The group dynamics activation of online learning communities can help promote deep connectivity and knowledge innovation among learners from diverse and complex backgrounds.By mining and integrating the quantitative indicators of learners,concepts and topics in complex networks,the group dynamics activation mechanism is constructed,and then the ideas and suggestions for the group interaction and sustainable development of online learning communities are provided.Based on the multiplexed network and multi-dimensional multi-plex network analysis method,a four-layer relationship network model of social interaction,cognitive co-occurrence,concept association and topic association was constructed,and a group dynamic activation mechanism including learning peers,learning resources and learning topic recommendation strategies was designed.Taking a connectivism online course named cMOOC 5.0 as the application scenario,the ef-fectiveness of the multi-layer network model applied to the online learning community was verified,and the specific activation mechanism of group dynamics was proposed according to the modeling results:the network recommends learning peers based on social interaction and cognitive co-occurrence to strengthen group cohesion,recommends learning resources based on concept association network to improve group driving force,and recommends learning topics based on concept association and topic association network to reduce group dissipation.The research value of multi-layer network modeling is extended from the learning law mining at the micro level to the teaching intervention design at the meso-level.
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