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Developing and Validating a Computer-Based Training Tool for Inferring 2D Cross-Sections of Complex 3D Structures
Human Factors: The Journal of the Human Factors and Ergonomics Society ( IF 2.9 ) Pub Date : 2021-05-18 , DOI: 10.1177/00187208211018110
Anahita Sanandaji 1 , Cindy Grimm 2 , Ruth West 3 , Christopher A Sanchez 2
Affiliation  

Objective

Developing and validating a novel domain-agnostic, computer-based training tool for enhancing 2D cross-section understanding of complex 3D structures.

Background

Understanding 2D cross-sections of 3D structures is a crucial skill in many disciplines, from geology to medical imaging . It requires a complex set of spatial/visualization skills including mental rotation, spatial structure understanding, and viewpoint projection. Prior studies show that experts differ from novices in these skills.

Method

We have developed a novel training tool for inferring 2D cross-sections of 3D structures using a participatory design methodology. We used a between-subject study design, with 60 participants, to evaluate the training tool. Our primary effectiveness evaluation was based on pre- and postspatial tests that measured both cross-section abilities and specific spatial skills: viewpoint, mental rotation, and card rotation.

Results

Results showed significant performance gains on inferring 2D cross-sections for participants of the training group. Our tool improves two other spatial skills as well: mental rotation and viewpoint visualization.

Conclusion

Our training tool was effective not only in enhancing 2D cross-section understanding of complex 3D structures, but also in improving mental rotation and viewpoint visualization skills.

Application

Our tool can be beneficial in different fields such as medical imaging, biology, geology, and engineering. For example, an application of our tool is in medical/research labs to train novice segmenters in ongoing manual 3D segmentation tasks. It can also be adapted in other contexts, such as training children, older adults, and individuals with very low spatial skills.



中文翻译:

开发和验证基于计算机的训练工具,用于推断复杂 3D 结构的 2D 横截面

客观的

开发和验证一种新的与领域无关的、基于计算机的培训工具,以增强对复杂 3D 结构的 2D 横截面理解。

背景

了解 3D 结构的 2D 横截面是从地质学到医学成像等许多学科的关键技能。它需要一套复杂的空间/可视化技能,包括心理旋转、空间结构理解和视点投射。先前的研究表明,专家在这些技能上不同于新手。

方法

我们开发了一种新颖的培训工具,用于使用参与式设计方法推断 3D 结构的 2D 横截面。我们使用了 60 名参与者的受试者间研究设计来评估培训工具。我们的主要有效性评估基于测量横截面能力和特定空间技能的前后空间测试:观点、心理旋转和卡片旋转。

结果

结果显示,训练组参与者在推断 2D 横截面时获得了显着的性能提升。我们的工具还改进了另外两种空间技能:心理旋转和视点可视化。

结论

我们的培训工具不仅有效地增强了对复杂 3D 结构的 2D 横截面的理解,而且还提高了心理旋转和视点可视化技能。

应用

我们的工具可以在医学成像、生物学、地质学和工程学等不同领域发挥作用。例如,我们工具的一个应用是在医学/研究实验室中训练新手分割者处理正在进行的手动 3D 分割任务。它还可以在其他情况下进行调整,例如训练儿童、老年人和空间技能非常低的人。

更新日期:2021-05-19
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