Novick L R
University of California, Los Angeles.
J Exp Psychol Learn Mem Cogn. 1988 Jul;14(3):510-20. doi: 10.1037//0278-7393.14.3.510.
When we encounter a new problem, we are often reminded of similar problems solved earlier and may use the solution procedure from an old problem to solve a new one. Such analogical transfer, however, has been difficult to demonstrate empirically, even within a single experimental session. This article proposes a framework for conceptualizing analogical problem solving that can account for the conflicting findings in the literature. In addition, the framework leads to two predictions concerning the transfer behavior of experts and novices. These predictions concern both positive and negative transfer and are based on the different types of features included in the problem representations of experts and novices. First, when two problems share structural features but not surface features, spontaneous positive transfer should be more likely in experts than in novices. Second, when two problems share surface but not structural features, spontaneous negative transfer should be stronger for novices than for experts. These predictions were supported by the results of three experiments involving college students solving a complex arithmetic word problem.
当我们遇到一个新问题时，常常会想起之前解决过的类似问题，并可能运用旧问题的解决方法来解决新问题。然而，即便在单次实验过程中，这种类比迁移也很难通过实证来证明。本文提出了一个用于概念化类比问题解决的框架，该框架能够解释文献中相互矛盾的研究结果。此外，这一框架还产生了关于专家和新手迁移行为的两个预测。这些预测涉及正迁移和负迁移，且基于专家和新手问题表征中所包含的不同类型特征。首先，当两个问题共享结构特征但不共享表面特征时，专家比新手更有可能发生自发正迁移。其次，当两个问题共享表面特征但不共享结构特征时，新手比专家的自发负迁移更强。涉及大学生解决复杂算术应用题的三项实验结果支持了这些预测。
