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

Abstract

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.

Engineering students' noncognitive and affective factors: Group differences from cluster analysis

“…We measured respondents' NCA profiles using a collection of previously developed survey instruments (the development [Berger et al, 2018] and validation [Scheidt, Godwin, et al, 2019, 2018] of this comprehensive survey instrument have been described in earlier publications). The SUCCESS survey instrument combined the interests of a set of eight researchers at three institutions who negotiated research interest and overall questionnaire length to develop a survey instrument that captured many NCA factors.…”

“…This scale relates to a sense of belonging by focusing more on how faculty shape belonging. Our recent research shows that although the perceptions of faculty caring and engineering belongness scales are different, there is a moderate correlation between the two (Scheidt, Godwin, et al, 2018). Overall, students who perceive they are a member of the academic community recognized and valued by the faculty generally have a higher sense of belonging (Hoffman et al, 2003).…”

A Scoping Literature Review of Engineering Thriving to Redefine Student Success

“…Although general theories of human thriving have been developed in disciplines such as psychology (Butler & Kern, 2016;Su et al 2014), some measures developed in psychology do not appear to measure the same theoretical constructs in undergraduate engineering students (Scheidt et al 2018) and may not directly transfer to this population. Within the discipline of engineering education, engineering education researchers study engineering identity uniquely in the engineering culture even though identity research spans several disciplines (Godwin, 2016;Prybutok et al 2016).…”

Board 98: Validity Evidence for the SUCCESS Survey: Measuring Noncognitive and Affective Traits of Engineering and Computing Students (Part II)

“…After cleaning (removing responses which failed an attention check embedded toward the end of the survey or incomplete surveys), 1074 responses were removed, resulting in a total of n = 2672 responses. This survey was focused on measuring non-cognitive and affective factors, taken from existing instruments used with similar populations, that have the potential to predict engineering and computing student success [5]. This survey measures 32 NCA factors that may contribute to student success including personality, grit, identity, mindset, motivation, stress, gratitude, mindfulness, and belongingness, and is the first of its kind launched on a national scale.…”

“…In the Summer of 2017, we launched a pilot survey to determine if our survey measures showed evidence of validity (n = 490). Using that data, we conducted exploratory factor analysis (EFA) [5] and found some measures that did not have strong validity evidence, which led to the exclusion of two constructs and over 50 survey items, resulting in the survey administered and discussed within this paper.…”