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Validity Evidence for the SUCCESS Survey: Measuring Non-Cognitive and Affective Traits of Engineering and Computing Students

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Conference

2018 ASEE Annual Conference & Exposition

Location

Salt Lake City, Utah

Publication Date

June 23, 2018

Start Date

June 23, 2018

End Date

July 27, 2018

Conference Session

System 1 in Engineering Education and Research

Tagged Division

Educational Research and Methods

Tagged Topic

Diversity

Page Count

28

Permanent URL

https://peer.asee.org/31222

Download Count

64

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Paper Authors

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Matthew Scheidt Purdue University, West Lafayette Orcid 16x16 orcid.org/0000-0001-6779-1992

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Matthew Scheidt is a Ph.D. student in Engineering Education at Purdue University. He graduated from Purdue University with a B.S. in Mechanical Engineering, and The Ohio State University with a M.S. in Mechanical Engineering with a focus in Ultrasonic Additive Manufacturing. Matt is currently part of Dr. Allison Godwin’s STRIDE (Shaping Transformative Research on Identity and Diversity in Engineering) research group at Purdue.

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Allison Godwin Purdue University, West Lafayette (College of Engineering) Orcid 16x16 orcid.org/0000-0002-0741-3356

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Allison Godwin, Ph.D. is an Assistant Professor of Engineering Education at Purdue University. Her research focuses what factors influence diverse students to choose engineering and stay in engineering through their careers and how different experiences within the practice and culture of engineering foster or hinder belongingness and identity development. Dr. Godwin graduated from Clemson University with a B.S. in Chemical Engineering and Ph.D. in Engineering and Science Education. Her research earned her a National Science Foundation CAREER Award focused on characterizing latent diversity, which includes diverse attitudes, mindsets, and approaches to learning, to understand engineering students’ identity development. She is the recipient of a 2014 American Society for Engineering Education (ASEE) Educational Research and Methods Division Apprentice Faculty Grant. She has also been recognized for the synergy of research and teaching as an invited participant of the 2016 National Academy of Engineering Frontiers of Engineering Education Symposium and 2016 New Faculty Fellow for the Frontiers in Engineering Education Annual Conference. She also was an NSF Graduate Research Fellow for her work on female empowerment in engineering which won the National Association for Research in Science Teaching 2015 Outstanding Doctoral Research Award.

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Ryan R. Senkpeil Purdue University, West Lafayette (College of Engineering)

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Ryan Senkpeil is a Ph.D. student in Engineering Education at Purdue University who's research is focused on non-cognitive factors that impact engineering student performance and developing interventions to improve students' non-cognitive factors.

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Julianna Sun Ge Purdue University, West Lafayette (College of Engineering)

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Julianna Ge is a Ph.D. student in the School of Engineering Education at Purdue University. At Purdue, she created and currently teaches a novel course for undergraduate engineering students to explore the intersections of wellbeing, leadership, diversity and inclusion. As an NSF Graduate Research Fellow, her research interests intersect the fields of engineering education, positive psychology, and human development to understand diversity, inclusion, and success for undergraduate engineering students. Prior to Purdue, she received dual bachelor’s degrees in Industrial Engineering and Human Development and Family Studies from the University of Illinois at Urbana-Champaign. Her prior work experiences include product management, consulting, tutoring, marketing, and information technology.

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John Chen P.E. 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, and lifelong learning skills and behaviors.

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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, and during Fall 2017 he taught at the Karlsruhe 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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James M. Widmann California Polytechnic State University, San Luis Obispo

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Jim Widmann is a professor of mechanical engineering 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 an Interdisciplinary senior project class and teaches mechanics and design courses. He also conducts research in the areas of creative design, machine design, fluid power control, and engineering education.

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Edward J. Berger Purdue University, West Lafayette (College of Engineering)

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Edward Berger is an Associate Professor of Engineering Education and Mechanical Engineering at Purdue University, joining Purdue in August 2014. He has been teaching mechanics for over 20 years, and has worked extensively on the integration and assessment of specific technology interventions in mechanics classes. He was one of the co-leaders in 2013-2014 of the ASEE Virtual Community of Practice (VCP) for mechanics educators across the country. His current research focuses on student problem-solving processes and use of worked examples, change models and evidence-based teaching practices in engineering curricula, and the role of non-cognitive and affective factors in student academic outcomes and overall success.

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Abstract

Each engineering and computing student admitted to a university has clear potential for academic and personal success in their undergraduate curriculum. While some thrive academically, others flounder. Why is it that highly credentialed and previously successful students do not see the same success in college? We posit that some collection of characteristics—apparently not visible on their admission applications and perhaps not related to their talent or intelligence—is an important piece of the student performance puzzle. We developed a survey to measure various non-cognitive and affective factors that we believe are important for student achievement, academically, personally, and professionally. This research examines the validity evidence for our piloted SUCCESS survey (Studying Underlying Characteristics for Computing and Engineering Student Success), which measures latent factors of personality, community, grit, thriving, identity, mindset, motivation, perceptions of faculty caring, stress, gratitude, self-control, mindfulness, and belongingness. These non-cognitive and affective factors are representative of multifaceted aspects of undergraduate student success in prior literature. Each of the constructs we chose had validity evidence from prior studies, some within an engineering population. We piloted the survey across two different universities, one West Coast and one Midwest (n = 490), in Summer 2017. We used Exploratory Factor Analysis (EFA) to evaluate instrument performance to decide which items to include in the national release of the survey in Fall 2017. Our results provide preliminary validity evidence for items that measure various non-cognitive and affective factors. The wide-ranging constructs within the SUCCESS survey provide multiple pathways to understand students’ likelihood for success in engineering and computing. Our future work includes distributing this survey to over a dozen universities across the U.S., yielding a broad dataset of non-cognitive profiles of engineering and computing students broadly. In parallel, we will link these results with students’ registrar information at three study sites to develop predictive models for student success.

Scheidt, M., & Godwin, A., & Senkpeil, R. R., & Ge, J. S., & Chen, J., & Self, B. P., & Widmann, J. M., & Berger, E. J. (2018, June), Validity Evidence for the SUCCESS Survey: Measuring Non-Cognitive and Affective Traits of Engineering and Computing Students Paper presented at 2018 ASEE Annual Conference & Exposition , Salt Lake City, Utah. https://peer.asee.org/31222

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