当前概率类别学习中主要存在多系统和单系统两种观点之争,而持不同观点的研究者在其实验中分别采用了不同的线索位置呈现方式,因此本研究采用经典的天气预测任务通过操纵线索位置的呈现方式来进一步探讨其对概率类别学习的影响。本研究包括2个实验:实验1考察所有线索位置固定和随机对概率类别学习系统的影响;实验2通过单线索模式下线索位置固定考察概率类别学习的策略。结果发现,当所有线索的呈现位置固定时,概率类别学习是外显学习;而当所有线索的呈现位置随机时,概率类别学习是内隐学习;而当只在线索单独出现时固定其位置,概率类别学习仍是内隐学习。结果表明,线索位置的不同呈现方式会影响概率类别学习中外显和内隐学习系统的竞争,研究支持了多系统观点,且概率类别学习的主要策略可能是多线索策略而不是单模式策略。
There is a debate between the multiple systems opinion and the single system opinion in probabilistic category learning,and the experiments of researchers holding different opinions have adopted different ways of presenting the positions of the cues respectively.So using the classical weather prediction task,the current study manipulated the ways in which the positions of cues were presented to explore the influence that this had on probabilistic category learning.This study included two experiments.Experiment 1 investigated the learning systems by fixing and randomizing the positions of all the cues.Experiment 2 investigated the strategy through fixing the positions of the singleton cues.The results showed that when the positions of all cues were held constant,probabilistic category learning was an explicit learning process.However,when the positions of all cues were random,it was an implicit learning process.And when only the positions of the singleton cues were held constant,it was also an implicit learning process.These results indicate that the different ways of presenting the positions of the cues affect the competition between the explicit learning and implicit learning systems,which supports the multi-system opinion.Moreover,the main strategy in probabilistic category learning may be the multi-cue strategy rather than the singleton strategy.