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A Priori Evaluation Refinement of Curricula by Data Mining over Storyboards

机译:数据挖掘故事挖掘先验与细化课程

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摘要

In university studies, there is a flexible but complicated learning system of subject offers, enrollment rules for particular subject combinations, and prerequisites to meet for taking particular subjects, which need to be matched with students' needs and desires. Students need assistance in the jungle of such learning opportunities and limitations at today's universities. To face this problem, we employed our formerly developed storyboard concept and used it to develop, maintain, and evaluate curricula. Storyboarding is based on the idea of formally representing, processing, evaluating and refining didactic knowledge. This concept is utilized to supplement an educational system called Dynamic Learning Needs Reflection System (DLNRS) of the School of Information Environment of Tokyo Denki University, Japan. Didactic knowledge of DLNRS can be represented by storyboarding and used for supporting dynamic learning activities of students. Here, we introduce an additional benefit of storyboarding. By using data mining-like methods to evaluate storyboard paths, we are able to estimate success chances of storyboard paths. Based on this evaluation we will be able to rate planned (future) paths and thus, to prevent students from failing by non-appropriate curricula. Moreover, besides the evaluation, the estimation can be used for computer enforced suggestions to complete a path towards optimal success chances.
机译:在大学学习中,有一个灵活但复杂的学习系统的主题优惠,特别是特定主题组合的入学规则,以及符合特定科目的先决条件,需要与学生的需求和欲望相匹配。学生需要在当今大学的这种学习机会的丛林中提供帮助。要面对这个问题,我们聘请了我们以前开发的故事板概念,并用它来发展,维护和评估课程。故事板基于正式代表,加工,评估和炼制教学知识的想法。该概念用于补充日本东京丹吉大学信息环境学院的动态学习需求反射系统(DLNR)的教育系统。 DLNR的教学知识可以由故事板代表,并用于支持学生的动态学习活动。在这里,我们介绍了故事板的额外好处。通过使用类似数据挖掘的方法来评估故事板路径,我们能够估计故事板路径的成功机会。根据这种评估,我们将能够评估计划(未来)路径,从而防止学生因非适合课程而失败。此外,除了评估之外,估计可用于计算机强制建议,以完成最佳成功机会的路径。

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