Despite the 30 years of research on the effects of using computer-based mapping tools to construct concept maps, the research has provided little insight into the cognitive processes and strategies students use to create more accurate maps and the types of behaviors that can be mined in computer-based mapping tools to reveal and support processes that improve student performance. This study used video analysis to identify, operationally define, and code processes of reasoning students used while using a computer-based tool to construct causal maps. The process data was then used to conduct a path analysis to determine which and how specific processes impact the quality of students' causal maps and to determine how students’ prior knowledge on the given problems influence which processes students use. The findings reveal that students exhibiting the tendency to use more backward than forward processing and use more breadth than depth-first processing produced higher quality causal maps, and that the influence of prior content knowledge on what processes students use are not conclusive. The findings and the methods developed in this study present new ideas on ways to integrate learning analytics into computer-based mapping tools to model and manage the cognitive processes students use to construct better cognitive maps.

尽管对使用基于计算机的地图工具构造概念图的效果进行了30年的研究，但该研究对学生用来创建更准确的地图的认知过程和策略以及可以在其中挖掘的行为类型的了解很少。基于计算机的地图绘制工具，用于揭示和支持提高学生表现的过程。这项研究使用视频分析来识别，操作上定义和编码推理学生的过程，同时使用基于计算机的工具构造因果图。然后使用过程数据进行路径分析，以确定哪些过程以及特定过程如何影响学生因果图的质量，并确定学生对给定问题的先验知识如何影响学生使用的过程。调查结果表明，学生倾向于使用比后向处理更多的正向趋势，比深度优先处理使用的广度更大，从而产生了更高质量的因果图，并且先验内容知识对学生使用哪种过程的影响尚无定论。这项研究中发现的结果和方法提出了关于将学习分析集成到基于计算机的制图工具中以建模和管理学生用来构建更好的认知图的认知过程的新思路。