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Predicting Engineering Student Success: An Examination of College Entrance Exams, High School GPA, Perceived Competence, Engineering Achievement, and Persistence

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Conference

2020 ASEE Virtual Annual Conference Content Access

Location

Virtual On line

Publication Date

June 22, 2020

Start Date

June 22, 2020

End Date

June 26, 2021

Conference Session

Data-informed Approaches to Understanding Student Experiences and Outcomes

Tagged Division

Educational Research and Methods

Tagged Topic

Diversity

Page Count

10

DOI

10.18260/1-2--35072

Permanent URL

https://strategy.asee.org/35072

Download Count

236

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Paper Authors

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Harrison Douglas Lawson Michigan State University Orcid 16x16 orcid.org/0000-0002-0946-2354

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Harrison Lawson is a graduate student pursuing his M.S. of Chemical Engineering at Michigan State University. He completed his undergraduate studies in chemical engineering at the University of Pittsburgh. He plans to continue his doctoral studies at Carnegie Mellon University. His research interests include drug delivery, cell biology, and STEM education. He aspires to become a university faculty member.

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Amalia Krystal Lira Michigan State University

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Amalia (Krystal) Lira is a doctoral student in Educational Psychology and Educational Technology at Michigan State University. She is interested in addressing STEM attrition among underrepresented racial and ethnic minority students using motivational frameworks.

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Alexandra A. Lee Michigan State University

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Minhye Lee Daegu National University of Education

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Minhye Lee is an assistant professor of educational psychology at Daegu National University of Education. Her research interests are about how to enhance student academic motivation in STEM domains throughout supports from teachers, programs, and institutions.

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Lisa Linnenbrink-Garcia Michigan State University

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Dr. Lisa Linnenbrink-Garcia is a Professor of Educational Psychology in the Department of Counseling, Educational Psychology, and Special Education at Michigan State University. She received her Ph.D. in Education and Psychology from the University of Michigan, Ann Arbor. Her research focuses on the development of achievement motivation in educational settings and the interplay among motivation, emotions, and learning, especially in STEM fields.

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S. Patrick Walton Michigan State University

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S. Patrick Walton is the Associate Chair and C. Robert and Kathryn M. Weir Endowed Associate Professor in the Department of Chemical Engineering and Materials Science at Michigan State University. He received his bachelors in chemical engineering from Georgia Tech, and then attended MIT where he received his masters and doctoral degrees. After a post-doc at Stanford University, he joined MSU in 2004 where his research is focused on the development of novel therapeutic and diagnostic technologies based upon the unique physical and chemical properties of nucleic acids. He is also engaged in studying engineering student persistence and success through the lens of motivation. He has been recognized for his accomplishments in both teaching and research, receiving the MSU Teacher-Scholar award, the College of Engineering Withrow Teaching Excellence Award and being named an MSU Lilly Teaching Fellow and MSU's Undergraduate Research Faculty Mentor of the Year.

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Daina Briedis Michigan State University

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DAINA BRIEDIS is a faculty member in the Department of Chemical Engineering and Materials Science at Michigan State University and Assistant Dean for Student Advancement and Program Assessment in the College of Engineering. Dr. Briedis is involved in several areas of education research including student retention and the use of technology in the classroom. She has been involved in NSF-funded research in the areas of integration of computation in engineering curricula and in developing comprehensive strategies to retain early engineering students. She is active nationally and internationally in engineering accreditation and is a Fellow of ASEE, ABET and of the AIChE.

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Abstract

This Work in Progress seeks to better understand what relates prior achievement to future achievement. College entrance exams, such as the ACT and SAT, and high school GPA (HSGPA) are commonly used for college admission decisions because they are believed to predict achievement. While HSGPA tends to be a consistent predictor of achievement, prior studies have conflicting results as to whether or not college entrance exams predict academic achievement in engineering, especially beyond students' first year of college [1] - [7]. In Expectancy-Value Theory, Eccles and Wigfield suggest that perceived competence may be an important mechanism relating prior achievement and future academic success and persistence [8]. Examining this psychological mechanism may improve the understanding of how prior achievement and perceived competence influence engineering achievement and persistence [9]. Furthermore, it is unclear if a students' racial group membership affects how entrance exam scores and HSGPA predict future achievement and persistence [10], [11]. As engineering student populations often do not reflect the diversity of student bodies as a whole, it is also important to consider the social pressures minoritized students face that may deflate or inflate their perceived competence, and in turn affect their achievement and persistence [11],[12].

