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Cited by 633

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Educational Research in Developing 3‐D Spatial Skills for Engineering Students

Sorby, Sheryl A.·2009·International Journal of Science Education

Abstract

The ability to visualize in three dimensions is a cognitive skill that has been shown to be important for success in engineering and other technological fields. For engineering, the ability to mentally rotate 3‐D objects is especially important. Unfortunately, of all the cognitive skills, 3‐D rotation abilities exhibit robust gender differences, favoring males. The assessment of 3‐D spatial skills and associated gender differences has been a topic of educational research for nearly a century; however, a great deal of the previous work has been aimed at merely identifying differences. The author has been conducting applied research in the area of spatial skills development for more than a decade aimed at identifying practical methods for improving 3‐D spatial skills, especially for women engineering students. This paper details the significant findings obtained over the past several years through this research and identifies strategies that appear to be effective in developing 3‐D spatial skills and in contributing to student success.

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Metadata

Authors
Sorby, S. A.
Venue
International Journal of Science Education
Published
2009-02
Volume
31
Issue
3
Pages
459-480
ISSN
  • 0950-0693 (ISSN-L)
  • 1464-5289
OpenAlex
W2155328926
Cited by
633
References
0
FWCI
31.03
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Educational Research in Developing 3‐D Spatial Skills for Engineering Students. https://app.cochat.ai/papers/10.1080/09500690802595839
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Sorby, S. A. (2009). Educational Research in Developing 3‐D Spatial Skills for Engineering Students. International Journal of Science Education. https://doi.org/10.1080/09500690802595839

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.