Reengineering the Feature Distillation Process: A case study in detection of Gaming the System
Reengineering the Feature Distillation Process: A case study in detection of Gaming the System
复制标题
重新设计特征蒸馏过程：检测系统博弈的案例研究
DOI：
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发表时间：
2014
期刊：
影响因子：
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通讯作者：
Jaclyn L. Ocumpaugh
中科院分区：
文献类型：
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作者：
L. Paquette;A. Carvalho;R. Baker;Jaclyn L. Ocumpaugh
随着教育技术的成熟，研究争论数据挖掘（EDM）或知识工程（KE）范式是最好的建模复杂的学习结构。混合范式可以从两种方法中获得优势。特别是，最近的工作认为，成功的数据挖掘取决于周到的功能工程。在本文中，我们探讨了使用认知建模（知识工程的一种形式），以提高游戏系统，EDM中研究最多的复杂结构之一的检测器的特征工程过程。使用这个结构使我们能够衡量我们的技术在多大程度上提高了以前的模型的性能。
As education technology matures, researches debate whether data mining (EDM) or knowledge engineering (KE) paradigms are best for modeling complex learning constructs. A hybrid paradigm may capture strengths from both approaches. In particular, recent work has argued that successful data mining depends on thoughtful feature engineering. In this paper, we explore the use of cognitive modeling (a form of knowledge engineering) to enhance the feature engineering process for detectors of gaming the system, one of the most studied complex constructs in EDM. Using this construct enables us to measure the extent to which our techniques improve performance over previous models.