In this work in progress, we are addressing the following research questions: 1) How are college entrance exam scores and HSGPA related to changes in perceived competence and in turn related to college GPA, degree attainment, persistence, and career intentions among engineering students? 2) Do the relations in the overall model vary among White, Asian, and minoritized students (i.e., Black and Latinx)? We hypothesize that prior academic achievement will be related to growth (or less reduction) in perceived competence, and, in turn, will predict academic achievement. Additionally, we hypothesize that minoritized students will have differential relations among prior achievement, changes in perceived competence, and future achievement [3],[11].

The present study uses longitudinal data from a large, public, midwestern university. Specifically, our sample includes approximately 900 engineering students (25.8% Female, 20.5% Asian, 64.6% White, and 14.9% minoritized students). The data include institutional academic data (to measure achievement and persistence) and self-reported measures of perceived competence in engineering across four years of college. We are testing a latent growth model to determine the trajectory of engineering students’ perceived competence as a function of college entrance exams and HSGPA over four years. Initial descriptive analyses indicated that college entrance exams and HSGPA are correlated with students’ perceived competence and achievement. However, mean scores of students’ perceived competence showed declines over time.

This study begins to address gaps in the engineering education literature, where few studies examine motivational constructs or longitudinal data [9]. Furthermore, understanding how perceived competence changes over time will inform interventions, curriculum design, or teaching practices that aim to support engineering student motivation, persistence, and achievement. In addition to understanding how prior achievement relates to the trajectory of students’ perceived competence and engineering persistence, this study will provide new insight about minoritized students’ sense of perceived competence in engineering.

References

[1] S. Katz, G. J. Lautenschlager, A. B. Blackburn, and F. H. Harris, “Answering Reading Comprehension Items without Passages on the SAT,” Psychol. Sci., vol. 1, no. 2, pp. 122–127, Mar. 1990. [2] R. Zwick and J. Greif Green, “New Perspectives on the Correlation of SAT Scores, High School Grades, and Socioeconomic Factors,” J. Educ. Meas., vol. 44, no. 1, pp. 23–45, Mar. 2007. [3] T. Abdel-Salam, P. Kauffmann, and K. Williamson, “A case study: DO high school GPA/ SAT scores predict the performance of freshmen engineering students?,” Proc. - Front. Educ. Conf. FIE, vol. 2005, pp. 7–11, 2005. [4] B. F. French, J. C. Immekus, and W. Oakes, “A structural model of engineering students success and persistence,” Proc. - Front. Educ. Conf. FIE, vol. 1, p. T2A19-T2A24, 2003. [5] S. D. Brown, S. Tramayne, D. Hoxha, K. Telander, X. Fan, and R. W. Lent, “Social cognitive predictors of college students’ academic performance and persistence: A meta-analytic path analysis,” J. Vocat. Behav., vol. 72, no. 3, pp. 298–308, 2008. [6] J. C. F. De Winter and D. Dodou, “Predicting academic performance in engineering using high school exam scores,” Int. J. Eng. Educ., vol. 27, no. 6, pp. 1343–1351, 2011. [7] Brenda Hannon, “Predicting College Success: The Relative Contributions of Five Social/Personality Factors, Five Cognitive/Learning Factors, and SAT Scores,” J Educ Train Stud., no. 1, pp. 1–7, 2015. [8] J. S. Eccles and A. Wigfield, “Motivational Beliefs, Values, and Goals,” Annu. Rev. Psychol., vol. 53, no. 1, pp. 109–132, Feb. 2002. [9] National Academies of Sciences, Engineering, “Supporting students’ college success: Assessment of intrapersonal and interpersonal competencies. Board on Testing and Assessment, Division of Behavioral and Social Sciences and Education.,” 2016. [10] J. Fleming and C. Morning, “Correlates of the SAT in Minority Engineering Students: An Exploratory Study,” J. Higher Educ., vol. 69, no. 1, p. 89, Jan. 1998. [11 E. McGee, “‘Black Genius, Asian Fail’: The Detriment of Stereotype Lift and Stereotype Threat in High-Achieving Asian and Black STEM Students,” AERA Open, vol. 4, no. 4, p. 233285841881665, Oct. 2018. [12] H. Garrison, “Underrepresentation by race-ethnicity across stages of U.S. science and engineering education,” CBE Life Sci. Educ., vol. 12, no. 3, pp. 357–63, 2013.

Lawson, H. D., & Lira, A. K., & Lee, A. A., & Lee, M., & Linnenbrink-Garcia, L., & Walton, S. P., & Briedis, D. (2020, June), Predicting Engineering Student Success: An Examination of College Entrance Exams, High School GPA, Perceived Competence, Engineering Achievement, and Persistence Paper presented at 2020 ASEE Virtual Annual Conference Content Access, Virtual On line . 10.18260/1-2--35072

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