United States

High working memory capacity (WMC) is linked with stronger mathematical abilities; however, underlying mechanisms remain unclear. One theory suggests that problem solvers may offload information from their working memory in order to reduce cognitive load to solve problems more effectively. We investigated whether the use of offloading improved problem-solving skills. Ninety-three undergraduate students were administered a pre-test and WMC tasks. Participants were then split into two conditions, offloading or no-offloading, and were administered a post-test. ANOVA results indicated that while both groups improved, the offloading group showed greater improvement. Participants with lower WMC performed better when offloading, but there was no significant interaction between WMC and condition. Additionally, pre-test moderated the effect of offloading, suggesting students might benefit from offloading with greater prior knowledge. These findings have theoretical implications for mechanisms underlying the relationship between working memory and mathematics, and how to support students in classrooms.

CogSci 2025

Understanding working memory as a facilitator of math learning: Offloading as a potential strategy

### Welcome to CogSci Conference 2025!

The 47th Annual Meeting of the Cognitive Science Society was a hybrid meeting held in San Francisco. 

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#### About

The Cognitive Science Society brings together researchers from around the world who hold a common goal: understanding the nature of the human mind. The mission of the Society is to promote Cognitive Science as a discipline, and to foster scientific interchange among researchers in various areas of study, including Artificial Intelligence, Linguistics, Anthropology, Psychology, Neuroscience, Philosophy, and Education.

The Society is a non-profit professional organization and its activities include sponsoring an annual conference and publishing the journals Cognitive Science and TopiCS.

#### Our History 

* **Society Creation**<br>
The Society was incorporated as a 501(c)(3) non-profit professional organization in Massachusetts in 1979. The organizing committee included Roger Schank, Allan Collins, Donald Norman, and a number of other scholars from psychology, linguistics, computer science, and philosophy. 
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* **Conference Creation**<br>
The first conference on cognitive science was held at La Jolla, California in August, 1979, and has occurred annually since then. The proceedings of each conference are published, and those from most years are available through Lawrence Erlbaum Associates, Inc. The annual proceedings of the Cognitive Science Conference represent a major source of information on new work and new ideas in the scientific study of thinking. In 1990, the Society, with help from an anonymous donor, established the David Marr Prize for the best student paper at each annual meeting.
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* **Journal Creation**<br>
The Journal, Cognitive Science, began publication in 1976, and is now published by Wiley-Blackwell. The Executive Editor is currently Richard P. Cooper of Birkbeck, University of London, and there are 18 Associate Editors and a 30-member editorial board. It serves as the premier outlet for research reports that intersect two or more disciplines. Copyrights for articles published in the journal are held by the Society. The Governing Board of the Cognitive Science Society voted in late 2006 to found a new journal, Topics in Cognitive Science (topiCS). The Editor in Chief is Wayne Gray, Cognitive Science Department, Rensselaer Polytechnic Institute. The journal seeks to fill a niche not occupied by Cognitive Science Journal or other cognitive science journals. Membership in the Society includes a subscription to Cognitive Science and TopiCS. Copyrights for articles published in the journal are held by the Society.
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#### Code of Conduct

By attending the CogSci 2025 Conference, you are required to adhere to the society’s **[Code of Conduct](https://drive.google.com/file/d/1ChPuihLy6jE_BWqfO7J2KKgX35JW2zsM/view?usp=sharing)**.
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The 47th Annual Meeting of the Cognitive Science Society presents the latest research across cognitive science and highlights the theme of Cognition in Context.

poster

People's beliefs sometimes diverge after observing the same information, which has been interpreted as evidence of irrationality. This behaviour has been proposed to result from people's limited cognitive resources and motivated reasoning, but how belief revision differs across these explanations has not been formalized or compared to a rational norm. Further, while people may be biased relative to a normative ideal, they may still make optimal choices given their limited cognitive resources, or rationally balance the utility of holding accurate beliefs with the belief's intrinsic utility. Across two studies, we develop and test a unified computational account of belief polarization under these proposed mechanisms, showing that people's performance on a belief updating task best fits a limited-resource Bayesian model; external motivations may contribute to divergence (or convergence) by determining what pre-existing information people consider relevant to a situation, rather than by changing how people evaluate new information in isolation.

Resource-rational belief revision can mitigate as well as amplify polarization

What intuitions guide adults in extending the meanings of new words? Are these intuitions consistent with prelinguistic sensitivities operative in infancy? Across two preregistered experiments, adult participants saw simple grid-world environments in which characters moved in a “C” path efficiently (or not) to an object (or not). These events were labeled with a novel verb or noun. Participants were asked whether that word applied to new events varying in object-directedness, path, and efficiency. By contrast to infants’ focus on efficiency, adults instead focused on object-directedness and path, and they did so similarly for both verbs and nouns. Language might thus build on universal, prelinguistic assumptions of goal-directedness and efficiency to specify what goal an agent might have (e.g., object- vs. location-directed) as well as how an agent might achieve that goal (e.g., this vs. that kind of path), ultimately restricting the hypothesis space for action understanding and supporting learning.

