.png){kind=icon}
返回
Dimensions in data: testing psychological models using state-trace analysis
.png){kind=icon}
PRE
AI
DOI：10.1016/j.tics.2008.04.009.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Cognitive science is replete with fertile and forceful debates about the need for one or moire underlying mental processes or systems to explain empirical observations. Such debates can be found in many areas, including learning, memory, categorization, reasoning and decision-making. Multiple-process models are often advanced on the basis of dissociations in data. We argue and illustrate that using dissociation logic to draw conclusions about the dimensionality of data is flawed. We propose that a more widespread adoption of 'state-trace analysis' - an approach that overcomes these flaws could lead to a re-evaluation of the need for multiple-process models and to a re-appraisal of how these models should be formulated and tested.
Keyword:
INFERENCE
TASK
RECOLLECTION
FAMILIARITY
JUDGMENTS
SYSTEMS
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
17.2
论文数:
3.6K
被引数:
3.5W
机构
引用论文
.png){kind=icon}
分享收藏
分享收藏
查看更多内容