Somatori Keita, Kunisato Yoshihiko
Department of Psychology, Graduate School of Letters, Senshu University, Kawasaki, Japan.
Department of Psychology, School of Human Sciences, Senshu University, Kawasaki, Japan.
Front Hum Neurosci. 2022 Apr 13;16:706538. doi: 10.3389/fnhum.2022.706538. eCollection 2022.
In prior research, signal detection theory (SDT) has been widely utilized to assess metacognitive ability. However, the SDT metacognitive model requires the use of a two-alternative forced-choice task, while confidence must also be measured discretely. In our model, participants' cognitive ability and their confidence in the cognitive task were used to estimate their metacognitive abilities. Therefore, in this study, a metacognitive model that can be applied to various cognitive tasks was developed. This model implements the item response theory (IRT) and -learning models to estimate cognitive ability; participants' metacognitive ability is defined as the discrepancy between their confidence in their cognitive ability and their actual cognitive ability. The entire procedure was divided into two experiments. In experiment 1, two different cognitive tasks were used to estimate metacognitive ability and to examine overall discriminative and convergent validity. Notably, the parameters representing metacognitive ability did not correlate with cognitive ability but were positively correlated between the two tasks. In experiment 2, we performed a similar analysis using a different task to test the replicability of experiment 1. The results for experiment 2 were replicated for discriminative and convergent validity, albeit with weak results. Our metacognitive model exhibited high interpretability and versatility.
在先前的研究中，信号检测理论（SDT）已被广泛用于评估元认知能力。然而，SDT元认知模型需要使用二选一的强制选择任务，同时信心也必须进行离散测量。在我们的模型中，参与者的认知能力以及他们对认知任务的信心被用来估计他们的元认知能力。因此，在本研究中，开发了一种可应用于各种认知任务的元认知模型。该模型采用项目反应理论（IRT）和学习模型来估计认知能力；参与者的元认知能力被定义为他们对自身认知能力的信心与实际认知能力之间的差异。整个过程分为两个实验。在实验1中，使用两种不同的认知任务来估计元认知能力，并检验总体区分效度和聚合效度。值得注意的是，代表元认知能力的参数与认知能力不相关，但在两项任务之间呈正相关。在实验2中，我们使用不同的任务进行了类似的分析，以测试实验1的可重复性。实验2的结果在区分效度和聚合效度方面得到了重复，尽管结果较弱。我们的元认知模型具有很高的可解释性和通用性。
