Improving Spatial Visualization Abilities Using 3D Printed Blocks
- Conference
- Location
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Salt Lake City, Utah
- Publication Date
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June 23, 2018
- Start Date
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June 23, 2018
- End Date
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July 27, 2018
- Conference Session
- Tagged Division
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Pre-College Engineering Education
- Tagged Topic
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Diversity
- Page Count
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15
- DOI
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10.18260/1-2--30634
- Permanent URL
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https://peer.asee.org/30634
- Download Count
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704
Paper Authors
Vanessa LeBow University of Arkansas
Vanessa LeBow is a student at the University of Arkansas pursuing her Master of Science in Civil Engineering. Her areas of focus are geotechnical and environmental engineering. She graduated with her Bachelor of Science in Civil Engineering this past May and as a part of her undergraduate honors thesis, she investigated the use of 3D printed aids to improve spatial visual retention.
Michelle L. Bernhardt-Barry University of Arkansas
Dr. Bernhardt-Barry is an Assistant Professor of Civil Engineering at the University of Arkansas. She received her Ph.D, M.S., and B.S. in civil engineering from Texas A&M University. Her research interests include geotechnical engineering, and the use of 3d printed models to aid learning in K-12 and college classrooms.
Jyotishka Datta
University of Arkansas
orcid.org/0000-0001-5991-5182
Jyotishka Datta is an Assistant Professor of Statistics at the University of Arkansas at Fayetteville since August 2016. He was an NSF postdoctoral fellow at Duke University and Statistical and Applied Mathematical Sciences Institute (SAMSI) working with Dr. David B. Dunson (Statistical Science) and Dr. Sandeep S. Dave (School of Medicine). He received my Ph.D. in Statistics from Purdue University in 2014 under the guidance of Prof. Jayanta K. Ghosh. Dr. Datta's research interest spans Bayesian methodology and theory for structured high-dimensional or infinite-dimensional objects. He has contributed to the area of large-scale simultaneous testing, shrinkage prior, sparse signal recovery, nonparametric Bayes, computational aspects of big data analysis, bioinformatics, applied probability, and default Bayes. Recent applications include next-gen sequencing studies, auditory neuroscience, and crime forecasting.
Abstract
Spatial visualization abilities have been shown to be a key predictor of success in science, technology, engineering, and math fields. Past research has revealed that women and underrepresented minorities tend to lag behind in spatial visual abilities, however, research has also shown that these skills can be improved with guided practice. This study seeks to examine whether 3D printed aids help spatial visual retention in 6th graders. A modified Purdue spatial visualization test was used as the assessment standard. Students’ mental rotation abilities were assessed before and after the 3D printed aids were administered. Data was collected from five different schools in Northwest Arkansas to measure the effectiveness of the 3D aids and to examine the performance of students across various gender, ethnic, and socioeconomic backgrounds. A prospective power calculation was performed to ensure that the sample size for each group was sufficient enough for significant differences to be detected. A P-value of 8.2x10-16 was obtained for significant difference between the pre and post assessments. This indicates that the post scores were significantly higher than the pre scores, while adjusting for the other factors. The results suggest that the blocks are effective in improving scores on the Modified Purdue Visualization of Rotation test regardless of a student’s gender, socioeconomic background, or language.
LeBow, V., & Bernhardt-Barry, M. L., & Datta, J. (2018, June), Improving Spatial Visualization Abilities Using 3D Printed Blocks Paper presented at 2018 ASEE Annual Conference & Exposition , Salt Lake City, Utah. 10.18260/1-2--30634
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