Person-centered cognition: The presence of people in a visual scene promotes relational reasoning

Simplifying social learning

Social learning is complex, but people often seem to navigate social environments with ease. This ability creates a puzzle for traditional accounts of reinforcement learning (RL) that assume people negotiate a tradeoff between easy-but-simple behavior (model-free learning) and complex-but-difficult behavior (e.g., model-based learning). We offer a theoretical framework for resolving this puzzle: although social environments are complex, people have social expertise that helps them behave flexibly with low cognitive cost. Specifically, by using familiar concepts instead of focusing on novel details, people can turn hard learning problems into simpler ones. This ability highlights social learning as a prototype for studying cognitive simplicity in the face of environmental complexity and identifies a role for conceptual knowledge in everyday reward learning.

Social Concepts Simplify Complex Reinforcement Learning

Humans often generalize rewarding experiences across abstract social roles. Theories of reward learning suggest that people generalize through model-based learning, but such learning is cognitively costly. Why do people seem to generalize across social roles with ease? Humans are social experts who easily recognize social roles that reflect familiar semantic concepts (e.g., "helper" or "teacher"). People may associate these roles with model-free reward (e.g., learning that helpers are rewarding), allowing them to generalize easily (e.g., interacting with novel individuals identified as helpers). In four online experiments with U.S. adults (N = 577), we found evidence that social concepts ease complex learning (people generalize more and at faster speed) and that people attach reward directly to abstract roles (they generalize even when roles are unrelated to task structure). These results demonstrate how familiar concepts allow complex behavior to emerge from simple strategies, highlighting social interaction as a prototype for studying cognitive ease in the face of environmental complexity.

Generating distant analogies facilitates relational integration: Intermediary role of relational mindset and cognitive load

Relational integration is essential for learning, working, and living, as we must encode enormous volumes of information and extract their relations to construct knowledge about the environment. Recent research hints that generating distant analogies can temporarily facilitate learners’ state-based relational integration. This study aimed to investigate the internal mechanism underlying the facilitation effect and preliminarily confirm its application in education. First, we adopted the classical n-term premise integration task (Experiment 1a) and the Latin Square Task (Experiment 1b) to explore the robustness of the facilitation effect. Then we employed an emerging multidimensional relational reasoning task to further explore the internal mechanism underlying this facilitation effect (Experiment 2). Finally, we verified the practical role of the facilitation effect in learning the interaction concept in statistics (Experiment 3). The results showed that generating distant analogies did facilitate students’ relational integration performance, both in classical cognitive tasks and in a practical learning task, and a relational mindset and cognitive load play an intermediary role in the facilitation, supporting the cognitive load theory. The results suggest that generating distant analogies can be a useful warm-up activity to assist educators in promoting students’ relational integration.