Grouping strategies change classroom collaboration
Classroom grouping is not a neutral logistical decision. Whether students self-select, work with friends, or are assigned to more exploratory groups changes the social network that learning depends on.
Recent work with Javier Pulgar and collaborators studies this problem in high school physics. The results point to a useful tension: familiar groups can increase stability, but excessive stability can reduce new collaboration and limit exposure to different sources of information. More exploratory grouping can create broader contact, but it needs pedagogical support so that the network actually helps learning.
For CRiSS-LAB, this connects network science with a practical teaching question: how should classrooms be organized so that students feel enough trust to work together and enough novelty to learn from different peers?
Cristian Candia
Associate Professor, Data Science Institute, School of Engineering, Universidad del Desarrollo, Chile. Head of CRiSS-LAB.
Cristian Candia studies how societies transform information into collective relevance through attention, memory, preferences, and coordination. His work combines computational social science, network science, AI, and large-scale behavioral data to understand how groups, institutions, and societies decide what matters.