Brewe, Bruun, and Bearden first applied network analysis to understand patterns of incorrect conceptual physics reasoning in multiple-choice instruments introducing the module analysis for multiple-choice responses (MAMCR) algorithm. Wells et al. proposed an extension to the algorithm which allowed the analysis of large datasets called modified module analysis (MMA). This method analyzed the network structure of the correlation matrix of the responses to a multiple-choice instrument. Both MAMCR and MMA could only be applied to networks of incorrect responses. In this study, an extension of MMA is explored which allows the analysis of networks involving both correct and incorrect responses. The extension analyzes the network structure of the partial correlation matrix instead of the correlation matrix. The new algorithm, called MMA-P, was applied to the FCI and recovered much of the structure identified by MMA. The algorithm also identified sets of correct answers requiring similar physical reasoning reported in previous studies. Beyond groups of all correct and all incorrect responses, some groups of responses which mixed correct and incorrect responses were also identified. Some of these mixed response groups were produced when a correct response was selected for incorrect reasons; some of the groups were related to the gender unfair items previously reported for the FCI.

中文翻译：

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扩展修改后的模块分析以包括正确的响应：力概念清单的分析

Brewe，Bruun和Bearden首先应用网络分析来理解选择题工具中错误的概念物理推理的模式，并介绍了选择题响应（MAMCR）算法的模块分析。韦尔斯等。提出了对该算法的扩展，该算法允许对称为修改模块分析（MMA）的大型数据集进行分析。该方法分析了对多项选择工具的响应的相关矩阵的网络结构。MAMCR和MMA都只能应用于错误响应的网络。在这项研究中，探索了MMA的扩展，它允许分析涉及正确和错误响应的网络。该扩展分析部分相关矩阵而不是相关矩阵的网络结构。称为MMA-P的新算法已应用于FCI，并恢复了MMA识别的大部分结构。该算法还确定了正确答案的集合，这些答案需要先前研究中报告的相似的物理推理。除了所有正确答案和错误答案的组合之外，还确定了一些混合了正确答案和错误答案的答案。当由于错误的原因选择了正确的回答时，就会产生其中一些混合回答。其中一些小组与先前为FCI报告的性别不平等项目有关。