Empowering the Construction of Education Power with the Learning Community:Based on the Analysis of Online Learner Relationship Networks
The building of learning communities contributes significantly to the realization of education power.Various collaborative and interactive behaviors of online learners in the community facilitate the formation of learner relationship networks.A deep analysis of these networks can uncover intrinsic characteristics of community learning.This study proposes to analyze the learner relationship networks from the perspective of community discovery.It starts by designing a novel method for discovering learning communities based on graph convolution networks and nonnegative matrix factorization,integrating information from the learner's relational network and textual content.It introduces four community feature measurement metrics for applications in read-world learner relationship networks.The results show that the proposed analysis method can effectively uncover interest-themed communities within the learner relationship networks.It also allows for the characterization of the community as a whole and individual member,providing the decision support to guide the online interaction and collaborative behaviors of learners.Finally,it develops an online learning community enabling strategy,comprising"building visual learning communities,facilitating knowledge sharing among communities,promoting interaction and cooperation between communities,and reflecting and iterating under the feedback of indicators".Through the strategy to enable the high-quality development of learning communities,with the combination of community new quality productivity to foster a learning community,which will boost the development of education powerhouse.
learner relationship networksnetwork analysislearning communitycommunity discoveryeducation power
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