The Relation between First-Order Performance and Metacognitive Judgments in Implicit Learning Research

内隐学习研究中一阶表现与元认知判断的关系

• 批准号: 415700880
• 负责人: Professorin Dr. Hilde Haider
• 金额: --
• 依托单位: Department Psychologie
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2018
• 资助国家: 德国
• 起止时间: 2017-12-31 至 2022-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/415700880?language=en
• 关键词: Relation; between; First; Order; Performance

How conscious awareness about a sequence develops in an implicit learning situation is an important but not yet solved question (e.g. Cleeremans, 2014; Scott & Dienes, 2008; Esser & Haider, submitted). Our former findings suggest that strengthening of implicitly acquired representations is not sufficient to explain the emergence of consciousness in an implicit learning situation. Rather, and in line with the current discussion in the field of consciousness concerning Higher-Order Thought theories, we assume that implicit knowledge is represented in terms of first-order representations whereas conscious representations presuppose the generation of higher-order thoughts or metacognitive representations. In the last years, the interaction between first-order and metacognitive representations triggered a lot of research in many different domains (cf. decision making, Fleming & Daw, 2017). The central still open question here is whether first-order and higher-order judgments rely on the same signals. Alternatively, it is conceivable that former experiences in similar situations additionally modulate the metacognitive representations.The proposal comprises two series of experiments. The first series is aimed to investigate which information is integrated into metacognitive judgments. We assume that while performing a current task, participants develop an increasingly more stable metacognitive model of the situation. This model not only includes information derived from the first-order performance but also experiences made in similar situations. The second goal of this series then is to examine how metacognitive models of a current task are modulated by recognizing a discrepancy between predicted and experienced metacognitive judgements (prediction error). Building on these findings, we then turn to the question how conscious awareness emerges in an implicit learning situation. We assume that a large metacognitive prediction error in conjunction with a stable metacognitive model leads to a reappraisal of the validity of the current metacognitive model. Instead of adjusting the current model on the basis of the prediction error, an explicit search process for a better fitting model is triggered, which can lead to conscious insight into the acquired implicit sequence knowledge. The goal of this second series of experiments is to investigate whether and how the size of the prediction error modulates the development of conscious knowledge about the underlying sequence. Overall, the proposal contributes to our understanding of metacognitive judgments. Contrary to the usual binary decision tasks, implicit learning paradigms allow to investigate how former learning experiences might modulate the metacognitive judgments. Furthermore, the proposal will also contribute to our understanding of the interaction between unconscious and conscious knowledge.

在内隐学习情境中，关于序列的意识如何发展是一个重要但尚未解决的问题(例如，Cleeremans，2014；Scott&Dienes，2008；Esser&Haider，提交)。我们以前的发现表明，内隐获得表征的强化不足以解释内隐学习情境中意识的出现。相反，与目前意识领域关于高阶思维理论的讨论一致，我们假设内隐知识是用一阶表征来表示的，而意识表征是以高阶思维或元认知表征的产生为前提的。近年来，一阶表征和元认知表征之间的相互作用引发了许多不同领域的研究。《决策》，Fleming&Daw，2017)。这里仍然悬而未决的核心问题是，一阶判断和更高阶判断是否依赖于相同的信号。或者，可以想象，以前在类似情境中的经历对元认知表征有额外的调节作用。第一个系列旨在调查哪些信息被整合到元认知判断中。我们假设，在执行当前任务的同时，参与者会发展出一种越来越稳定的情景元认知模型。该模型不仅包含了一阶性能的信息，而且还包含了类似情况下的经验。因此，本系列的第二个目标是研究当前任务的元认知模型是如何通过认识到预测的元认知判断和经验的元认知判断(预测误差)之间的差异来调节的。在这些发现的基础上，我们接着转向内隐学习环境中意识意识是如何出现的问题。我们假设一个较大的元认知预测误差与一个稳定的元认知模型相结合，会导致对当前元认知模型的有效性的重新评估。不是基于预测误差调整当前模型，而是触发显式搜索过程以寻找更好的拟合模型，这可以导致对所获得的隐含序列知识的有意识的洞察。第二系列实验的目标是调查预测误差的大小是否以及如何调节关于潜在序列的有意识知识的发展。总体而言，该建议有助于我们理解元认知判断。与通常的二元决策任务相反，内隐学习范式允许研究以前的学习经验如何调节元认知判断。此外，该提议还将有助于我们理解无意识知识和有意识知识之间的相互作用。