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The impact of system specifics on systems thinking

机译:系统细节对系统思维的影响

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Present and future social and ecological challenges are complex both to understand and to attempt to solve. To comprehend the complex systems underlying these issues, students need systems thinking skills. However, in science education, a uniform delineation of systems thinking across contexts has yet to be established. While there seems to be consensus on a number of key skills from a theoretical perspective, it remains uncertain whether it is possible to distinguish levels of systems thinking, and if so, how they would be determined. In this study, we investigated the impact of the specifics of a system on the skills and levels of systems thinking. We administered a 36-item multiple-choice test to 196 Grade 5 and 6 students. For our analysis, we followed a quantitative approach, applying a systems thinking model that incorporates the latest insights on the levels and skills of systems thinking in geography to the context of ecology. By following an Item Response Theory approach, we confirmed a set of systems thinking skills that are necessary to understand complex systems in ecology: identifying system organization, analyzing system behavior, and system modeling. We examined whether individual skill levels can be distinguished to determine whether a system's general principle or system-specific features cause difficulty for students. Our results indicate that system specifics, such as type of relation within ecosystems (e.g., predator-prey), appear to determine the formation of levels. Students struggled most with the difference between basic, direct cause-and-effect relationships and indirect effects. Once they understood the relevance of indirect relationships in moderately complex systems, a further increase in complexity caused little additional difficulty. Accordingly, we suggest that systems thinking should be examined from a variety of perspectives. To promote interdisciplinary learning, a systems thinking model that defines key commonalities across fields while leaving space for system specifics is needed.
机译:现在和未来的社会和生态挑战都很复杂,可以理解和尝试解决。要理解这些问题的复杂系统,学生需要系统思维技能。然而,在科学教育中,迄今尚未建立在语境上思考的系统统一划分。虽然从理论上的角度来看,似乎对许多关键技能有所共识,但它仍然不确定是否有可能区分系统思维的水平,如果是的话,他们将如何确定它们。在这项研究中,我们调查了系统细节对系统思维技能和水平的影响。我们向196年级和6名学生提供了36项多项选择测试。为了我们的分析,我们采用了定量方法,应用了一个系统思维模型,该模型融入了对地理学中思维的水平和技能的最新见解与生态学的背景。通过遵循项目响应理论方法,我们确认了一组系统思维技能,这些技能是理解生态学中的复杂系统所必需的:识别系统组织,分析系统行为和系统建模。我们检查了是否可以区分个别技能水平以确定系统的一般原则或系统特定功能是否对学生造成困难。我们的结果表明,系统细节,例如生态系统内的关系类型(例如,捕食者 - 猎物),似乎确定了水平的形成。学生最挣扎的基本,直接原因和效应关系与间接影响之间的差异。一旦他们理解间接关系在中等复杂系统中的关联关系,复杂性的进一步增加导致额外的额外难度。因此,我们建议应从各种角度检查系统思考。为了促进跨学科学习,需要一个系统思维模型,用于跨越字段的关键公共性,同时需要为系统细节留下空间。

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