United States

Assessing language abilities in multilingual children is critical for identifying necessary support. The SPEAK project (German acronym for “Language assessment of multilingual children”) validates a comprehensive test battery for 4- to 8-year-olds in Germany. This study reports on data from 207 multilingual children with 50 first languages other than German.
The battery includes German versions of internationally established tools: Nonword Repetition Task (phonological complexity), Cross-Linguistic Lexical Task (vocabulary comprehension and production), and Sentence Repetition Task (grammar), alongside a parental questionnaire.
Results show that age strongly predicts task performance, with earlier exposure to German improving phonology, vocabulary and grammar. Parental education also consistently predicts outcomes. Suspected Developmental Language Disorder negatively affects receptive vocabulary and grammar. Findings highlight the complex interplay of factors in multilingual language development.

CogSci 2025

Language assessment for multilingual children in Germany - developmental factors, environmental influences, and individual differences

developmental analysis

phonology

language acquisition

morphology

syntax

The 45th Annual Meeting of the Cognitive Science Society will take place in Sydney, Australia as a modified hybrid conference. Presentations from the main-session room will be live-streamed every day for all events. This will include all invited talks and award sessions. Recordings of all CogSci 2023 sessions will be made available for on-demand viewing after the conference.<br>
The in-person component will be held at the International Convention Centre Sydney at Darling Harbour. The Conference will take place Wednesday July 26th – Saturday July 29th, 2023 (Wednesday, July 26th is the Workshops Day).

Join us!

<br>[**The Program at a Glance can be found here**](https://cognitivesciencesociety.org/wp-content/uploads/2023/07/COgSci-PAAG-V2.pdf)
<br>[**The Detailed Program can be found here**](https://online.fliphtml5.com/ebtyf/mswz/)
<br><br>

#### **CogSci 2023 Program Book**
<iframe style="width:700px;height:400px" src="https://online.fliphtml5.com/ebtyf/tzgk/"  seamless="seamless" scrolling="no" frameborder="0" allowtransparency="true" allowfullscreen="true" ></iframe>
<br>

CogSci 2023

The 45th Annual Meeting of the Cognitive Science Society presents the latest research across cognitive science and highlights the theme of Cognition in Context.

poster

### Welcome to CogSci Conference 2025!

The 47th Annual Meeting of the Cognitive Science Society was a hybrid meeting held in San Francisco. 

<div style="position:relative;padding-top:0;width:900px;height:500px;"><iframe style="position:absolute;border:none;width:100%;height:100%;left:0;top:0;" src="https://online.fliphtml5.com/ebtyf/amvr/"  seamless="seamless" scrolling="no" frameborder="0" allowtransparency="true" allowfullscreen="true" ></iframe></div>

#### 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. 
<br><br>
* **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.
<br><br>
* **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.
<br><br>

#### 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)**.
<br><br>


You need to log in with the email address you registered with. 

Login credentials were sent to you from Underline -  subject line "Welcome to the CogSci 2025 Conference". Please be sure to check your spam/promotional inbox  if you do not see an email confirmation right away.





Please log in to join this event.

To access the site, please register [**here**](https://cognitivesciencesociety.org/registration/).

If you are registered and feel like you are seeing this message by mistake, please make sure you are logged in with the same email that you registered with. 

Please register!

The 47th Annual Meeting of the Cognitive Science Society presents the latest research across cognitive science and highlights the theme of Cognition in Context.

Neural Network Models of Morphological Inflection (NNMIs) have deep relevance to cognitive science stemming from the central role that they played in the Past Tense Debate of the 1980s and 1990s. Critics of the connectionist approach to the mind frequently pointed to NNMIs’ shortcomings in the area of developmental realism: they argued that regardless of their ultimate accuracy, they failed to capture patterns of child language acquisition including developmental regressions and a propensity for over-regularization rather than irregularization. However, NNMIs have seen impressive improvement in the deep learning era of the 2010s and 2020s. Have modern NNMIs solved the old problems of developmental realism? We find that they have not. The persistence of these shortcomings suggests that they reflect “innate” characteristics of NNMIs as a class of learner, and that even substantial advancement in neural architectures and subsequent performance increases do not necessarily entail increased cognitive plausibility.

Some Innate Characteristics of Neural Models of Morphological Inflection

Face processing is widely regarded in cognitive science as the integration of individual features into a holistic percept. However, recent neuroscience research highlights a more nuanced interplay between holistic and featural mechanisms, with specific facial features receiving greater emphasis during early perception. Event-related potential studies reveal that the number and type of parafoveal features significantly influence neural response delays, yet the underlying mechanistic model remains unclear. This paper examines these phenomena through the lens of the predictive coding network, a biologically plausible alternative to traditional deep neural networks. Our findings show that predictive coding networks accurately simulate the influence of parafoveal features on neural response times while upholding the saliency hierarchy of facial features. These results provide a computational explanation for the observed neural delays and highlight the potential of predictive coding as a robust framework for understanding face perception in the human brain.

A Mechanistic Perspective of Face Perception Latency: Predictive Coding

Price expectations drive traders' buy, hold, and sell decisions. They are often estimated by surveying investors; however, verbal accounts may differ from latent expectations. In this paper, we propose how to infer traders' price expectations from trading data instead. We assume traders' goal is maximizing final earnings by sequentially buying, holding, or selling shares. Due to sequentiality, trading is represented as a Partially Observable Markov Decision Process solved with Deep Reinforcement Learning. This model follows an approximately optimal trading policy with respect to price paths used in training. Meanwhile, we assume traders choose optimal trading actions given their price expectations. Therefore, price paths characterized by trend and volatility parameters are assumed to approximate expectations. We then infer which values of these parameters produce a human-like trading policy. While this approach achieves a good model fit with worst-performing traders in an empirical study, our results are more ambiguous for top traders.

