Number gestures predict learning of number words

Finger counting to relieve working memory in children with developmental coordination disorder: Insights from behavioral and three-dimensional motion analyses

A limited number of studies have attempted to understand how motor deficits affect numerical abilities in children with developmental coordination disorder (DCD). The purpose of this study was to explore the functionality of finger-counting (FC) in children with DCD. The participants, 15 children with DCD and 15 typically developing (TD) children matched on school level and fluid reasoning abilities, were asked to use FC to solve an ordinal task with high working memory (WM) load. Behavioral measures supplemented with biomechanical measures, from three-dimensional motion analysis synchronized to a voice recording were used to assess children's performance and FC functionality (total duration, inter-finger [IF] transition, IF variance, finger/voice synchronization, and automatization of FC movements). Children with DCD were less accurate than TD children in using FC to solve ordinal problems with high WM load. This group difference could not be accounted for by poor FC skills given that FC movement turned out to be as functional in children with DCD as in their TD peers. When added to the model as a covariate, WM captured a greater proportion of intergroup variability than manual dexterity, further suggesting that their difficulties would be better accounted for by limited WM resources than by fine motor skills.

Exploring Individual Differences: A Case for Measuring Children's Spontaneous Gesture Production as a Predictor of Learning From Gesture Instruction

Decades of research have established that learners benefit when instruction includes hand gestures. This benefit is seen when learners watch an instructor gesture, as well as when they are taught or encouraged to gesture themselves. However, there is substantial individual variability with respect to this phenomenon-not all individuals benefit equally from gesture instruction. In the current paper, we explore the sources of this variability. First, we review the existing research on individual differences that do or do not predict learning from gesture instruction, including differences that are either context-dependent (linked to the particular task at hand) or context-independent (linked to the learner across multiple tasks). Next, we focus on one understudied measure of individual difference: the learner's own spontaneous gesture rate. We present data showing rates of "non-gesturers" across a number of studies and we provide theoretical motivation for why this is a fruitful area for future research. We end by suggesting ways in which research on individual differences will help gesture researchers to further refine existing theories and develop specific predictions about targeted gesture intervention for all kinds of learners.

Multimodality matters in numerical communication

Modern society depends on numerical information, which must be communicated accurately and effectively. Numerical communication is accomplished in different modalities-speech, writing, sign, gesture, graphs, and in naturally occurring settings it almost always involves more than one modality at once. Yet the modalities of numerical communication are often studied in isolation. Here we argue that, to understand and improve numerical communication, we must take seriously this multimodality. We first discuss each modality on its own terms, identifying their commonalities and differences. We then argue that numerical communication is shaped critically by interactions among modalities. We boil down these interactions to four types: one modality can amplify the message of another; it can direct attention to content from another modality (e.g., using a gesture to guide attention to a relevant aspect of a graph); it can explain another modality (e.g., verbally explaining the meaning of an axis in a graph); and it can reinterpret a modality (e.g., framing an upwards-oriented trend as a bad outcome). We conclude by discussing how a focus on multimodality raises entirely new research questions about numerical communication.

Hands on: Nonverbal communication in Native and non-Native American parent-child dyads during informal learning

Parent-child communication is a rich, multimodal process. Substantial research has documented the communicative strategies in certain (predominantly White) United States families, yet we know little about these communicative strategies in Native American families. The current study addresses that gap by documenting the verbal and nonverbal behaviors used by parents and their 4-year-old children (N = 39, 25 boys) across two communities: Menominee families (low to middle income) living on tribal lands in rural Wisconsin, and non-Native, primarily White families (middle income) living in an urban area. Dyads participated in a free-play forest-diorama task designed to elicit talk and play about the natural world. Children from both communities incorporated actions and gestures freely in their talk, emphasizing the importance of considering nonverbal behaviors when evaluating what children know. In sharp contrast to the stereotype that Native American children talk very little, Menominee children talked more than their non-Native counterparts, underlining the importance of taking into account cultural context in child assessments. For children and parents across both communities, gestures were more likely than actions to be related to the content of speech and were more likely than actions to be produced simultaneously with speech. This tight coupling between speech and gesture replicates and extends prior research with predominantly White (and adult) samples. These findings not only broaden our theories of communicative interaction and development, but also provide new evidence about the role of nonverbal behaviors in informal learning contexts. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Integrating Embodied Cognition and Information Processing: A Combined Model of the Role of Gesture in Children's Mathematical Environments

Children learn and use various strategies to solve math problems. One way children's math learning can be supported is through their use of and exposure to hand gestures. Children's self-produced gestures can reveal unique, math-relevant knowledge that is not contained in their speech. Additionally, these gestures can assist with their math learning and problem solving by supporting their cognitive processes, such as executive function. The gestures that children observe during math instructions are also linked to supporting cognition. Specifically, children are better able to learn, retain, and generalize knowledge about math when that information is presented within the gestures that accompany an instructor's speech. To date, no conceptual model provides an outline regarding how these gestures and the math environment are connected, nor how they may interact with children's underlying cognitive capacities such as their executive function. In this review, we propose a new model based on an integration of the information processing approach and theory of embodied cognition. We provide an in-depth review of the related literature and consider how prior research aligns with each link within the proposed model. Finally, we discuss the utility of the proposed model as it pertains to future research endeavors.

