基于复杂网络分析为进一步剖析在线学习行为中的注意力，本研究选取学堂在线平台《C++语言程序设计基础（2019春）》为例，对在线视频学习中集体注意力的分配模式，以及MOOCs视频设计和与视频的交互如何影响集体注意力的积聚、流转和耗散进行探究，从集体层面角度探讨了开放灵活的在线学习环境中注意力减少的动态过程。研究结果显示：在视频中呈现知识的方式会影响注意力分配的模式，但不会影响参与者观看视频的时长。视频中使用的全屏幕使用会对参与者观看视频时长产生影响，可以通过学习者与视频的交互行为预测学习者的集体注意力流转。本研究为了解注意力流动的模式和动态以及学习者如何与视频互动提供了新的视角，有助于设计更能有效促进学生学习的在线视频资源，以避免造成学习者负荷超载。

Based on complex network analysis, in order to further analyze the attention in online learning behavior, this study selects "Fundamentals of C++ programming (spring 2019)" on XuetangX as an example through which to observe the allocation patterns of attention within MOOC videos, as well as how the features of videos and interactions with videos affect the accumulation, circulation and dissipation of collective attention. This paper discusses the dynamic process of participation mode reduction in an open and flexible online learning environment. The results show that: the way of presenting knowledge in the video will affect the pattern of attention allocation, but will not affect the time of watching the video. The use of full screen in the video affects how long the participants were likely to watch the videos, and the amount of watching video can be used to predict learners' collective attention flow. The results imply that understanding the patterns and dynamics of attention flow as well as how learners actually interact with videos will allow us to design cost-effective learning resources to prevent learners from becoming overloaded.