Exact Number Concepts Are Limited to the Verbal Count Range

Exploring Early Number Abilities With Multimodal Transformers

Early number skills represent critical milestones in children's cognitive development and are shaped over years of interacting with quantities and numerals in various contexts. Several connectionist computational models have attempted to emulate how certain number concepts may be learned, represented, and processed in the brain. However, these models mainly used highly simplified inputs and focused on limited tasks. We expand on previous work in two directions: First, we train a model end-to-end on video demonstrations in a synthetic environment with multimodal visual and language inputs. Second, we use a more holistic dataset of 35 tasks, covering enumeration, set comparisons, symbolic digits, and seriation. The order in which the model acquires tasks reflects input length and variability, and the resulting trajectories mostly fit with findings from educational psychology. The trained model also displays symbolic and non-symbolic size and distance effects. Using techniques from interpretability research, we investigate how our attention-based model integrates cross-modal representations and binds them into context-specific associative networks to solve different tasks. We compare models trained with and without symbolic inputs and find that the purely non-symbolic model employs more processing-intensive strategies to determine set size.

Dissociating language and thought in large language models

Large language models (LLMs) have come closest among all models to date to mastering human language, yet opinions about their linguistic and cognitive capabilities remain split. Here, we evaluate LLMs using a distinction between formal linguistic competence (knowledge of linguistic rules and patterns) and functional linguistic competence (understanding and using language in the world). We ground this distinction in human neuroscience, which has shown that formal and functional competence rely on different neural mechanisms. Although LLMs are surprisingly good at formal competence, their performance on functional competence tasks remains spotty and often requires specialized fine-tuning and/or coupling with external modules. We posit that models that use language in human-like ways would need to master both of these competence types, which, in turn, could require the emergence of separate mechanisms specialized for formal versus functional linguistic competence.

The algorithmic origins of counting

The study of how children learn numbers has yielded one of the most productive research programs in cognitive development, spanning empirical and computational methods, as well as nativist and empiricist philosophies. This paper provides a tutorial on how to think computationally about learning models in a domain like number, where learners take finite data and go far beyond what they directly observe or perceive. To illustrate, this paper then outlines a model which acquires a counting procedure using observations of sets and words, extending the proposal of Piantadosi et al. (2012). This new version of the model responds to several critiques of the original work and outlines an approach which is likely appropriate for acquiring further aspects of mathematics.

Is two cuter than one? number and relationship effects on the feeling of kawaii toward social robots

Kawaii, which is a Japanese word that means cute, lovely, and adorable, is an essential factor in promoting positive emotions in people. The characteristics of a target's appearance that induce such feelings of kawaii have been thoroughly investigated around the notion of Konrad Lorenz's famous baby schema. Such knowledge has been exploited to design the appearance of commercial products to increase their social acceptance and commercial appeal. However, the effects of the number of targets and showing their mutual relationships (like friendship) have not been investigated in the context of kawaii. Therefore, in this study, we conducted three web-based experiments and focused on how such factors contribute to feelings of kawaii toward social robots. In Experiment 1, the feelings of kawaii toward static images of targets were compared when they appeared alone or with another target: persons (twin boys/girls), non-human objects (cherries), and social robots. The results showed that the feeling of kawaii was stronger for two targets that displayed a mutual relationship (e.g., looking at each other and/or making physical contact) than for one target alone and for two-independent targets. In Experiment 2, these findings were replicated using video clips of robots. Two-related targets were rated as more kawaii than two-independent targets or a single target. These two experiments consistently show the advantage of multiple robots that display their mutual relationship for enhancing the viewer's feeling of kawaii. Experiment 3 examined the effect of the number of robots (from one to ten) and found that two robots induced the strongest feeling of kawaii. These results indicate that not only the physical characteristics of a target itself but also the number of targets and their perceived relationships affect feelings of kawaii.

Diverse mathematical knowledge among indigenous Amazonians

We investigate number and arithmetic learning among a Bolivian indigenous people, the Tsimane', for whom formal schooling is comparatively recent in history and variable in both extent and consistency. We first present a large-scale meta-analysis on child number development involving over 800 Tsimane' children. The results emphasize the impact of formal schooling: Children are only found to be full counters when they have attended school, suggesting the importance of cultural support for early mathematics. We then test especially remote Tsimane' communities and document the development of specialized arithmetical knowledge in the absence of direct formal education. Specifically, we describe individuals who succeed on arithmetic problems involving the number five-which has a distinct role in the local economy-even though they do not succeed on some lower numbers. Some of these participants can perform multiplication with fives at greater accuracy than addition by one. These results highlight the importance of cultural factors in early mathematics and suggest that psychological theories of number where quantities are derived from lower numbers via repeated addition (e.g., a successor function) are unlikely to explain the diversity of human mathematical ability.

Over-reliance on English hinders cognitive science

English is the dominant language in the study of human cognition and behavior: the individuals studied by cognitive scientists, as well as most of the scientists themselves, are frequently English speakers. However, English differs from other languages in ways that have consequences for the whole of the cognitive sciences, reaching far beyond the study of language itself. Here, we review an emerging body of evidence that highlights how the particular characteristics of English and the linguistic habits of English speakers bias the field by both warping research programs (e.g., overemphasizing features and mechanisms present in English over others) and overgeneralizing observations from English speakers' behaviors, brains, and cognition to our entire species. We propose mitigating strategies that could help avoid some of these pitfalls.

Mathematics anxiety in deaf, hard of hearing, and hearing college students

While mathematics anxiety (MA) has been widely researched in recent decades, this study addresses significant gaps: namely, research that explores the relationship between MA and self‐reported mathematics experiences; samples adults with a range of MA levels; and controls for general anxiety. Additionally, the study sampled deaf and hard of hearing (DHH) students, whose diverse life and educational experiences often differ from hearing students’. We investigated whether DHH students’ experiences with mathematics (i.e., parental behaviors, school environment, and mathematics feelings) and demographic variables (i.e., hearing status, age, and gender) predict their MA, and whether these relationships differ from those in hearing students. Self‐report questionnaires were completed by 296 DHH and hearing college students. Linear regression analyses controlling for general anxiety led to the following inference: DHH students who reported more positive attitudes toward mathematics and school environments demonstrated higher MA. Also, the relationships between mathematics feelings, parental behaviors, and MA differed between DHH and hearing students. Logistic regression analyses showed no contribution of MA to students’ likelihood of pursuing STEM degrees in either DHH or between DHH and hearing groups. Overall, this work breaks new ground in the study of MA in DHH students and challenges standard views of the relationships between MA and individual experiences.