Do They Need To See It To Learn It? Spatial Abilities, Representational Competence, and Conceptual Knowledge in Statics

Eric Davishahl; Todd Haskell; Lee Singleton; Matthew Parsons Fuentes

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Conference: 2021 ASEE Virtual Annual Conference Content Access
Location: Virtual Conference
Publication Date: July 26, 2021
Start Date: July 26, 2021
End Date: July 19, 2022
Conference Session: The ABCs of FBDs
Tagged Division: Mechanics
Tagged Topic: Diversity
Page Count: 18
DOI: 10.18260/1-2--36990
Permanent URL: https://peer.asee.org/36990
Download Count: 460

Paper Authors

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Eric Davishahl Whatcom Community College orcid.org/0000-0001-9506-2658

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Eric Davishahl holds an MS degree in mechanical engineering from the University of Washington and currently serves as professor and engineering program coordinator at Whatcom Community College in northwest Washington state. Eric has been teaching community college engineering transfer students for 20 years. His teaching and research interests include developing, implementing and assessing active learning instructional strategies and course-based undergraduate research experiences. Eric has been a member of ASEE since 2001. He currently serves as awards chair for the Pacific Northwest Section and was the recipient of the 2008 Section Outstanding Teaching Award.

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Todd Haskell

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Todd Haskell is a cognitive scientist interested in learning and the development of expertise, especially in STEM fields. He is currently Associate Professor of Psychology at Western Washington University. In previous projects Dr. Haskell has worked on understanding how chemistry novices and experts navigate between macroscopic, symbolic, and small particle representations, and how pre-service elementary teachers translate an understanding of energy concepts from physics to other disciplines.

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Lee Singleton Whatcom Community College

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Lee Singleton is a professor at Whatcom Community College, in Bellingham, WA. He holds a BS in mathematics from Harding University, a MS in mathematics and PhD in biomedical mathematics from Florida State University. His current interests include 3D-printing, active learning, and infusing more physical activity into mathematics courses. Recent grant positions include principal investigator on the NSF-funded grant “EAGER: MAKER: Engaging Math Students with 3D-Printing for STEM Success and co-PI on the NSF-funded grant "Collaborative Research: Improving Representational Competence by Engaging with Physical Modeling in Foundational STEM Courses".

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Matthew Parsons Fuentes

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Abstract

A growing body of research indicates spatial visualization skills are important to success in many STEM disciplines, including several engineering majors that rely on a foundation in engineering mechanics. Many fundamental mechanics concepts such as free-body diagrams, moments, and vectors are inherently spatial in that application of the concept and related analytical techniques requires visualization and sketching. Visualization may also be important to mechanics learners’ ability to understand and employ common mechanics representations and conventions in communication and problem solving, a skill known as representational competence. In this paper, we present early research on how spatial abilities might factor in to students’ conceptual understanding of vectors and associated representational competence.

We administered the Mental Cutting Test (MCT), a common assessment of spatial abilities, in the first and last week of the term. We also administered the Test of Representational Competence with Vectors (TRCV), a targeted assessment of vector concepts and representations, in week one and at mid-term. The vector post-test came after coverage of moments and cross products. We collected this assessment data in statics courses across multiple terms at three different colleges. To understand how spatial skills relate to the development of representational competence, we use a multiple regression model to predict TRCV scores using the pre-class MCT scores as well as other measures of student preparation in the form of grades in prerequisite math and physics coursework. We then extend the analysis to consider both MCT and TRCV scores as predictors for student performance on the Concept Assessment Test in Statics. We find that spatial abilities are a factor in students’ development of representational competence with vectors. We also find that representational competence with vectors likely mediates the importance of spatial abilities to student success in developing broader conceptual understanding in statics. We conclude by discussing implications for mechanics instruction.

Citation
Format

Davishahl, E., & Haskell, T., & Singleton, L., & Fuentes, M. P. (2021, July), Do They Need To See It To Learn It? Spatial Abilities, Representational Competence, and Conceptual Knowledge in Statics Paper presented at 2021 ASEE Virtual Annual Conference Content Access, Virtual Conference. 10.18260/1-2--36990

TY - CPAPER
AB - A growing body of research indicates spatial visualization skills are important to success in many STEM disciplines, including several engineering majors that rely on a foundation in engineering mechanics. Many fundamental mechanics concepts such as free-body diagrams, moments, and vectors are inherently spatial in that application of the concept and related analytical techniques requires visualization and sketching. Visualization may also be important to mechanics learners’ ability to understand and employ common mechanics representations and conventions in communication and problem solving, a skill known as representational competence. In this paper, we present early research on how spatial abilities might factor in to students’ conceptual understanding of vectors and associated representational competence.

We administered the Mental Cutting Test (MCT), a common assessment of spatial abilities, in the first and last week of the term. We also administered the Test of Representational Competence with Vectors (TRCV), a targeted assessment of vector concepts and representations, in week one and at mid-term. The vector post-test came after coverage of moments and cross products. We collected this assessment data in statics courses across multiple terms at three different colleges. To understand how spatial skills relate to the development of representational competence, we use a multiple regression model to predict TRCV scores using the pre-class MCT scores as well as other measures of student preparation in the form of grades in prerequisite math and physics coursework. We then extend the analysis to consider both MCT and TRCV scores as predictors for student performance on the Concept Assessment Test in Statics. We find that spatial abilities are a factor in students’ development of representational competence with vectors. We also find that representational competence with vectors likely mediates the importance of spatial abilities to student success in developing broader conceptual understanding in statics. We conclude by discussing implications for mechanics instruction.

AU - Eric Davishahl
AU - Todd Haskell
AU - Lee Singleton
AU - Matthew Parsons Fuentes
CY - Virtual Conference
DA - 2021/07/26
PB - ASEE Conferences
TI - Do They Need To See It To Learn It? Spatial Abilities, Representational Competence, and Conceptual Knowledge in Statics
UR - https://peer.asee.org/36990
DO - 10.18260/1-2--36990
ER -