When networks learn to adapt: the plasticity of collaborative learners in a knowledge-building environment

Constructing adaptive social networks offers a promising approach to transforming traditional classroom structures and advancing teaching and learning reforms. This study explores how learners exhibit plasticity in adaptive settings, shedding light on the cognitive and behavioral mechanisms that support flexible collaboration. A three-stage, semester-long teaching intervention was designed to build adaptive social networks within a knowledge-building environment integrating online and offline activities. Participants were twenty-four master’s students majoring in educational technology enrolled in a required Learning Sciences course. Data sources included video recordings of students’ movement trajectories; records of online interactions and content of students’ online notes. Through video analysis, social network analysis and content analysis, we explored students’ plasticity characteristics across observable activities, collaborative structures and cognition. Findings revealed that students self-organized into diverse interaction configurations (intra-group, inter-group, and new-group), forming clustered-dispersed and concentric circular patterns. Collaboration was characterized by rotating leadership and exhibited a dynamic structural configuration. Students’ movement frequency was moderately correlated with the depth of explanation, but not with the depth of inquiry. The results suggest that collaboration in adaptive social networks is self-organizing and dynamically balanced, offering implications for instructional design that leverages students’ potential as knowledge workers.