Making Sense of Number, Bit-by-Bit- [electronic resource]
Making Sense of Number, Bit-by-Bit- [electronic resource]
상세정보
- 자료유형
- 학위논문파일 국외
- 최종처리일시
- 20240214095909
- ISBN
- 9798380620611
- DDC
- 153
- 서명/저자
- Making Sense of Number, Bit-by-Bit - [electronic resource]
- 발행사항
- [S.l.]: : University of California, Berkeley., 2021
- 발행사항
- Ann Arbor : : ProQuest Dissertations & Theses,, 2021
- 형태사항
- 1 online resource(122 p.)
- 주기사항
- Source: Dissertations Abstracts International, Volume: 85-04, Section: A.
- 주기사항
- Advisor: Piantadosi, Steven T.
- 학위논문주기
- Thesis (Ph.D.)--University of California, Berkeley, 2021.
- 사용제한주기
- This item must not be sold to any third party vendors.
- 초록/해제
- 요약Numerosity perception has been studied for at least 150 years and its psychophysics have been well characterized by experimental work. However, the origins of many of its key properties remain obscure. For instance, people estimate the numerosity of small sets (up to four) much more rapidly and accurately than larger sets; people tend to underestimate larger numerosities; estimation precision and accuracy increase with exposure duration. Standard models of numerical estimation do not account for these wide ranging phenomena, with large number estimation typically characterized as a draw from Gaussian(n, w · n) where w is a person's "Weber fraction," and exact small number perception characterized separately, the result of an independent object-file system. Furthermore, the inherently perceptual nature of estimation is largely ignored in many accounts of individual differences, which are often considered evidence of disparities in innate mathematical cognition. In my dissertation, I present studies of human behavior and computational models aimed at clarifying the visual mechanisms underlying numerical estimation. Our findings help to understand, and unify, key properties of number psychophysics which have previously been explained in terms of independent mechanisms or with ad hoc modifications to existing theories. For instance, we show how the psychophysics of both small and large number estimation can be unified into a single framework with a common mechanistic origin, and in fact how myriad properties of both (including estimation precision, bias, effects of time) can be understood as downstream consequences of bounded-optimal perceptual inference.
- 일반주제명
- Cognitive psychology.
- 일반주제명
- Mathematics education.
- 키워드
- Eye-tracking
- 기타저자
- University of California, Berkeley Psychology
- 기본자료저록
- Dissertations Abstracts International. 85-04A.
- 기본자료저록
- Dissertation Abstract International
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
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■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a153
■1001 ▼aCheyette, Samuel J.
■24510▼aMaking Sense of Number, Bit-by-Bit▼h[electronic resource]
■260 ▼a[S.l.]:▼bUniversity of California, Berkeley. ▼c2021
■260 1▼aAnn Arbor :▼bProQuest Dissertations & Theses, ▼c2021
■300 ▼a1 online resource(122 p.)
■500 ▼aSource: Dissertations Abstracts International, Volume: 85-04, Section: A.
■500 ▼aAdvisor: Piantadosi, Steven T.
■5021 ▼aThesis (Ph.D.)--University of California, Berkeley, 2021.
■506 ▼aThis item must not be sold to any third party vendors.
■520 ▼aNumerosity perception has been studied for at least 150 years and its psychophysics have been well characterized by experimental work. However, the origins of many of its key properties remain obscure. For instance, people estimate the numerosity of small sets (up to four) much more rapidly and accurately than larger sets; people tend to underestimate larger numerosities; estimation precision and accuracy increase with exposure duration. Standard models of numerical estimation do not account for these wide ranging phenomena, with large number estimation typically characterized as a draw from Gaussian(n, w · n) where w is a person's "Weber fraction," and exact small number perception characterized separately, the result of an independent object-file system. Furthermore, the inherently perceptual nature of estimation is largely ignored in many accounts of individual differences, which are often considered evidence of disparities in innate mathematical cognition. In my dissertation, I present studies of human behavior and computational models aimed at clarifying the visual mechanisms underlying numerical estimation. Our findings help to understand, and unify, key properties of number psychophysics which have previously been explained in terms of independent mechanisms or with ad hoc modifications to existing theories. For instance, we show how the psychophysics of both small and large number estimation can be unified into a single framework with a common mechanistic origin, and in fact how myriad properties of both (including estimation precision, bias, effects of time) can be understood as downstream consequences of bounded-optimal perceptual inference.
■590 ▼aSchool code: 0028.
■650 4▼aCognitive psychology.
■650 4▼aMathematics education.
■650 4▼aDevelopmental psychology.
■653 ▼aCognitive modeling
■653 ▼aEye-tracking
■653 ▼aInformation theory
■653 ▼aNumerical cognition
■653 ▼aVisual perception
■690 ▼a0633
■690 ▼a0620
■690 ▼a0280
■71020▼aUniversity of California, Berkeley▼bPsychology.
■7730 ▼tDissertations Abstracts International▼g85-04A.
■773 ▼tDissertation Abstract International
■790 ▼a0028
■791 ▼aPh.D.
■792 ▼a2021
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T16931084▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
■980 ▼a202402▼f2024
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