Learning through intermediate problems in creating cognitive models
Learning through intermediate problems in creating cognitive models
复制标题
通过创建认知模型的中间问题进行学习
DOI：
10.1080/10494820.2012.666668
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发表时间：
2014
影响因子：
5.4
通讯作者：
H. Terai
中科院分区：
文献类型：
--
作者：
K. Miwa;J. Morita;Ryuichi Nakaike;H. Terai
认知建模是认知科学中具有代表性的研究方法之一。人们认为，创建认知模型可以促进学习者的元认知活动，例如自我监控和反思自己的认知过程。此前的研究已经证实，这种元认知活动实际上可以促进学习效果。然而，通过在教育环境中创建认知模型来实现学习存在一些困难。为了克服这些困难，我们提出了一种创新的学习设计，“通过中间问题学习”，并开发了一个名为DoCoPro的基于网络的生产系统，可以在连接到互联网的环境中随时随地使用。我们开设了三门认知科学入门课程，参与者学习认知建模并使用我们的系统构建运行计算机模型。在第一和第二课中，参与者被要求构建解决滑轮问题的生产系统模型。他们还提出了最初的滑轮问题，随后他们自己的模型能够解决这些问题。这些产生的问题被分发给其他成员。参与者能够发现他们的认知模型中的不完整性，修改它们以消除不完整性，并在解决给定问题的同时改进他们的模型。通过成功创建复杂的模型，参与者获得了对学习领域更深入的了解。课堂实践证实了“通过中间问题学习”在构建学习创建认知模型的教育环境时的效用。在第三节课中，参与者使用 DoCoPro 构建了解决加法和减法问题的认知模型。此类问题解决背后的认知处理是自动化的，因此可能难以用语言表达和外化此类认知过程。调查后的调查显示，有证据表明参与者在监控自己的内部信息处理的同时实际上进行了元认知活动。
Cognitive modelling is one of the representative research methods in cognitive science. It is believed that creating cognitive models promotes learners’ meta-cognitive activities such as self-monitoring and reflecting on their own cognitive processing. Preceding studies have confirmed that such meta-cognitive activities actually promote learning effects. However, there are some difficulties in bringing about learning by creating cognitive models in an educational context. To overcome the difficulties, we propose an innovative learning design, ‘learning through intermediate problems’ and also developed a web-based production system called DoCoPro that can be used anywhere and anytime in an environment connected to the Internet. We performed three introductory cognitive science classes in which the participants learned cognitive modelling and constructed running computer models using our system. In the first and second classes, the participants were required to construct production system models that solve pulley problems. They also posed their original pulley problems that their own models were subsequently able to solve. These generated problems were distributed to the other members. The participants were able to find incompleteness in their cognitive models, revise them to remove the incompleteness, and improve their models while solving the given problems. The participants, by successfully creating sophisticated models, acquired a deeper knowledge of the learning domain. The class practices confirmed the utility of ‘learning through intermediate problems’ when constructing an educational environment for learning creating cognitive models. In the third class, the participants constructed cognitive models solving addition and subtraction problems using DoCoPro. The cognitive processing underlying such problem solving is automated, therefore it may be difficult to verbalize and externalize such cognitive processes. The post-questionnaire showed evidence that the participants actually performed meta-cognitive activities while monitoring their own internal information processing.
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