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内隐与外显概率类别学习的分离及其认知机制
其他题名The Dissociation and Cognitive Mechanism of Implicit and Explicit Probabilistic Category Learning
李开云
学位类型硕士
导师付秋芳
2013-05
学位授予单位中国科学院研究生院
学位授予地点北京
学位专业心理学
关键词内隐学习 外显学习 概率类别学习 学习时间 工作记忆 意识知识
摘要类别学习是学习者通过不断的练习,学会对刺激分类的过程。日常生活中人们对某些刺激的分类并不是非此即彼,非A即B的,而是有时属于类别A有时属于类别B,但属于类别A和B的概率或权重不同。在这种不确定的分类情况下,人们逐渐学会对新事物或新情境做出较准确的概率性分类的过程,称为概率类别学习(Probabilistic catgory learning)。基于观察的学习和基于反馈的学习是概率类别学习的两种学习方式。研究者一般认为,基于观察的概率类别学习是通过外显的言语系统进行;而基于反馈的概率类别学习是基于内隐的程序学习或知觉学习系统,还是基于外显的言语学习系统尚存在很大争议。
本研究采用经典的天气预报任务范式,基于多重分类学习系统理论,设计完成了两个研究共5个实验,旨在考查内隐与外显概率类别学习的分离机制。研究一包含3个实验,通过改变总学习时间、刺激呈现时间、反馈时间,考察学习时间长短对内隐和外显概率类别学习的影响。结果发现,学习时间影响基于观察的概率类别学习但不影响基于反馈的概率类别学习,说明学习时间在基于观察和反馈的概率类别学习中具有不同的作用。研究二包括2个实验,通过加入不同的第二任务,探究工作记忆在内隐和外显概率类别学习中的作用。结果发现,言语工作记忆和视觉空间工作记忆都影响基于观察的概率类别学习过程,但只有视觉空间工作记忆任务干扰反馈的概率类别学习,说明不同的工作记忆任务在基于观察和反馈的概率类别学习中具有不同的作用。
综上所述,本研究结果发现,学习时间和工作记忆对基于观察和反馈的概率类别学习的影响不同,基于观察和反馈的概率类别学习可能分别依赖于外显的言语学习系统和内隐的程序学习或知觉学习系统。
其他摘要Category learning is the process to categorize objects and events into separate classes. In an uncertain world, a certain object is not be classified either this class or that class, but sometimes in category A, sometimes belongs to the category B, depending on the different categorical weights. Probabilistic category learning involves a gradual learning that holding the probabilistic associations between available information and an outcome of interest to some degree and integrating this information into a singular judgment. There are two versions of probabilistic category learning task, known as “observation-based” and “feedback-based” version. The “observation-based” version is claimed to recruit the declarative systems. However, it is still controversial whether the “feedback-based” version recruits the implicit, procedural or perception learning system, or explicit, verbal learning system.
The purpose of this study is to investigate the dissociative characteristics and the cognitive mechanism of implicit and explicit probabilistic category learning based on multiple-systems theory, using the weather prediction task. This thesis is constructed with four parts and five experiments totally. Study 1 included three experiments investigating the differences between implicit and explicit probabilistic category learning by manipulating the total training time, stimulus presentation time and feedback time. The results shows that training time has different roles in implicit and explicit probabilistic category learning, which impacts the learning performance and the acquisition of the consciousness of the “observation-based” version but not the “feedback-based” version. Study 2 was composed of two experiments, exploring the role of working memory on implicit and explicit probabilistic category learning by using a concurrent task methodology. We found that both concurrent verbal and visuospatial working memory task impaired the explicit, “observation-based” probabilistic category learning, and only the visuospatial task but not the verbal task damaged the performance of the “feedback-based” probabilistic category learning, suggesting the different role of working memory on implicit and explicit probabilistic category learning.
Based on the findings of the research, we proposed that the effects of training time and work memory on implicit and explicit probabilistic category learning are quite different and the “feedback-based” probabilistic category learning is a process of implicit and nonverbal procedural or perception learning, while the “observation-based” version is an explicit, verbal learning.
学科领域基础心理学
语种中文
文献类型学位论文
条目标识符http://ir.psych.ac.cn/handle/311026/19614
专题认知与发展心理学研究室
作者单位中国科学院心理研究所
推荐引用方式
GB/T 7714
李开云. 内隐与外显概率类别学习的分离及其认知机制[D]. 北京. 中国科学院研究生院,2013.
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