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arXiv 2106.07765physics.ed-ph
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物理MajorsDuring问题解决中的自发图和自动图研究

Investigating Unprompted and Prompted Diagrams Generated by Physics MajorsDuring Problem Solving

Michael Vignal, Bethany R. Wilcox

摘要:

图表在物理学中无处不在,尤其是在物理教育和物理问题解决中。问题解决者可以生成图表来定位场景,组织信息,直接提取答案,或作为沟通工具。在这项研究中,我们采访了19名物理专业的本科生和研究生,要求他们解决18个多项选择物理问题-没有提示有关图表-然后六个类似于六个多项选择题的情况下的图形任务。通过比较自发生成和提示图,我们确定了不同的建模元素和功能,物理专业的行为对不同的目的(\textit{i.e.,}在不同的认知框架)。我们发现,不同的物理环境会影响绘制准确图表的重要性,并且队列之间(低年级本科生和研究生之间的\textit{e.g.})的差异似乎小于队列内的差异。我们还探讨了教学和研究的影响。

英文摘要:

Diagrams are ubiquitous in physics, especially in physics education and physics problem solving. Problem solvers may generate diagrams to orient to a scenario, to organize information, to directly extract an answer, or as a tool of communication. In this study, we interviewed 19 undergraduate and graduate physics majors, asking them to solve 18 multiple-choice physics problems -- with no prompting regarding diagrams -- and then six diagramming tasks of situations similar to six of the multiple-choice problems. By comparing spontaneously generated and prompted diagrams, we identify different diagramming elements and features used by physics majors acting towards different ends (\textit{i.e.,} in different epistemic frames). We found that different physical contexts impact how critical it is to draw an accurate diagram, and that the differences in diagramming between cohorts (\textit{e.g.}, between lower-division undergraduate and graduate students) seem to be smaller than the differences within a cohort. We also explore implications for teaching and research.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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