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The Mechanics of SUCCESS: How Non-Cognitive and Affective Factors Relate to Academic Performance in Engineering Mechanics

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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

MASS: Mastery, Assessment and Success of Students

Tagged Division

Mechanics

Tagged Topic

Diversity

Page Count

11

Permanent URL

https://peer.asee.org/37876

Download Count

18

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Paper Authors

biography

Brian P. Self California Polytechnic State University, San Luis Obispo

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Brian Self obtained his B.S. and M.S. degrees in Engineering Mechanics from Virginia Tech, and his Ph.D. in Bioengineering from the University of Utah. He worked in the Air Force Research Laboratories before teaching at the U.S. Air Force Academy for seven years. Brian has taught in the Mechanical Engineering Department at Cal Poly, San Luis Obispo since 2006. During the 2011-2012 academic year he participated in a professor exchange, teaching at the Munich University of Applied Sciences. His engineering education interests include collaborating on the Dynamics Concept Inventory, developing model-eliciting activities in mechanical engineering courses, inquiry-based learning in mechanics, and design projects to help promote adapted physical activities. Other professional interests include aviation physiology and biomechanics.

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Jenna Landy California Polytechnic State University, San Luis Obispo

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Jenna Landy graduated from Cal Poly, San Luis Obispo, in June 2020 with a Bachelor's degree in Statistics and a minor in Data Science. She worked with this group from Fall 2018 until graduation, carrying out statistical analysis of survey data. She enjoyed learning about engineering education and the role of non-cognitive and affective competencies.

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James M. Widmann California Polytechnic State University, San Luis Obispo

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Jim Widmann is a professor and chair of the Mechanical Engineering Department at California Polytechnic State University, San Luis Obispo. He received his Ph.D. in 1994 from Stanford University and has served as a Fulbright Scholar at Kathmandu University it Nepal. At Cal Poly, he teaches the College of Engineering's interdisciplinary, industry sponsored, senior project class as well as course in mechanics and design. He also conducts research in the areas of creative design, machine design, fluid power control, and engineering education.

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John Chen California Polytechnic State University, San Luis Obispo

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John Chen is a professor of mechanical engineering. His interests in engineering education include conceptual learning, conceptual change, student autonomy and motivation, lifelong learning skills and behaviors, and non-cognitive factors that lead to student success.

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Michelle Kerfs California Polytechnic State University, San Luis Obispo

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Michelle is a fourth year statistics and data science student at Cal Poly San Luis Obispo. She joined this research team in January 2020 and is excited by what they can discover! She enjoys learning more about data analysis and machine learning methods but in her free time also loves running, hiking, and any type of arts and crafts.

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Abstract

One particular academic area of engineering student difficulty is in the field of mechanics. Mechanics, including introductory physics, statics, and dynamics, forms the basis of many upper division engineering courses and often causes students considerable conceptual and problem- solving difficulty. These courses sometimes have the highest failure rate for engineers and can be an engineering student’s first experience with academic difficulty. Although grades might be predicted by factors such as high school GPA or standardized test results (e.g., ACT/SAT), we postulate that non-cognitive factors such as grit and motivation might play a larger role in student performance in mechanics. The Studying Underlying Characteristics of Computing and Engineering Student Success (SUCCESS) survey was designed to investigate how these types of non-cognitive and affective (NCA) competencies can better predict academic success. Using results of the SUCCESS survey given to hundreds of students at a large western public engineering school, this work investigates the correlation between the 14 constructs measured by the survey (including such factors as Self Control, Motivation, Grit, Identity and Belongingness) to performance in introductory engineering physics courses, engineering statics, and engineering dynamics. Adding NCA factors to traditional predictors of Math SAT score and Highs school GPA increased the R^2 values by up to 0.1. Test anxiety was a strong negative predictor for all mechanics course grades, and Time and Study environment was positively correlated to grades in statics and dynamics.

Self, B. P., & Landy, J., & Widmann, J. M., & Chen, J., & Kerfs, M. (2021, July), The Mechanics of SUCCESS: How Non-Cognitive and Affective Factors Relate to Academic Performance in Engineering Mechanics Paper presented at 2021 ASEE Virtual Annual Conference Content Access, Virtual Conference. https://peer.asee.org/37876

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