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…

Interpreting a seemingly simple function word like "or," "behind," or "more" can require logical, numerical, and relational reasoning. How are such words learned by children? Prior acquisition theories have often relied on positing a foundation of innate knowledge. Yet recent neural-network-based visual question…

We present a visual world eye-tracking study on Tseltal (a Mayan language) and investigate whether verbal information can be used to anticipate an upcoming referent. Basic word order in transitive sentences in Tseltal is Verb--Object--Subject (VOS). The verb is usually encountered first, making argument structure and syntactic information…

In recent years, a multitude of datasets of human-human conversations has been released for the main purpose of training conversational agents based on data-hungry artificial neural networks. In this paper, we argue that datasets of this sort represent a useful and underexplored source to validate, complement, and enhance cognitive studies on…

Gestures--hand movements that accompany speech and express ideas--can help children learn how to solve problems, flexibly generalize learning to novel problem-solving contexts, and retain what they have learned. But does it matter who is doing the gesturing? We know that producing gesture leads to better comprehension of a message than watching…

Euclidean geometry has formed the foundation of architecture, science, and technology for millennia, yet the development of human's intuitive reasoning about Euclidean geometry is not well understood. The present study explores the cognitive processes and representations that support the development of humans' intuitive reasoning about Euclidean…

In order to learn the mappings from words to referents, children must integrate co-occurrence information across individually ambiguous pairs of scenes and utterances, a challenge known as cross-situational word learning. In machine learning, recent multimodal neural networks have been shown to learn meaningful visual-linguistic mappings from…

Communication is a multimodal phenomenon. The cognitive mechanisms supporting it are still understudied. We explored a natural dataset of academic lectures to determine how communication modalities are used and coordinated during the presentation of complex information. Using automated and semi-automated techniques, we extracted and analyzed, from…

Visual representations are prevalent in STEM instruction. To benefit from visuals, students need representational competencies that enable them to see meaningful information. Most research has focused on explicit conceptual representational competencies, but implicit perceptual competencies might also allow students to efficiently see meaningful…