Berger, Edward J.; Godwin, Allison; Chen, John; Widmann, James M.; Self, Brian P.; Gates, Ann Q.; Scheidt, Matthew; Senkpeil, Ryan R.; and Ge, Julianna Sun, "Studying Underlying Characteristics of Computing and Engineering Student Success (SUCCESS) Survey" (2018). School of Engineering Education Working Papers. Paper 4.
Date of this Version
This survey was developed to measure underlying factors that may influence student success including personality, community, grit, thriving, identity, mindset, motivation, perceptions of faculty caring, stress, gratitude, self-control, mindfulness, and belongingness. We measure these underlying factors because each engineering and computing student admitted to a university has clear potential for academic and personal success in their undergraduate curriculum based upon admissions criteria. However, while some thrive academically, others struggle in a variety of ways. In our NSF-funded project (1626287/1626185/1626148), 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. 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. An exploratory and confirmatory factor analysis have been conducted on the original list of items to develop this finalized survey (Scheidt et al., 2018). The survey takes approximately 30 minutes for students to complete.
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