Taking the C-nic Route: Object-Directedness and Path, Not Efficiency, Shape Adults' Word Extension

When speakers refer to objects in the world, they often overinform: provide their listener with redundant adjectival information. Contrary to classical theories in linguistics, recent theories have framed overinformativeness as an efficient means of grounding reference in perceptual information of high discriminability to facilitate listener comprehension. However, the generalisability of such theories is constrained by the methodological challenge associated with reliably manipulating the perceptual discriminability of naturalistic stimuli. Here, we overcome these methodological challenges, using methods from psychophysics to manipulate the perceptual discriminability of colour and material attributes in a reference-production experiment. We provide a robust validation of the view that overinformative reference is driven by speakers grounding expressions in attributes of high discriminability. However, we also find that colour information is privileged above and beyond such factors of discriminability.

Perceptual Discriminability Drives Overinformative Reference, But Colour Information is Special

Adults’ ability to detect online misinformation is improved by cognitive reflection and targeted instruction. Is the same true for children? We explored this question by asking elementary-school-aged children (n = 135) to judge the veracity of news stories, some real and some fake, and comparing their performance to scores on the Cognitive Reflection Test, Developmental version (CRT-D). Participants were also administered a tutorial encouraging them to scrutinize the plausibility of a story’s content or the credibility of its source. Children’s differentiation of fake news from real news was correlated with their CRT-D scores but did not improve with instruction. A comparison group of adults (n = 117) demonstrated similar findings with the exception that source-based instruction improved their news differentiation. These findings suggest that the ability to detect online misinformation is aided by cognitive reflection from the start but could be improved with knowledge of news sources.

Children's Differentiation of Fake News from Real News is Facilitated by Cognitive Reflection

Future theories of cognition need to encompass a wide range of human experiences, beyond those typically assessed in the laboratory. This study assessed how the experience of a prior artwork (prime) influenced the experience of the next artwork (target), and how this influence was affected by the presence or absence of event boundaries in a VR environment. We found that when primes were more emotionally intense, targets were rated lower in liking/beauty and emotional intensity. This influence was attenuated when the paintings were separated by an event boundary (separate rooms). Surprisingly, there was an effect of event boundaries on the processing of the prime paintings. An evaluation of additional data suggests that this is due to the mere presence of another painting in the same room, even before it is actually viewed. Thus, event structure can meaningfully impact the experience of viewing art.

Event Structure and the Experience of Viewing Art

Why do we say ''grasp an idea” but not ''hold an idea,” or ''small talk” but not ''little talk”? Although these word pairs share similar meanings, they differ in their tendency to be metaphorically extended. Prior research has focused on how well source concepts map onto target meanings to explain why some words are more readily extended to novel metaphorical contexts. However, much less attention has been paid to how the structural properties of a word’s semantic network contribute to its patterns of metaphorical extension. Using a large-scale dataset of semantic networks in English (De Deyne et al., 2019), we explored whether these structural properties predict selective extension in a metaphor rating study with English speakers, who were presented with Mandarin metaphorical expressions that lack direct English equivalents. Our findings revealed that English speakers systematically favor certain conceptual mappings from Chinese, suggesting that some metaphorical mappings may be universally recognized. However, when controlling for conceptual mappings by analyzing synonym pairs, we found that the structural features of a word’s semantic network significantly predict rates of extension. Specifically, words embedded in densely interconnected neighborhoods showed stronger resistance to extension, while words bridging diverse semantic communities demonstrate greater mutability.

Words with more diverse semantic networks are more readily extended to novel meanings

Humans make decisions collectively by combining individual and social learning. Individuals benefit from groups when individual exploration fails to accurately assess the environment, a phenomenon known as the “wisdom of crowds.” Previous studies indicate that self-organizing group dynamics can reduce suboptimal biases in noisy environments, particularly in fully connected groups. However, agents often have only partial information due to cognitive and physical constraints. To explore how diverse social network structures influence the collective dynamics of social learners, we integrate a decentralized network with a social reinforcement learning model in repeated two-armed bandit tasks. Our results suggest that: 1. Social learning in a sparse network outperforms asocial solo learning in highly uncertain tasks. 2. The phenomenon “less is more, and more is different” holds true only when agents strategically balance individual and social learning. 3. The group size effect on collective performance is significantly influenced by network structures.

Collective Behavior Emerging from Social Learning Strategies and Network Structures

Decades of research in cognitive science and AI have focused on compositionality as a hallmark property of the human mind. This focus can seem to frame the question as though we must classify systems as either compositional or idiomatic, cognitive or associative. In this talk, i describe a set of related but different empirical studies of how neural networks achieve, or fail to achieve, compositional behavior. I argue that these findings point to a middle ground in which traditional “symbolic” compositionality can be seen as a special case which is emergent—but nonetheless qualitatively different—from a more general associative mechanism characteristic of neural networks.

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