Inferring Traders' Price Expectations from Time Series Data with POMDPs

Can paradigmatic associations be implicitly formed through parallel contexts?

Humans can remember arrays or sequences of stimuli that exceed working memory limits in many domains, from auditory sequences to geometric shapes. This ability has been interpreted as evidence for language-like representations that compress stimuli into compact descriptions. We extend this evidence in the domain of geometry by showing that representations of geometric shapes are not only compressed but also syntactically structured. Experiment 1 shows that different representations can be induced for the same geometric shape, indicating structural representation. Experiment 2 shows that subparts of a shape are easier to recognize when they belong to the same subtree than whey do not, indicating hierarchical organization. Taken together, the results indicate that geometric shapes are encoded in representations that possess internal syntax, just like natural language sentences.

Constituency tests in human adults’ language of thought for geometry

Misinformation poses a growing challenge in society, particularly as people seem reluctant to revise discredited information. However, emerging research suggests that people’s persistence in believing discredited information is sometimes rational, with individuals applying their own assumptions in a consistent way. In this experimental study, we employ a political vignette with a false accusation to show that even in politically charged contexts, people can correct misinformation and return their beliefs to baseline. Our results demonstrate that participants' belief updating generally aligns with Bayesian predictions, although with a more conservative approach. With regards to source evaluation, participants were more likely to downgrade the reliability of an accuser’s claim when it conflicted with their political views but returned to their initial assessments after the correction. This suggests that while worldview can affect source evaluation at the individual level, this effect does not necessarily translate into a broader erosion of institutional credibility. This study enhances our understanding of how worldview influences belief revision and source evaluation, especially in politically sensitive contexts.

The Role of Worldview Congruence in Misinformation Correction: A Bayesian Approach to Belief Updating

Children’s understanding of privacy develops as they navigate both physical and digital spaces. This study examines how children aged 3- to 13- years-old conceptualize privacy through their drawings, analyzing data from the Privacy Illustrated dataset. We explored two key dimensions: regulation (mechanisms controlling access, such as doors) and content (what children consider private, such as bedrooms or intellectual property). Our findings suggest that as children get older, they are more likely to view privacy as something that can be actively managed using physical barriers and control mechanisms. In contrast, younger children often depicted privacy as simply being alone. Content-related depictions remained relatively stable across ages, though older children included more abstract ideas, such as digital privacy. This study provides a novel framework for examining privacy development, highlighting distinct but interrelated dimensions of privacy.

Drawing Privacy: How Children Conceptualize Regulation and Content Across Development

Recent work in Bayesian, agent-based modelling of scientific communities has employed the Bala-Goyal framework to study the mechanisms involved when industry influence applies the so-called 'Tobacco  Strategy' to undermine collective inquiry. Motivated by limitations of these models, we propose an alternative based on a recently introduced framework for normative argument exchange across networks. We implement representations of two distinct types of industry influence: `Obfuscating' influence directs inquiry to experiments with low expected value of information. `Misleading' influence filters private research and only communicates misleading signals from the world. We explored the impacts of both strategies on the polarization \& mean error of, and flow of information through, social networks of scientists via computer simulations. We conclude that even against highly optimistic background assumptions, and in a less simplified model of inquiry and argumentation, industry influence poses a plausible threat to collective deliberation.

Industry Influencing Collective Scientific Reasoning: A Bayesian, Agent-based Exploration

Why do large-scale field experiments in education often have muted effects? Drawing on system dynamics and self-regulated learning theory, we sought answer this question by simulating the behavior of self-regulated (discrepancy-reducing) learners over time affected by different types of educational interventions. We analyze three types of interventions: changing students’ learning rates (learning strategies), intercepts (prior knowledge or teaching effectiveness), and norms of study (achievement goals). We uncover situations where educational interventions can affect achievement in the short run, but typical cross-sectional analyses do not find a measurable effect in the long run. Results indicate that highly motivated, self-regulated learners may resist external interventions, particularly those targeting learning strategies or prior knowledge. In contrast, interventions show the greatest effect on achievement when students are under time constraints and struggling to achieve their desired performance. Ultimately, self-regulated learners may be the hardest to help, a phenomenon we call the "self-regulated learning paradox."

The self-regulated learning paradox: Or, one reason why educational interventions might fail

What factors of our learning experiences enable us to best acquire complex skills? Recent ideas from artificial intelligence point to two such factors: (1) a balance of real experience with simulated experience acquired during planning itself, and (2) appropriate diversity in training examples. To test whether these factors influence the development of human expertise, we analyzed data from 1,873 chess players on the online platform Lichess, each of whom played hundreds to thousands of games over months to years. We found that both the time spent planning before moves and the diversity of opening positions encountered predict skill improvement over time. These findings suggest that principles shaping the development of expertise in artificial intelligence systems may also apply to human learning.

Downloads

Next from CogSci 2025

Some Innate Characteristics of Neural Models of Morphological Inflection

Similar lecture

Effects of Accent Exposure on Monolingual and Bilingual Children’s Early Vocabulary Development

Stay up to date with the latest Underline news!

PRODUCT

COMPANY

RESOURCES