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2021 ASEE Virtual Annual Conference Content Access

Update on the Role of Non-Cognitive and Affective (NCA) Factors in Engineering and Computing Student Academic Performance

Presented at NSF Grantees Poster Session

The NSF-funded Studying Underlying Characteristics of Computing and Engineering Student Success (SUCCESS) project is exploring the role that non-cognitive and affective (NCA) factors relate to retention and broad definitions of success for undergraduate engineering and computing students. The main tool used in this study is the SUCCESS survey which provides insight into a student’s big 5 personality, Community, Grit, Thriving, Identity, Mindset, Motivation, Time and Study Environment, Test Anxiety, Perception of Faculty Caring, Self-Control, Stress, Gratitude, Belongingness and Mindfulness. Over the last three years, the survey has been given to over 4,000 engineering and computing students nationally. It is postulated that understanding the interplay among NCA factors may impart a more in-depth understanding of engineering student success than traditionally tracked cognitive factors, such as standardized test scores and GPA. After identifying groups of NCA factors that are both malleable and important in engineering and computing student success, targeted NCA-based interventions are being developed that can become a critical tool for use by engineering departments, faculty and academic affairs professionals to enhance the student experience.

The project is driven by the exploration of three primary research questions:
• RQ1. What are the NCA profiles of engineering and computing students, and to what extent do profiles vary by institution, academic program, demographics, or over time?
• RQ2. In what ways are NCA factors predictors of academic performance, and how do they mediate a student’s response to academic or personal obstacles they may face?
• RQ3. To what extent can NCA-based interventions improve academic performance and the perceived quality of the undergraduate experience, and how do students at different institutions experience those interventions?

This paper presents work completed through year four of the SUCCESS project (collaborative research between three partner institutions: IUSE awards NSF 1626287, 1626185, and 1626148) with special emphasis on results from efforts at on undergraduate focused public university on the west coast. Analysis of the SUCCESSS survey results shows that engineering students NCA profiles fall into five discernable clusters. Tracking of student academic performance over two years based on cluster membership show differences in academic progression. Result from a third year of tracking are included in this paper. We have also found that generally available Cognitive factors (such as standardized test scores or high school GPA) fail to predict major and university retention rates, especially for underserved student populations. Using survey results, we examine how student retention and success relate to NCA factors these underserved students. Additionally, we have added another year to our longitudinal study through the continual data collection from Mechanical Engineering students to gain an understanding of how student NCA profiles evolve over time and through experiences within an engineering program. It is anticipated that the results of this study would lead to the production of student programs aimed to aid students with NCA factor profiles that predict lower performances. Finally we will present our recent efforts of deploying NCA-based interventions and their effectiveness.

Authors
  1. Christina Grigorian California Polytechnic State University, San Luis Obipso [biography]

    Christina Grigorian is a graduate student majoring in biomedical engineering at Cal Poly San Luis Obispo. She also completed her undergraduate degree in biomedical engineering at Cal Poly. Her graduate work involves the commercialization of medical devices made at Cal Poly. She joined this research team in 2019 and has thoroughly enjoyed researching engineering student success.

  2. Michelle Kerfs California Polytechnic State University, San Luis Obispo [biography]

    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 science but in her free time also loves running, hiking, and any type of arts and crafts.

  3. Jocelyn Paula Gee California Polytechnic State University, San Luis Obispo [biography]

    Jocelyn Gee is a third year student at Cal Poly, San Luis Obispo pursuing a Bachelor's degree in Statistics. Jocelyn has recently joined the team and has assisted with the statistical analyses on the survey data. She is excited to be a part of the team and have the opportunity to apply her statistical skills while also learning more about engineering education.

  4. Dr. James M. Widmann California Polytechnic State University, San Luis Obispo [biography]

    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

  5. Dr. John Chen P.E. California Polytechnic State University, San Luis Obispo [biography]

    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 stu

  6. Dr. Brian P. Self California Polytechnic State University, San Luis Obispo [biography]

    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 sev

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