The purpose of this study was to explore the relationship between clout and cognitive processing in massive open online course (MOOC) discussion forum posts. Cognitive processing, a category variable generated by the automated text analysis tool, Linguistic Inquiry Word Count (LIWC), is made up of six sub‐scores (insight, causation, discrepancy, tentativeness, certainty and differentiation). Clout is a nontransparent summary variable in LIWC that can be used to understand the level of confidence conveyed in the text. Because clout is nontransparent, we do not know the algorithm used to calculate its value. To better understand this variable, this study examined cognitive processing alongside clout. In this study, a series of linear mixed models were fitted to evaluate, after controlling for gender, degree and type of post, if the focal relationship between each sub‐score of cognitive processing as the predictor variables and clout as the dependent variable changed across courses with different pacing (self‐paced or instructor‐paced). Next, the focal relationship between each predictor and clout was examined with or without regard to pacing. Findings showed words classified as showing discrepancy, certainty or differentiation were negatively associated with clout scores.

中文翻译：

---

在MOOC论坛中探索影响力与认知处理之间的关系

这项研究的目的是探讨大规模开放在线课程（MOOC）讨论论坛帖子中的影响力与认知处理之间的关系。认知处理是由自动文本分析工具“语言查询词计数”（LIWC）生成的类别变量，由六个子得分组成（洞察力，因果关系，差异，暂定性，确定性和区分性）。Clout是LIWC中的非透明摘要变量，可用于了解文本中传达的置信度。由于clout是不透明的，因此我们不知道用于计算其值的算法。为了更好地理解此变量，本研究考察了影响力与认知力的关系。在这项研究中，在控制了性别，职位程度和职位类型之后，拟合了一系列线性混合模型来评估 如果认知过程的每个子得分之间的关​​系（作为预测变量）和影响力（作为因变量）在具有不同节奏（自定进度或讲师定速）的课程之间发生了变化。接下来，检查每个预测变量与影响力之间的焦点关系，无论是否考虑起搏。调查结果显示，分类为显示差异，确定性或差异性的单词与影响力得分呈负相关。