Give yourself a hand: The role of gesture and working memory in preschoolers' numerical knowledge

Hand gestures can be beneficial in math contexts to reduce the user's cognitive load by supporting domain-general abilities such as working memory. Although prior work has shown a strong relation between young children's early math performance and their general cognitive abilities, it is important to consider how children's working memory ability may relate to their use of spontaneous gesture as well as their math-specific abilities. The current study examined how preschool-aged children's gesture use and working memory relate to their performance on an age-appropriate math task. Head Start preschoolers (N = 81) were videotaped while completing a modified version of the Give-N task to measure their cardinality understanding. Children also completed a forward word span task and a computerized Corsi Block task to assess their working memory. The results showed that children's spontaneous gesture use and working memory were related to their performance on the cardinality task. However, children's gestures were not significantly related to working memory after controlling for age. Findings suggest that young children from low-income backgrounds use gestures during math contexts in similar ways to preschoolers from higher-income backgrounds.

Causal Effects of Parent Number Talk on Preschoolers' Number Knowledge

Individual differences in children's number knowledge arise early and are associated with variation in parents' number talk. However, there exists little experimental evidence of a causal link between parent number talk and children's number knowledge. Parent number talk was manipulated by creating picture books which parents were asked to read with their children every day for 4 weeks. N = 100 two- to four-year olds and their parents were randomly assigned to read either Small Number (1-3), Large Number (4-6), or Control (non-numerical) books. Small Number books were particularly effective in promoting number knowledge relative to the Control books. However, children who began the study further along in their number development also benefited from reading the Large Number Books with their parents.

Partial knowledge in the development of number word understanding

A common measure of number word understanding is the give-N task. Traditionally, to receive credit for understanding a number, N, children must understand that N does not apply to other set sizes (e.g. a child who gives three when asked for 'three' but also when asked for 'four' would not be credited with knowing 'three'). However, it is possible that children who correctly provide the set size directly above their knower level but also provide that number for other number words ('N + 1 givers') may be in a partial, transitional knowledge state. In an integrative analysis including 191 preschoolers, subset knowers who correctly gave N + 1 at pretest performed better at posttest than did those who did not correctly give N + 1. This performance was not reflective of 'full' knowledge of N + 1, as N + 1 givers performed worse than traditionally coded knowers of that set size on separate measures of number word understanding within a given timepoint. Results support the idea of graded representations (Munakata, Trends in Cognitive Sciences, 5, 309-315, 2001.) in number word development and suggest traditional approaches to coding the give-N task may not completely capture children's knowledge.

The Challenge of Modeling the Acquisition of Mathematical Concepts

As a full-blown research topic, numerical cognition is investigated by a variety of disciplines including cognitive science, developmental and educational psychology, linguistics, anthropology and, more recently, biology and neuroscience. However, despite the great progress achieved by such a broad and diversified scientific inquiry, we are still lacking a comprehensive theory that could explain how numerical concepts are learned by the human brain. In this perspective, I argue that computer simulation should have a primary role in filling this gap because it allows identifying the finer-grained computational mechanisms underlying complex behavior and cognition. Modeling efforts will be most effective if carried out at cross-disciplinary intersections, as attested by the recent success in simulating human cognition using techniques developed in the fields of artificial intelligence and machine learning. In this respect, deep learning models have provided valuable insights into our most basic quantification abilities, showing how numerosity perception could emerge in multi-layered neural networks that learn the statistical structure of their visual environment. Nevertheless, this modeling approach has not yet scaled to more sophisticated cognitive skills that are foundational to higher-level mathematical thinking, such as those involving the use of symbolic numbers and arithmetic principles. I will discuss promising directions to push deep learning into this uncharted territory. If successful, such endeavor would allow simulating the acquisition of numerical concepts in its full complexity, guiding empirical investigation on the richest soil and possibly offering far-reaching implications for educational practice.

Becoming human: human infants link language and cognition, but what about the other great apes?

Human language has no parallel elsewhere in the animal kingdom. It is unique not only for its structural complexity but also for its inextricable interface with core cognitive capacities such as object representation, object categorization and abstract rule learning. Here, we (i) review recent evidence documenting how (and how early) language interacts with these core cognitive capacities in the mind of the human infant, and (ii) consider whether this link exists in non-human great apes-our closest genealogical cousins. Research with human infants demonstrates that well before they begin to speak, infants have already forged a link between language and core cognitive capacities. Evident by just three months of age, this language-cognition link unfolds in a rich developmental cascade, with each advance providing the foundation for subsequent, more precise and more powerful links. This link supports our species' capacity to represent and convey abstract concepts and to communicate beyond the immediate here and now. By contrast, although the communication systems of great apes are sophisticated in their own right, there is no conclusive evidence that apes establish reference, convey information declaratively or pass down communicative devices via cultural transmission. Thus, the evidence currently available reinforces the uniqueness of human language and the power of its interface to cognition. This article is part of the theme issue 'What can animal communication teach us about human language?'