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Validation study of a method for assessing complex ill-structured problem solving by using causal representations

机译：因果表示法评估复杂结构不良问题解决方法的验证研究

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摘要

The important but little understood problem that motivated this study was the lack of research on valid assessment methods to determine progress in higher-order learning in situations involving complex and ill-structured problems. Without a valid assessment method, little progress can occur in instructional design research with regard to designing effective learning environments to facilitate acquisition of expertise in complex, ill-structured knowledge domains. In this paper, we first present a method based on causal representations for assessing progress of learning in complex, ill-structured problem solving and discuss its theoretical framework. Then, we present an experimental study investigating its validity against adapted protocol analysis. This study explored the impact of a massively multiplayer online educational game, which was designed to support an interdisciplinary STEM education on ninth-grade students’ complex, ill-structured problem solving skill acquisition. We identify conceptual similarities and differences between the two methods, present our comparative study and its results, and then discuss implications for diagnostics and applications. We conclude by determining how the two approaches could be used in conjunction for further research on complex and ill-structured problem solving.
机译：推动这项研究的一个重要但鲜为人知的问题是缺乏有关在涉及复杂和结构不良问题的情况下确定高级学习进展的有效评估方法的研究。如果没有有效的评估方法，那么在设计有效的学习环境以促进复杂，结构不良的知识领域的专业知识获取方面，教学设计研究的进展就很少。在本文中，我们首先提出一种基于因果表示的方法，用于评估复杂，结构不良的问题解决中的学习进度，并讨论其理论框架。然后，我们提出了一项实验研究，研究了其对适应性协议分析的有效性。这项研究探讨了大型多人在线教育游戏的影响，该游戏旨在支持跨学科STEM教育对九年级学生复杂，结构不良的问题解决技能的掌握。我们确定这两种方法之间的概念异同，介绍我们的比较研究及其结果，然后讨论对诊断和应用的意义。最后，我们通过确定如何将这两种方法结合使用来进一步研究复杂和结构不良的问题解决方案。

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