Evaluation of Individual Importance in Online Interactive Networks and Its Impact on Learning Outcomes
Online interaction is the foundation and core of online learning such as MOOC， online open courses. In an online interactive network， each learner has a different location and role. How to identify individuals who are important in the interaction network is particularly important. This research is based on the analysis of the importance evaluation of nodes in the social network. Based on the core idea of PageRank algorithm， an individual importance assessment model and method in the online interaction network are proposed. Through the analysis of online interaction data of learners in SPOC， it is concluded that the importance of learners in the interactive network has no significant effect on the level of knowledge construction; however， learners with more important roles in the interactive network have significantly higher academic performance.
|關鍵詞||在线交互、社会网络分析、节点重要性、知识建构水平、Online Interaction、Social Network Analysis、Node Importance、Level of Knowledge Construction、CSSCI|