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首页> 外文期刊>Journal of Educational Data Mining >Using the ECD Framework to Support Evidentiary Reasoning in the Context of a Simulation Study for Detecting Learner Differences in Epistemic Games
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Using the ECD Framework to Support Evidentiary Reasoning in the Context of a Simulation Study for Detecting Learner Differences in Epistemic Games

机译:在用于研究认知游戏中学习者差异的模拟研究中,使用ECD框架支持证据推理

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摘要

The evidence-centered design (ECD) framework is a powerful tool that supports careful and critical thinking aboutthe identification and accumulation of evidence in assessment contexts. In this paper, we demonstrate how the ECDframework provides critical support for designing simulation studies to investigate statistical methods within an ill-definedmethodological domain like games-based assessment. We discuss the design and selected findings of acomplex simulation study to investigate the utility of statistics derived from a non-parametric method calledepistemic network analysis; this method is used in practice for the analysis of real data from a suite of digitallearning environments called epistemic games. We present findings that show that one marginal ENA statistic, theweighted density statistic from social network analysis, has some ability to detect differences among a variety ofsimulated learners when they play different types of simulated games. Detection strength ranged from weak tostrong, depending jointly on game design characteristics and the types of learners being compared. Our workillustrates the complex challenges of how best to describe, justify, and evaluate design decisions for simulationstudies in the context of games-based assessment.
机译:以证据为中心的设计(ECD)框架是一个强大的工具,可支持对评估环境中证据的识别和积累进行认真而严格的思考。在本文中,我们演示了ECDframework如何为设计模拟研究以调查基于游戏评估的未明确定义的方法域内的统计方法提供关键支持。我们讨论了复杂模拟研究的设计和选定的结果,以研究从称为流行网络分析的非参数方法得出的统计数据的实用性。这种方法在实践中用于分析来自称为认知游戏的一系列数字学习环境中的真实数据。我们的发现表明,一项边际ENA统计数据(来自社交网络分析的加权密度统计数据)具有一定的能力,能够在他们玩不同类型的模拟游戏时检测各种模拟学习者之间的差异。检测强度的范围从弱到强,这取决于游戏设计特征和所比较学习者的类型。我们的工作说明了在基于游戏的评估的背景下,如何最好地描述,论证和评估模拟研究的设计决策所面临的复杂挑战。

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