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Misconceived Causal Explanations for Emergent Processes

机译:对紧急过程的误解的因果解释

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Studies exploring how students learn and understand science processes such as diffusion and natural selection typically find that students provide misconceived explanations of how the patterns of such processes arise (such as why giraffes' necks get longer over generations, or how ink dropped into water appears to "flow"). Instead of explaining the patterns of these processes as emerging from the collective interactions of all the agents (e.g., both the water and the ink molecules), students often explain the pattern as being caused by controlling agents with intentional goals, as well as express a variety of many other misconceived notions. In this article, we provide a hypothesis for what constitutes a misconceived explanation; why misconceived explanations are so prevalent, robust, and resistant to instruction; and offer one approach of how they may be overcome. In particular, we hypothesize that students misunderstand many science processes because they rely on a generalized version of narrative schemas and scripts (referred to here as a Direct-causal Schema) to interpret them. For science processes that are sequential and stage-like, such as cycles of moon, circulation of blood, stages of mitosis, and photosynthesis, a Direct-causal Schema is adequate for correct understanding. However, for science processes that are non-sequential (or emergent), such as diffusion, natural selection, osmosis, and heat flow, using a Direct Schema to understand these processes will lead to robust misconceptions. Instead, a different type of general schema may be required to interpret non-sequential processes, which we refer to as an Emergent-causal Schema. We propose that students lack this Emergent Schema and teaching it to them may help them learn and understand emergent kinds of science processes such as diffusion. Our study found that directly teaching students this Emergent Schema led to increased learning of the process of diffusion. This article presents a fine-grained characterization of each type of Schema, our instructional intervention, the successes we have achieved, and the lessons we have learned.
机译:研究探索学生如何学习和理解科学过程(例如扩散和自然选择)的研究通常发现,学生对这种过程的模式产生了错误的解释(例如,为什么长颈鹿的脖子长了几代人,或者为什么墨水掉进了水中“流”)。学生们没有解释这些过程的模式是从所有媒介(例如,水和墨水分子)的集体相互作用中产生的,而是经常解释该模式是由有目的的控制媒介所引起的,并表达了一个过程。许多其他误解的概念。在本文中,我们对构成误解的解释提供了假设。为什么误解的解释如此普遍,健壮并且难以指导;并提供一种解决方法。尤其是,我们假设学生会误解许多科学过程,因为他们依赖于叙述性图式和脚本(在这里称为直接因果图式)的广义版本来解释它们。对于月球周期,血液循环,有丝分裂阶段和光合作用等连续且类似阶段的科学过程,直接因果关系式足以正确理解。但是,对于非顺序的(或紧急的)科学过程,例如扩散,自然选择,渗透和热流,使用直接模式来理解这些过程将导致强烈的误解。取而代之的是,可能需要不同类型的通用模式来解释非顺序过程,我们将其称为“紧急原因模式”。我们建议学生缺乏这种新兴模式,并向他们教授这可能有助于他们学习和理解新兴的科学过程,例如扩散。我们的研究发现,直接向学生教授这种紧急模式可以增加对扩散过程的学习。本文对每种类型的Schema进行了细粒度的描述,我们的指导性干预,我们取得的成功以及我们所汲取的教训。

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