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Choosing the right solution approach: The crucial role of situational knowledge in electricity and magnetism

机译:选择正确的解决方案方法:情境知识在电力和磁力中的关键作用

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摘要

Novice problem solvers are rather sensitive to surface problem features, and they often resort to trial and error formula matching rather than identifying an appropriate solution approach. These observations have been interpreted to imply that novices structure their knowledge according to surface features rather than according to problem type categories. However, it may also be the case that novices do know problem types, but cannot map the problem at hand to a known type, because they fail to create a sufficiently well-elaborated problem representation. This study aims to distinguish between these explanations. In this study novice physics students at high and low levels of proficiency completed two problem-sorting tasks from the domain of electricity and magnetism, one with and one without elaboration support. Results confirm that these students do distinguish problem types in accordance with their required solution approaches, and that their problem-sorting performance improves with elaboration support. Therefore, it was concluded that their major difficulty lies in the process of matching concrete problems to a proper category. Within-group analysis revealed that the performance of proficient novices clearly improved with elaboration support, whereas the effect for less proficient novices remained inconclusive. The latter finding is explained from the less proficient novices' problem representations being too fragmented to integrate new information. These results suggest that, in order to promote schema-based problem solving, instruction in the domain of electricity and magnetism should be based not so much on restructuring the conceptual knowledge base but rather on enriching situational knowledge.
机译:新手问题求解器对表面问题特征相当敏感,他们经常诉诸试验和错误公式匹配而不是识别适当的解决方案方法。这些观察结果被解释为暗示,新的是根据表面特征而非根据问题类型类别构建其知识。但是,也可能是新手确实知道问题类型的情况,但不能将问题映射到已知类型,因为它们未能创建足够良好精细的问题表示。本研究旨在区分这些解释。在这项研究中,新手物理学生在高度和低的熟练程度上完成了来自电力和磁力领域的两个问题分类任务,一个与一个没有阐述支持。结果证实,这些学生确实根据所需的解决方案方法区分问题类型,并且它们的问题排序性能提高了阐述支持。因此,得出结论是,他们的主要困难在于将具体问题与适当类别匹配的过程中。在组内分析显示,精通新手的表现明显改善了阐述的支持,而富于熟练的新手的效果仍然不确定。后者发现是从不太熟练的新手的问题表现解释为整合以整合新信息的问题表示。这些结果表明,为了促进基于模式的问题解决,电力和磁领域的指示应该不是在重组概念知识库的情况下,而是基于丰富的情境知识。

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