Multi-modal integration in number sense acquisition

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Abstract/Contents

Abstract
Mathematical concepts usually have multiple representations. Even the simplest mathematical concepts, such as natural numbers, can be grounded in various ways. Different representations of natural numbers are supported by diverse sensorimotor modalities. How do children learn to integrate representations of numbers from different modalities like visual, verbal, motion and gestures? In fact, this flexible mapping between different representations of natural numbers is an important component in numeric knowledge development, such as counting number of objects in a set (mapping cardinality to number word), naming an Arabic numeral (mapping written number symbols to verbal number words), number line estimation (mapping number words to positions on a number line), etc. In this PhD work, we systematically answer this question by building neural network models that simulate the learning procedure underlying diverse numeric processing tasks and thus account for multi-modal integration in number sense acquisition. It explains why symbolic numbers demonstrate similar properties as non-symbolic numbers, why training children on non-symbolic number arithmetic results in improvement on symbolic arithmetic and how they learn to selectively attend to different aspects of a number and processing numbers according to different instructions. Furthermore, we apply our model to a situated learning scenario, the number board game (e.g., Siegler and Ramani (2008)). We use our model to explain why playing the number board game leads to improvement in various basic number-related tasks, including numeral identification, magnitude comparison, counting, number line estimation, etc., and how such cross-task transfer happens. Our model provides a unified framework that simulates a diverse set of numeric processing tasks. Overall, it offers computational accounts for various empirical findings in the number cognition literature and deepens our understanding of the underlying mechanism in number sense acquisition.

Description

Type of resource text
Form electronic resource; remote; computer; online resource
Extent 1 online resource.
Place California
Place [Stanford, California]
Publisher [Stanford University]
Copyright date 2020; ©2020
Publication date 2020; 2020
Issuance monographic
Language English

Creators/Contributors

Author Yuan, Xuefei
Associated with Stanford University, Department of Psychology

Subjects

Genre Theses
Genre Text

Bibliographic information

Statement of responsibility Arianna Xuefei Yuan.
Note Submitted to the Department of Psychology.
Thesis Thesis Ph.D. Stanford University 2020.
Location electronic resource

Access conditions

Copyright
© 2020 by Xuefei Yuan
License
This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).

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