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Learning from graphically integrated 2D and 3D representations improves retention of neuroanatomy.

机译:从图形集成的2D和3D表示中学习可以改善神经解剖结构的保留。

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摘要

Visualizations in the form of computer-based learning environments are highly encouraged in science education, especially for teaching spatial material. Some spatial material, such as sectional neuroanatomy, is very challenging to learn. It involves learning the two dimensional (2D) representations that are sampled from the three dimensional (3D) object. In this study, a computer-based learning environment was used to explore the hypothesis that learning sectional neuroanatomy from a graphically integrated 2D and 3D representation will lead to better learning outcomes than learning from a sequential presentation. The integrated representation explicitly demonstrates the 2D-3D transformation and should lead to effective learning.;The Integrated 2D3D group was better than the Whole then Sections group in retaining knowledge of difficult instances of sectional anatomy after the retention interval. The benefit of learning from an integrated 2D3D representation suggests that there are some spatial transformations which are better retained if they are learned through an explicit demonstration. Participants also showed evidence of continued learning on the tests of generalization with the help of cues and practice, even without feedback. This finding suggests that the computer-based learning programs used in this study were good tools for instruction of neuroanatomy.;This study was conducted using a computer graphical model of the human brain. There were two learning groups: Whole then Sections, and Integrated 2D3D. Both groups learned whole anatomy (3D neuroanatomy) before learning sectional anatomy (2D neuroanatomy). The Whole then Sections group then learned sectional anatomy using 2D representations only. The Integrated 2D3D group learned sectional anatomy from a graphically integrated 3D and 2D model. A set of tests for generalization of knowledge to interpreting biomedical images was conducted immediately after learning was completed. The order of presentation of the tests of generalization of knowledge was counterbalanced across participants to explore a secondary hypothesis of the study: preparation for future learning. If the computer-based instruction programs used in this study are effective tools for teaching anatomy, the participants should continue learning neuroanatomy with exposure to new representations. A test of long-term retention of sectional anatomy was conducted 4-8 weeks after learning was completed.
机译:在科学教育中,尤其是在空间材料教学中,强烈鼓励以计算机为基础的学习环境形式的可视化。一些空间材料,例如断层神经解剖学,很难学习。它涉及学习从三维(3D)对象采样的二维(2D)表示形式。在这项研究中,使用基于计算机的学习环境来探索这样的假设:从图形化的2D和3D表示中学习断层神经解剖结构比从顺序表示中学习将产生更好的学习结果。整合表示法明确地显示了2D-3D转换,并应导致有效的学习。整合2D3D组在保留间隔后仍保留断层解剖学的困难实例方面要比“整体”然后“剖面”组更好。从集成的2D3D表示中学习的好处表明,如果通过显式演示学习到某些空间变换,则可以更好地保留它们。参与者还展示了在提示和实践的帮助下,即使没有反馈,也可以继续学习有关泛化测试的知识。这一发现表明,本研究中使用的基于计算机的学习程序是指导神经解剖学的良好工具。;该研究是使用人脑的计算机图形模型进行的。有两个学习小组:整个然后是部分,以及集成2D3D。两组在学习截面解剖(2D神经解剖学)之前都学习了整个解剖学(3D神经解剖学)。然后,“整体然后剖面”小组仅使用2D表示学习剖面解剖。集成2D3D小组从以图形方式集成的3D和2D模型中学习了剖面解剖。学习完成后,立即进行了一系列的知识概括性测试,以解释生物医学图像。参与者之间的知识普遍化测试的呈示顺序被抵消,以探索该研究的次要假设:为将来的学习做准备。如果本研究中使用的基于计算机的教学程序是教授解剖学的有效工具,则参与者应继续学习神经解剖学并接触新的表现形式。学习完成后的4-8周进行了长期保留的截面解剖学测试。

著录项

  • 作者

    Naaz, Farah.;

  • 作者单位

    University of Louisville.;

  • 授予单位 University of Louisville.;
  • 学科 Psychology Experimental.;Education Educational Psychology.;Education Sciences.;Education Technology of.
  • 学位 Ph.D.
  • 年度 2012
  • 页码 76 p.
  • 总页数 76
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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