The Evolution Analysis Of Social Network Structure And Knowledge Construction Level In Online Collaborative Learining

Interaction issues has always been the focus of research in the field of online learning.At present,the online learning interaction research at home and abroad mainly focuses on the analysis of interaction relationship,while the research on the evolution process,regular pattern and specific content of interaction in online collaborative learning is relatively rare.This paper analyzes the evolutionary characteristics and relationships of social network structure and knowledge construction of online collaborative learning from the perspective of empirical analysis using social network analysis and content analysis,exploring how interactions occur between online collaborative learning communities and how these interactions affect academic performance,and giving some advises for online collaborative learning to improve learning outcomes for online collaborative learning.The main contents of this paper are as follows:(1)Social network structure analysis of learner interaction in online collaborative learning.Analyze the evolution of the network structure from the aspects of the overall social network structure,internal substructure,individual network,and network density,centrality,and cohesion subgroups through the number of postings,topic initiators,topic respondents,and responding objects in the discussion area of the online course,in order to reveal the characteristics and laws of learner interaction in online collaborative learning.Based on the analysis,it is found that the whole network presents a loosely sparse and multi-center complex interactive network structure with obvious physical class boundaries,from the perspective of social network characteristics,there is less interaction between members,the core members are the main members of sharing and discussion,and the characteristics of cohesive subgroups are not obvious.When analyzing the characteristics of social networks in different periods,it is found that the community structure changes from multi-center to non-center,the network density shows a “valley” evolution.(2)Content analysis of learner interaction in online collaborative learning.Formulating a knowledge construction coding system based on content analysis,quantitative analysis of the frequency and ratio of interactive content various with time,to explore the evolution process of learner knowledge construction level and the relationship the change of social network structure with group knowledge construction in online collaborative.Based on the analysis,it is found that although there are many effective meaning units published by the learning group,but the overall knowledge construction level is low,and the published deep knowledge construction meaning units are few.When analyzing the characteristics of knowledge construction in different periods,it is found that the level of community knowledge construction has gradually shifted from shallow to deep,and the learners at the core position have a driving role in the shallow and middle-level knowledge construction,and the deep knowledge construction content is gradually approaching the cognitive network center.However,due to the lack of opinion leaders,the community has a low frequency of interaction when constructing deep knowledge,which leads to the community failing to achieve a good level of deep knowledge construction.(3)Correlation analysis of learner's interaction quality and academic achievement in online collaborative learning.Combining the network structure analysis and interactive content analysis of the community,explores the relationship between the interaction quality with learning achievement of learners in online collaborative learning.According to the analysis,the higher the learner's score,the more frequency of interaction with other learners in the discussion area,the more they promote the shallow and middle-level knowledge construction of the learning group.