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An Overview of Models for Response Times and Processes in Cognitive Tests

机译:认知测验中反应时间和过程的模型概述

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摘要

Response times (RTs) are a natural kind of data to investigate cognitive processes underlying cognitive test performance. We give an overview of modeling approaches and of findings obtained with these approaches. Four types of models are discussed: response time models (RT as the sole dependent variable), joint models (RT together with other variables as dependent variable), local dependency models (with remaining dependencies between RT and accuracy), and response time as covariate models (RT as independent variable). The evidence from these approaches is often not very informative about the specific kind of processes (other than problem solving, information accumulation, and rapid guessing), but the findings do suggest dual processing: automated processing (e.g., knowledge retrieval) vs. controlled processing (e.g., sequential reasoning steps), and alternative explanations for the same results exist. While it seems well-possible to differentiate rapid guessing from normal problem solving (which can be based on automated or controlled processing), further decompositions of response times are rarely made, although possible based on some of model approaches.
机译:响应时间(RTs)是研究调查认知测试表现基础的认知过程的自然数据。我们概述了建模方法以及使用这些方法获得的发现。讨论了四种类型的模型:响应时间模型(RT是唯一的因变量),联合模型(RT与其他变量一起作为因变量),局部依赖模型(在RT和准确性之间具有剩余依赖关系)和响应时间作为协变量模型(RT作为自变量)。这些方法的证据通常不能很好地说明特定类型的过程(除了解决问题,信息积累和快速猜测之外),但是发现确实建议双重处理:自动化处理(例如知识检索)与受控处理(例如,顺序推理步骤)以及对相同结果的替代解释。尽管将快速猜测与正常问题解决(可以基于自动或受控处理)区分开来似乎是很可能的,但是尽管基于某些模型方法是可能的,但响应时间的进一步分解却很少。

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