Kwantes Peter J, Neal Andrew, Kalish Michael
Defence Research & Development Canada and School of Psychology, University of Queensland, Australia.
Can J Exp Psychol. 2012 Jun;66(2):90-7. doi: 10.1037/a0026639.
In a function learning task, participants are taught the relationship between 2 variables, a predictor (e.g., the dosage of a drug) and a criterion (e.g., its effect on mood). Of particular interest in this article is the question of what information does a participant use to generate a response for test examples that fall outside the training region-so-called, extrapolation items. In this article, we test whether the presentation of training items has an impact on the pattern of responses for items requiring participants to extrapolate, and examine, whether the 2 dominant accounts of function learning (Population of Linear Experts [POLE]: Kalish, Lewandowsky, & Kruschke, 2004; and Extrapolation Association Model [EXAM]: DeLosh, Busemeyer, & McDaniel, 1997) can account for this effect. The results show that a manipulation of trial-to-trial changes in the relative magnitudes of the predictor and criterion does influence subsequent extrapolation, and neither POLE, nor EXAM, was able to account for this effect in their current forms. We demonstrate that a model that encodes information about the trial-to-trial changes in the predictor and criterion, and which subsequently uses this information to adjust the retrieved value of the criterion, can account for the effect.
在一项函数学习任务中，参与者要学习两个变量之间的关系，一个是预测变量（例如，药物剂量），另一个是标准变量（例如，其对情绪的影响）。本文特别感兴趣的问题是，参与者会使用什么信息来对落在训练区域之外的测试示例（即所谓的外推项目）生成反应。在本文中，我们测试训练项目的呈现是否会对要求参与者进行外推的项目的反应模式产生影响，并检验函数学习的两种主要理论解释（线性专家群体理论[POLE]：卡利什、莱万多夫斯基和克鲁施克，2004年；以及外推关联模型[EXAM]：德洛什、布西梅尔和麦克丹尼尔，1997年）是否能解释这种效应。结果表明，对预测变量和标准变量相对大小的逐次试验变化进行操纵确实会影响后续的外推，并且POLE理论和EXAM理论在其当前形式下都无法解释这种效应。我们证明，一个对预测变量和标准变量的逐次试验变化进行信息编码，并随后使用该信息来调整检索到的标准变量值的模型，可以解释这种效应。
