类别学习多重系统理论的研究与展望

The Multiple Systems Theory in Category Learning

介绍了国外学者为验证类别学习的多重系统理论所做的行为实验研究及主要结果，包括反馈训练、延迟反馈、反应位置、间断的类别刺激分布等因素对信息整合的类别学习的影响，和数字Stroop任务、序列记忆扫描任务、类别数量等因素对基于规则的类别学习的影响；同时，作者指出了实验中没有很好地解决两种类别结构之间的难度差异等问题，并提出了今后需要进一步研究的课题。

The multiple systems theory in category learning was introduced in this paper. A set of experiments for the theory were conducted by the multiple systems theorists. The results showed that feedback practices， delayed feedback， the location of the response and discontinuous categories effected on information-integration category learning but not on rule-based category learning， whereas the simultaneous performance of a numerical Stroop task， a sequential memory scanning task and categories’ number impacted rule-based category learning but not information-integration category learning. Basing on the analysis of the prior researches， the authors proposed some issues about difficulties and differences between the category structures that had been not solved and some topics should be studied further.