reflect on specific tutoring practices that could enhance success.
机译:许多在希腊开放大学(HOU)攻读信息学本科课程的学生都没有通过入门课程考试而辍学。我们分析他们的学业成绩,得出解释考试成功或失败的简短规则,并使用这些规则的准确性来反思可以提高成功率的特定补习做法。

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