Correlating Common Errors in Statics Problem Solving with Spatial Ability

Maxine Fontaine; Chaitanya Krishna Vallabh

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Conference: 2024 ASEE Annual Conference & Exposition
Location: Portland, Oregon
Publication Date: June 23, 2024
Start Date: June 23, 2024
End Date: June 26, 2024
Conference Session: Learning Mechanics through Visual and Tactile Modalities
Tagged Division: Mechanics Division (MECHS)
Page Count: 11
DOI: 10.18260/1-2--47079
Permanent URL: https://peer.asee.org/47079
Download Count: 61

Paper Authors

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Maxine Fontaine Stevens Institute of Technology

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Maxine Fontaine is a Teaching Associate Professor in Mechanical Engineering at Stevens Institute of Technology. She received her Ph.D. in 2010 from Aalborg University in Aalborg, Denmark. Maxine has a background in the biomechanics of human movement, and her current research projects are related to spatial skills and adaptive expertise in engineering students.

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Chaitanya Krishna Vallabh Stevens Institute of Technology orcid.org/0000-0003-4396-3176

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Abstract

Solving engineering problems is more than simply solving equations. It requires a clear visual representation of the problem, e.g. a schematic or diagram, before analysis is possible. In statics, for example, generating an appropriate free-body diagram is a critical step in the process. Spatial visualization skills (SVS) may play a critical role in developing these free-body diagrams properly. Many concepts in statics rely on the ability to visualize the effects of various force vectors on the equilibrium of an object. Understanding the direction of force and moment vectors is key to mastering these concepts. Without strong SVS, students may rely on other tactics such as identifying superficial patterns to help solve the problem without a good understanding of the underlying concept. When confronted with a new situation, they are unable to properly “extrapolate” the memorized examples, so their misconceptions are revealed. Students with strong SVS may be able to more easily interpret graphical representations (such as vector addition) leading to a stronger understanding of the underlying concepts. However, high visualizers are not guaranteed to grasp the concepts if they do not spend the effort to connect with the material. In this study, we aim to study the potential correlation between a student’s spatial ability and the types of errors made in solving fundamental statics problems. The two exam problems selected for the study focus on calculating resultant force and resultant moment in 2D. If certain types of errors are indicative of low spatial ability, identifying these types of errors will be the first step in developing activities to help correct these misconceptions. Activities involving physical manipulatives and/or virtual 3D models may improve conceptual understanding for low visualizers, including the development of hands-on lab experiments. Spatial ability is assessed using the Purdue Spatial Visualization Test: Rotations (PSVT:R), a timed standardized test of mental rotations. The passing threshold is typically set at 60% or 70% to identify students with low spatial ability. At [our university], thresholds of 60% and 80% are used to separate students into groups of low, medium, and high spatial ability. The prevalence of each type of error among the three SVS groups (low, medium, and high) will be determined and compared. We hypothesize that errors related to direction of resultant vectors and moments will be more prevalent among low visualizers, and errors related to calculating the magnitude of these vectors and moments will not be correlated with SVS.

Citation
Format

Fontaine, M., & Vallabh, C. K. (2024, June), Correlating Common Errors in Statics Problem Solving with Spatial Ability Paper presented at 2024 ASEE Annual Conference & Exposition, Portland, Oregon. 10.18260/1-2--47079

TY - CPAPER
AB - Solving engineering problems is more than simply solving equations. It requires a clear visual representation of the problem, e.g. a schematic or diagram, before analysis is possible. In statics, for example, generating an appropriate free-body diagram is a critical step in the process. Spatial visualization skills (SVS) may play a critical role in developing these free-body diagrams properly. Many concepts in statics rely on the ability to visualize the effects of various force vectors on the equilibrium of an object. Understanding the direction of force and moment vectors is key to mastering these concepts.
Without strong SVS, students may rely on other tactics such as identifying superficial patterns to help solve the problem without a good understanding of the underlying concept. When confronted with a new situation, they are unable to properly “extrapolate” the memorized examples, so their misconceptions are revealed.
Students with strong SVS may be able to more easily interpret graphical representations (such as vector addition) leading to a stronger understanding of the underlying concepts. However, high visualizers are not guaranteed to grasp the concepts if they do not spend the effort to connect with the material.
In this study, we aim to study the potential correlation between a student’s spatial ability and the types of errors made in solving fundamental statics problems. The two exam problems selected for the study focus on calculating resultant force and resultant moment in 2D. If certain types of errors are indicative of low spatial ability, identifying these types of errors will be the first step in developing activities to help correct these misconceptions. Activities involving physical manipulatives and/or virtual 3D models may improve conceptual understanding for low visualizers, including the development of hands-on lab experiments.
Spatial ability is assessed using the Purdue Spatial Visualization Test: Rotations (PSVT:R), a timed standardized test of mental rotations. The passing threshold is typically set at 60% or 70% to identify students with low spatial ability. At [our university], thresholds of 60% and 80% are used to separate students into groups of low, medium, and high spatial ability.
The prevalence of each type of error among the three SVS groups (low, medium, and high) will be determined and compared. We hypothesize that errors related to direction of resultant vectors and moments will be more prevalent among low visualizers, and errors related to calculating the magnitude of these vectors and moments will not be correlated with SVS.

AU - Maxine Fontaine
AU - Chaitanya Krishna Vallabh
CY - Portland, Oregon
DA - 2024/06/23
PB - ASEE Conferences
TI - Correlating Common Errors in Statics Problem Solving with Spatial Ability
UR - https://peer.asee.org/47079
DO - 10.18260/1-2--47079
ER -