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A test of two processes: The effect of training on deductive and inductive reasoning.
Cognition ( IF 2.8 ) Pub Date : 2020-02-20 , DOI: 10.1016/j.cognition.2020.104223
Rachel G Stephens 1 , John C Dunn 2 , Brett K Hayes 3 , Michael L Kalish 4
Affiliation  

Dual-process theories posit that separate kinds of intuitive (Type 1) and reflective (Type 2) processes contribute to reasoning. Under this view, inductive judgments are more heavily influenced by Type 1 processing, and deductive judgments are more strongly influenced by Type 2 processing. Alternatively, single-process theories propose that both types of judgments are based on a common form of assessment. The competing accounts were respectively instantiated as two-dimensional and one-dimensional signal detection models, and their predictions were tested against specifically targeted novel data using signed difference analysis. In two experiments, participants evaluated valid and invalid arguments, under induction or deduction instructions. Arguments varied in believability and type of conditional argument structure. Additionally, we used logic training to strengthen Type 2 processing in deduction (Experiments 1 & 2) and belief training to strengthen Type 1 processing in induction (Experiment 2). The logic training successfully improved validity-discrimination, and differential effects on induction and deduction judgments were evident in Experiment 2. While such effects are consistent with popular dual-process accounts, crucially, a one-dimensional model successfully accounted for the results. We also demonstrate that the one-dimensional model is psychologically interpretable, with the model parameters varying sensibly across conditions. We argue that single-process accounts have been prematurely discounted, and formal modeling approaches are important for theoretical progress in the reasoning field.

中文翻译:

对两个过程的测试:训练对演绎推理和归纳推理的影响。

双重过程理论认为,将各种直观过程(类型1)和反思过程(类型2)分开有助于推理。在这种观点下,归纳判断受类型1处理的影响更大,而演绎判断受类型2处理的影响更大。或者,单过程理论建议两种类型的判断都基于通用的评估形式。竞争帐户分别实例化为二维和一维信号检测模型,并使用带符号差异分析针对特定目标的新颖数据测试了它们的预测。在两个实验中,参与者根据归纳法或演绎法评估了有效和无效的论据。参数的可信度和条件参数结构的类型各不相同。另外,我们使用逻辑训练来增强演绎中的第二类处理(实验1和2),并使用信念训练来增强归纳中的第一类处理(实验2)。逻辑训练成功地改善了有效性-区分度,并且在实验2中明显体现了对归纳和推论判断的不同效果。尽管这种效果与流行的双处理帐户一致,但至关重要的是,一维模型成功地解释了结果。我们还证明了一维模型在心理上是可以解释的,模型参数在各种情况下都可以合理地变化。我们认为单流程帐户已过早打折,而正式的建模方法对于推理领域的理论进展很重要。2)和信念训练,以加强归纳中的1类处理(实验2)。逻辑训练成功地改善了有效性-区分度,并且在实验2中明显体现了对归纳和推论判断的不同效果。尽管这种效果与流行的双处理帐户一致,但至关重要的是,一维模型成功地解释了结果。我们还证明了一维模型在心理上是可以解释的,模型参数在不同情况下会合理地变化。我们认为单流程帐户已过早打折,而正式的建模方法对于推理领域的理论进展很重要。2)和信念训练,以加强归纳中的1型处理(实验2)。逻辑训练成功地改善了有效性-区分度,并且在实验2中明显体现了对归纳和推论判断的不同效果。尽管这种效果与流行的双处理帐户一致,但至关重要的是,一维模型成功地解释了结果。我们还证明了一维模型在心理上是可以解释的,模型参数在各种情况下都可以合理地变化。我们认为单流程帐户已过早打折,而正式的建模方法对于推理领域的理论进展很重要。实验2中,对归纳法和演绎法的判断具有明显的差异和明显影响。尽管这种效果与流行的双处理方法一致,但至关重要的是,一维模型成功地解释了结果。我们还证明了一维模型在心理上是可以解释的,模型参数在各种情况下都可以合理地变化。我们认为单流程帐户已过早打折,而正式的建模方法对于推理领域的理论进展很重要。实验2中,对归纳法和演绎法的判断具有明显的差异和明显影响。尽管这种效果与流行的双处理方法一致,但至关重要的是,一维模型成功地解释了结果。我们还证明了一维模型在心理上是可以解释的,模型参数在各种情况下都可以合理地变化。我们认为单流程帐户已过早打折,而正式的建模方法对于推理领域的理论进展很重要。我们还证明了一维模型在心理上是可以解释的,模型参数在不同情况下会合理地变化。我们认为单流程帐户已过早打折,而正式的建模方法对于推理领域的理论进展很重要。我们还证明了一维模型在心理上是可以解释的,模型参数在不同情况下会合理地变化。我们认为单流程帐户已过早打折,而正式的建模方法对于推理领域的理论进展很重要。
更新日期:2020-02-21
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