Given the recent call to strengthen collaboration between researchers and relevant practitioners, we consider participatory design as a way to advance Cognitive Science. Building on examples from the Learning Sciences and Human-Computer Interaction, we (a) explore "what," "why," "who," "when," and…

Iconicity is a relationship of resemblance between the form and meaning of a sign. Compelling evidence from diverse areas of the cognitive sciences suggests that iconicity plays a pivotal role in the processing, memory, learning, and evolution of both spoken and signed language, indicating that iconicity is a general property of language. However,…

Metaphor generation is both a creative act and a means of learning. When learning a new concept, people often create a metaphor to connect the new concept to existing knowledge. Does the manner in which people generate a metaphor, via sudden insight (Aha! moment) or deliberate analysis, influence the quality of generation and subsequent learning…

How does the act of explaining influence learning? Prior work has studied effects of explaining through a predominantly proximal lens, measuring short-term outcomes or manipulations within lab settings. Here, we ask whether the benefits of explaining extend to academic performance over time. Specifically, does the quality and frequency of student…

The framework of "plateaus, dips, and leaps" shines light on periods when individuals may be inventing new methods of skilled performance. We begin with a review of the role "performance plateaus" have played in (a) experimental psychology, (b) human-computer interaction, and (c) cognitive science. We then reanalyze two classic…

Learning a novel environment involves integrating first-person perceptual and motoric experiences with developing knowledge about the overall structure of the surroundings. The present experiments provide insights into the parallel development of these egocentric and allocentric memories by intentionally conflicting body- and world-centered frames…

This article demonstrates the potential of using hierarchical Bayesian methods to relate models and data in the cognitive sciences. This is done using a worked example that considers an existing model of category representation, the Varying Abstraction Model (VAM), which attempts to infer the representations people use from their behavior in…