Guthrie Lisa G, Vallée-Tourangeau Frédéric, Vallée-Tourangeau Gaëlle, Howard Chelsea
Department of Psychology, Kingston University, Kingston upon Thames, KT1 2EE, UK,
Mem Cognit. 2015 Jul;43(5):723-35. doi: 10.3758/s13421-015-0504-8.
Outside the psychologist's laboratory, thinking proceeds on the basis of a great deal of interaction with artefacts that are recruited to augment problem-solving skills. The role of interactivity in problem solving was investigated using a river-crossing problem. In Experiment 1A, participants completed the same problem twice, once in a low interactivity condition, and once in a high interactivity condition (with order counterbalanced across participants). Learning, as gauged in terms of latency to completion, was much more pronounced when the high interactivity condition was experienced second. When participants first completed the task in the high interactivity condition, transfer to the low interactivity condition during the second attempt was limited; Experiment 1B replicated this pattern of results. Participants thus showed greater facility to transfer their experience of completing the problem from a low to a high interactivity condition. Experiment 2 was designed to determine the amount of learning in a low and high interactivity condition; in this experiment participants completed the problem twice, but level of interactivity was manipulated between subjects. Learning was evident in both the low and high interactivity groups, but latency per move was significantly faster in the high interactivity group, in both presentations. So-called problem isomorphs instantiated in different task ecologies draw upon different skills and abilities; a distributed cognition analysis may provide a fruitful perspective on learning and transfer.
在心理学家的实验室之外，思维是在与被用于增强解决问题能力的人工制品大量互动的基础上进行的。使用过河问题研究了互动性在解决问题中的作用。在实验1A中，参与者两次完成相同的问题，一次是在低互动性条件下，一次是在高互动性条件下（参与者的顺序是平衡的）。从完成任务的潜伏期来看，当第二次体验高互动性条件时，学习效果更为明显。当参与者首先在高互动性条件下完成任务时，第二次尝试时向低互动性条件的迁移是有限的；实验1B重复了这一结果模式。因此，参与者在将完成问题的经验从低互动性条件转移到高互动性条件时表现出更大的便利性。实验2旨在确定低互动性和高互动性条件下的学习量；在这个实验中，参与者两次完成问题，但互动性水平在不同受试者之间进行了操纵。低互动性组和高互动性组都有明显的学习，但在两种呈现方式中，高互动性组每一步的潜伏期都明显更快。在不同任务生态中实例化的所谓问题同构利用了不同的技能和能力；分布式认知分析可能为学习和迁移提供一个富有成效的视角。
