Donkin Chris, Newell Ben R, Kalish Mike, Dunn John C, Nosofsky Robert M
School of Psychology, University of New South Wales.
Department of Psychology, Syracuse University.
J Exp Psychol Learn Mem Cogn. 2015 Jul;41(4):933-48. doi: 10.1037/xlm0000083. Epub 2014 Dec 22.
The strength of conclusions about the adoption of different categorization strategies-and their implications for theories about the cognitive and neural bases of category learning-depend heavily on the techniques for identifying strategy use. We examine performance in an often-used "information-integration" category structure and demonstrate that strategy identification is affected markedly by the range of models under consideration, the type of data collected, and model-selection techniques. We use a set of 27 potential models that represent alternative rule-based and information-integration categorization strategies. Our experimental paradigm includes the presentation of nonreinforced transfer stimuli that improve one's ability to discriminate among the predictions of alternative models. Our model-selection techniques incorporate uncertainty in the identification of individuals as either rule-based or information-integration strategy users. Based on this analysis we identify 48% of participants as unequivocally using an information-integration strategy. However, adopting the standard practice of using a restricted set of models, restricted data, and ignoring the degree of support for a particular strategy, we would typically conclude that 89% of participants used an information-integration strategy. We discuss the implications of potentially erroneous strategy identification for the security of conclusions about the categorization capabilities of various participant and patient groups.
关于采用不同分类策略的结论强度及其对类别学习的认知和神经基础理论的影响，在很大程度上取决于识别策略使用的技术。我们研究了在一种常用的“信息整合”类别结构中的表现，并证明策略识别受到所考虑模型的范围、所收集数据的类型以及模型选择技术的显著影响。我们使用一组27个潜在模型，这些模型代表了基于规则和信息整合的替代分类策略。我们的实验范式包括呈现非强化转移刺激，以提高人们区分替代模型预测的能力。我们的模型选择技术在将个体识别为基于规则或信息整合策略使用者时纳入了不确定性。基于此分析，我们确定48%的参与者明确使用信息整合策略。然而，采用使用一组受限模型、受限数据并忽略对特定策略支持程度的标准做法，我们通常会得出89%的参与者使用信息整合策略的结论。我们讨论了潜在错误的策略识别对关于各种参与者和患者群体分类能力结论可靠性的影响。
