Investigating Design Cognition during Brainstorming Tasks with Freshmen and Senior Engineering Students using Functional Near Infrared Spectroscopy
Investigating Design Cognition during Brainstorming Tasks with Freshmen and Senior Engineering Students using Functional Near Infrared Spectroscopy
复制标题
使用功能近红外光谱法与新生和高年级工科学生一起调查头脑风暴任务中的设计认知
DOI：
10.18260/1-2--28584
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发表时间：
2017
影响因子：
6.1
通讯作者：
R. Panneton
中科院分区：
文献类型：
--
作者：
Tripp Shealy;J. Grohs;Mo Hu;D. Maczka;R. Panneton
设计认知包括问题的形成、解决方案的生成和设计过程策略的利用。在这里，我们使用功能性近红外光谱（fNIRS）测量认知负荷，以生成可持续性工程挑战的解决方案。fNIRS可用于在更自然的环境中研究大脑活动，同时还提供比EEG更好的空间分辨率和比fMRI更好的时间分辨率。因此，它为探索大脑活动与工程设计的关系提供了新的机会。虽然有文献描述了哪些大脑区域支持特定的认知功能，但对这些区域如何通过学习发展以及它们如何支持设计思维的了解要少得多。通过测量大一（n=14）和大四（n=9）工科学生在头脑风暴任务中的血流动力学反应，我们发现产生解决方案所需的认知激活存在显著差异（p<0.001）。与高年级学生相比，大一工程专业的学生在背外侧前额叶皮层（已知涉及工作记忆，认知灵活性，计划，抑制和抽象推理）中的激活程度要高出5倍。而老年人的运动前皮层（已知参与管理不确定性，控制行为和决策中的自我反思）的激活平均增加10倍。生成的溶液数量也具有显著性（p=0.032）。在头脑风暴活动中，大一学生平均产生了5.6个解决方案，而大四学生平均产生了4.1个。在许多方面，这项初步工作可以作为使用神经成像研究工程设计过程的概念证明。通过更好地理解这些过程，我们可以开始探索工程课程的具体内容，这些内容可能有助于学生管理工程设计问题固有的复杂性的能力。我们希望这项整合工程教育和神经科学的跨学科研究能够引发关于其他工程设计任务和设置的对话，其中fNIRS可以有效地用作新工具。
Design cognition includes the formulation of problems, the generation of solutions, and the utilization of design process strategies. Here, we measure the cognitive load to generate solutions to engineering challenges for sustainability using functional near-infrared spectroscopy (fNIRS). fNIRS can be used to study brain activity in more natural environments, while also providing better spatial resolution than EEG and better temporal resolution than fMRI. It therefore offers new opportunities for exploring how brain activity relates to engineering design. While there is literature describing which brain regions support particular cognitive functions, far less is known about how these are developed through learning and how they support design thinking. By measuring hemodynamic responses during brainstorming tasks with freshmen (n=14) and senior (n=9) engineering students we find a significant difference (p<0.001) in the cognitive activation required to generate solutions. Freshmen engineering students show 5 times greater activation in the dorsolateral prefrontal cortex (known to involve working memory, cognitive flexibility, planning, inhibition, and abstract reasoning) compared to seniors. While seniors show an average of 10 times increase in activation in the premotor cortex (known to be involved in the management of uncertainty, control of behavior, and self-reflection in decision making). The number of solutions generated was also significant (p=0.032). Freshmen generated 5.6 solutions on average during the brainstorming activity while seniors developed 4.1. In many ways, this initial work serves as a proof of concept in using neuroimaging to study the processes involved in engineering design. Through a better understanding of these processes, we can begin to explore specific elements of the engineering curriculum that may contribute to student ability to manage complexity inherent in engineering design problems. We hope this interdisciplinary study integrating engineering education and neuroscience generates conversation about other engineering design tasks and settings, in which, fNIRS can be effectively used as a new tool.