Unraveling Cognitive Processes Driving the Development of Optimized Category Learning and Decision-Making
Unraveling Cognitive Processes Driving the Development of Optimized Category Learning and Decision-Making
상세정보
- 자료유형
- 학위논문 서양
- 최종처리일시
- 20250211153132
- ISBN
- 9798346852759
- DDC
- 150
- 저자명
- Wan, Qianqian.
- 서명/저자
- Unraveling Cognitive Processes Driving the Development of Optimized Category Learning and Decision-Making
- 발행사항
- [Sl] : The Ohio State University, 2024
- 발행사항
- Ann Arbor : ProQuest Dissertations & Theses, 2024
- 형태사항
- 204 p
- 주기사항
- Source: Dissertations Abstracts International, Volume: 86-06, Section: B.
- 주기사항
- Advisor: Sloutsky, Vladimir M.
- 학위논문주기
- Thesis (Ph.D.)--The Ohio State University, 2024.
- 초록/해제
- 요약This dissertation investigates the developmental trajectory of cognitive mechanisms underlying category learning and decision-making, with a particular focus on the role of cognitive control, working memory, and metacognition. The research attempts to address how children's cognitive processes transition from reliance on simpler, more automatic to more complex, goal-directed strategies.Chapter 3 explores the influence of cognitive control, specifically inhibition failure, in category learning contexts. It was hypothesized that immature cognitive control drives children's distributed attention, resulting in compression-based learning. To test this hypothesis, we introduced a paradigm that substantially decreased cognitive control (i.e., filtering) demands. If immature cognitive control is the principal driver of distributed attention, reducing such demands should result in greater attentional selectivity. However, the experimental results did not support the immature cognitive control hypothesis, instead pointing toward working memory as a more critical factor. This led to the formulation of the working memory hypothesis -compression-based, not selection-based learning results from immature working memory that cannot provide reliable guidance for selective attention.Chapter 4 presents an adult study using a dual-task paradigm to manipulate working memory capacity and assess its impact on attention distribution during category learning. The findings that under working memory load, adults tend to distribute attention establish a causal link between working memory and attention distribution. They suggest that immature working memory, rather than cognitive control, is the primary driver of distributed attention and compression-based category learning in children.Chapter 5 shifts to a longitudinal study that tracks the development from uncertainty-driven to performance-optimizing decision-making, discussed within the framework of metacognitive development.The dissertation concludes by synthesizing these findings to argue that, in the absence of a fully developed working memory system and sufficient knowledge base, children's learning and decision-making rely heavily on novelty preference-a bottom-up strategy to manage uncertainty. These insights contribute to understanding the cognitive foundations of learning and decision-making during early development.
- 일반주제명
- Psychology
- 일반주제명
- Neurosciences
- 일반주제명
- Cognitive psychology
- 키워드
- Working memory
- 키워드
- Metacognition
- 기타저자
- The Ohio State University Psychology
- 기본자료저록
- Dissertations Abstracts International. 86-06B.
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
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■020 ▼a9798346852759
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■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a150
■1001 ▼aWan, Qianqian.
■24510▼aUnraveling Cognitive Processes Driving the Development of Optimized Category Learning and Decision-Making
■260 ▼a[Sl]▼bThe Ohio State University▼c2024
■260 1▼aAnn Arbor▼bProQuest Dissertations & Theses▼c2024
■300 ▼a204 p
■500 ▼aSource: Dissertations Abstracts International, Volume: 86-06, Section: B.
■500 ▼aAdvisor: Sloutsky, Vladimir M.
■5021 ▼aThesis (Ph.D.)--The Ohio State University, 2024.
■520 ▼aThis dissertation investigates the developmental trajectory of cognitive mechanisms underlying category learning and decision-making, with a particular focus on the role of cognitive control, working memory, and metacognition. The research attempts to address how children's cognitive processes transition from reliance on simpler, more automatic to more complex, goal-directed strategies.Chapter 3 explores the influence of cognitive control, specifically inhibition failure, in category learning contexts. It was hypothesized that immature cognitive control drives children's distributed attention, resulting in compression-based learning. To test this hypothesis, we introduced a paradigm that substantially decreased cognitive control (i.e., filtering) demands. If immature cognitive control is the principal driver of distributed attention, reducing such demands should result in greater attentional selectivity. However, the experimental results did not support the immature cognitive control hypothesis, instead pointing toward working memory as a more critical factor. This led to the formulation of the working memory hypothesis -compression-based, not selection-based learning results from immature working memory that cannot provide reliable guidance for selective attention.Chapter 4 presents an adult study using a dual-task paradigm to manipulate working memory capacity and assess its impact on attention distribution during category learning. The findings that under working memory load, adults tend to distribute attention establish a causal link between working memory and attention distribution. They suggest that immature working memory, rather than cognitive control, is the primary driver of distributed attention and compression-based category learning in children.Chapter 5 shifts to a longitudinal study that tracks the development from uncertainty-driven to performance-optimizing decision-making, discussed within the framework of metacognitive development.The dissertation concludes by synthesizing these findings to argue that, in the absence of a fully developed working memory system and sufficient knowledge base, children's learning and decision-making rely heavily on novelty preference-a bottom-up strategy to manage uncertainty. These insights contribute to understanding the cognitive foundations of learning and decision-making during early development.
■590 ▼aSchool code: 0168.
■650 4▼aPsychology
■650 4▼aNeurosciences
■650 4▼aCognitive psychology
■653 ▼aCognitive development
■653 ▼aCategory learning
■653 ▼aWorking memory
■653 ▼aAttentional guidance
■653 ▼aMetacognition
■690 ▼a0621
■690 ▼a0317
■690 ▼a0633
■71020▼aThe Ohio State University▼bPsychology.
■7730 ▼tDissertations Abstracts International▼g86-06B.
■790 ▼a0168
■791 ▼aPh.D.
■792 ▼a2024
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17165174▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
