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Quantifying two-dimensional and three-dimensional stereoscopic learning in anatomy using electroencephalography

机译:使用脑电图定量解剖学中的二维和三维立体学习

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Advances in computer visualization enabling both 2D and 3D representation have generated tools to aid perception of spatial relationships and provide a new forum for instructional design. A key knowledge gap is the lack of understanding of how the brain neurobiologically processes and learns from spatially presented content, and new quantitative variables are required to address this gap. The objective of this study was to apply quantitative neural measures derived from electroencephalography (EEG) to examine stereopsis in anatomy learning by comparing mean amplitude changes in N250 (related to object recognition) and reward positivity (related to responding to feedback) event related to potential components using a reinforcement-based learning paradigm. Health sciences students (n?=?61) learned to identify and localize neuroanatomical structures using 2D, 3D, or a combination of models while EEG and behavioral (accuracy) data were recorded. Participants learning using 3D models had a greater object recognition (N250 amplitude) compared to those who learned from 2D models. Based on neurological results, interleaved learning incorporating both 2D and 3D models provided an advantage in learning, retention, and transfer activities represented by decreased reward positivity amplitude. Behavioral data did not have the same sensitivity as neural data for distinguishing differences in learning with and without stereopsis in these learning activities. Measuring neural activity reveals new insights in applied settings for educators to consider when incorporating stereoscopic models in the design of learning interventions.
机译:计算机可视化的进步使得2D和3D表示都有生成的工具,以帮助对空间关系感知并提供一个新的教学设计论坛。关键知识缺口是缺乏对脑神经生物学过程和学习如何从空间呈现的内容中学习的理解,并且需要新的定量变量来解决这种差距。本研究的目的是通过比较N250(与对象识别有关)的平均幅度变化和奖励与潜在的潜在的情况(与响应于反馈)事件(响应于反馈)事件的平均幅度变化进行解剖学学习中源自脑电图(脑电图)来检查立体内的定量神经措施。组件使用基于加强的学习范式。健康科学学生(N?=?61)学会了使用2D,3D或模型组合识别和本地化神经杀菌结构,而脑电图和行为(准确性)数据被记录。与从2D模型中学到的人相比,使用3D模型的参与者使用3D模型学习更大的对象识别(N250幅度)。基于神经系统结果,结合2D和3D模型的交错学习提供了学习,保留和由减少奖励积极幅度表示的转移活动的优点。行为数据没有与神经数据相同的敏感性,以区分学习的差异,并不在这些学习活动中的立体内。测量神经活动揭示了教育工作者应用设置的新见解,以考虑在学习干预设计中结合立体模型。

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