- Title
- Understanding the cognitive mechanisms behind numerical cognition
- Creator
- Garrett, Paul M.
- Relation
- University of Newcastle Research Higher Degree Thesis
- Resource Type
- thesis
- Date
- 2020
- Description
- Research Doctorate - Doctor of Philosophy (PhD)
- Description
- Quantities and numbers have shaped the collective course of human history, governing trade, science, mathematics, and warfare. The cognitive mechanisms that allow us to compare two quantities, or identify one numeral from another, are not well understood. In this thesis, I investigate the processes that govern numerical cognition. I present a series of investigations that identify how we combine information from two large quantities and two small quantities. Specifically, I identify the processing architecture (parallel vs serial) and workload capacity (efficiency) of these cognitive processing systems. I then extend this work with a simulation study to develop a new set of distributional signatures that can be used to identify mixtures of parallel and serial processing architectures. Finally, I engage in a cross-cultural investigation into the mental representations of numbers. By using confusion scores, I model the mental representations of Arabic, Thai, Chinese and dot numerals, in an English speaking and Chinese speaking cohort. This investigation shows how mental representations change with levels of expertise. This thesis develops new methods and analysis techniques, and provides new insight into the fundamental processes that govern numerical cognition.
- Subject
- numerical cognition; systems factorial technology; numerals; workload capacity; numerosity; quantities; numbers; processing architecture; multidimensional scaling; cross-cultural; Chinese numerals
- Identifier
- http://hdl.handle.net/1959.13/1418380
- Identifier
- uon:37342
- Rights
- Copyright 2020 Paul M. Garrett
- Language
- eng
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| Thumbnail | File | Description | Size | Format | |||
|---|---|---|---|---|---|---|---|
| View Details Download | ATTACHMENT01 | Thesis | 7 MB | Adobe Acrobat PDF | View Details Download | ||
| View Details Download | ATTACHMENT02 | Abstract | 212 KB | Adobe Acrobat PDF | View Details Download |