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A Mind with a Mind of Its Own: How Complexity Theory Can Inform Early Science Pedagogy

机译:心灵自己的思想:复杂性理论如何通知早期科学教育学

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In the current paper, we develop an approach to early science pedagogy that is based on insights about how complex adaptive systems function. Complexity approaches have an important advantage over traditional information-processing approaches: They anticipate the proverbial 'mind with a mind of its own' without having to postulate exclusively mental constructs. They also offer insights about key determinants of learning and effective pedagogy, again without postulating exclusively mental constructs. For complex adaptive systems, learning depends on the presence of sufficiently salient novelty (i.e., variability), and it depends on the presence of sufficiently salient repetitions or ordered patterns (i.e., stability). Science learning, therefore, requires science-relevant novelty and science-relevant patterns of order. Equipped with these insights, we address two challenges of early science pedagogy: (1) how to combine children's self-guided explorations with teachers' strategic interventions, and (2) how to minimize the chances of generating misconceptions about science. The answer lies in creating a learning context that maximizes science-relevant variability and science-relevant stability. If both aspects are abundantly available, a child's self-guided explorations are effective. Conversely, if either aspect is missing, efforts must be made to add them strategically to a child's experience. Adding science-relevant stability is particularly challenging, yet crucial to avoid science misconceptions.
机译:在目前的论文中,我们开发了一种早期科学教育学的方法,这是基于关于复杂自适应系统功能的洞察的洞察。复杂性方法具有与传统信息处理方法的重要优势:他们预计众所周知的“思想自己”,而无需假设精神构建。他们还提供了关于学习和有效教育的关键决定因素的见解,同样在没有专门的心理构建的情况下再次出现。对于复杂的自适应系统,学习取决于存在足够突出的新奇(即变异性),并且取决于存在足够突出的重复或有序图案(即,稳定性)。因此,科学学习需要科学相关的新奇和科学相关的订单模式。配备这些见解,我们解决了早期科学教育学的两个挑战:(1)如何将儿童的自我导游与教师战略干预措施结合起来,(​​2)如何最大限度地减少生成对科学误解的机会。答案在于创建一个学习背景,最大化科学相关的可变性和科学相关稳定性。如果两个方面都丰富了,那么孩子的自我导游探索是有效的。相反,如果缺少任何一个方面,必须努力将它们战略地添加到孩子的经验中。添加科学相关的稳定性尤其具有挑战性,但避免科学误解是至关重要的。

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