EAGER: Societies as learning communities: building the foundations for an empirical approach to the formation of collective memories

Princeton University, Princeton NJ

Investigators

Abstract

The overarching goal of the proposed work is to conduct proof-of-concept studies for how processes associated with individual learning can contribute to understanding the dynamics associated with the acquisition and maintenance of collective memories in communities/groups. These memories serve as a foundation on which individuals base their identities, beliefs, and behaviors. Despite their importance, there is limited experimental research into how collective memories are formed because of conceptual and technical challenges. First, these memories are dynamically changed in interactions among individuals, which makes their measurement complex. Second, real-world communities are typically larger than the small groups one could study in lab settings. In this project, investigator Alin Coman and his research team, from Princeton University, aim to build the foundation for the empirical exploration of the formation of collective memories in lab-created networked communities. They will build on psychological research on learning according to which once information is encoded, its memory is not sealed; rather, it experiences a transformation that involves a multitude of processes underlying learning, including strengthening, suppression, differentiation, and decay. In doing so, the project will contribute to the basic science of learning by providing an experimental framework that bridges between well-established cognitive mechanisms associated with learning at an individual level and large-scale social outcomes at a community level (i.e., collective memory). Ultimately, the findings will reveal how learning principles widely explored in psychology attenuate and facilitate the formation of collective memories. The advances that will be made from this project will be of interest to public health officials interested in disseminating accurate information to the public, to educators who aim to maximize knowledge acquisition in their classrooms, and to organizations interested in facilitating optimal coordination by strategically impacting the degree of information sharing among its members. This project uses insights from cognitive psychology, social psychology, and network science to explore the formation of collective memories in lab-created communities. It weaves together two strands of relevant research: (1) experimentally-based psychological research on the effect of communication on learning and memory and (2) studies of the propagation of influence through social networks. This cross-disciplinary fertilization is made possible by integrating relevant research at different levels of analysis: linking individual cognition and memory, then establishing how dyadic-level interaction changes memory representations, and then investigating how these dyadic-level effects propagate through social networks. Lab-created communities of 20 members will be assembled in which individuals will interact with one another according to a sequence of networked conversations. These free-flowing interactions will occur in a computer-mediated fashion in SoPHIE (Software Platform for Human Interaction Experiments), a software platform with features developed by the PI for the purposes of this research program. The focus will be on how conversations: (a) strengthen and induce forgetting in pre-existing individual memories of community members and (b) how they facilitate the learning of new information. Analyses will reveal how memory updating following conversational remembering circumscribes the formation of collective memories across the community. This research program constitutes a meaningful shift in how interdisciplinary approaches offer a bridge between individual-level cognitive phenomena and large-scale social outcomes. It would speak to cognitive scientists interested in exploring how the cognitive processes involved in learning have emergent properties at a collective level, and to sociologists who want to understand how cognition interacts with structural features of social networks to shape collective-level outcomes.