Adesope, O., & Sunday, O. J., & Ewumi, E. R., & Minichiello, A., & Asghar, M., & Claiborn, C. S. (2021, July), Investigating Factors that Predict Academic Success in Engineering and Computer Science  Paper presented at 2021 ASEE Virtual Annual Conference Content Access, Virtual Conference. 10.18260/1-2--37393

\bibitem{asee_peer_37393}
  Adesope, O., \& Sunday, O. J., \& Ewumi, E. R., \& Minichiello, A., \& Asghar, M., \& Claiborn, C. S. (2021, July), \emph{Investigating Factors that Predict Academic Success in Engineering and Computer Science}
  Paper presented at 2021 ASEE Virtual Annual Conference Content Access, Virtual Conference.
  10.18260/1-2--37393

Olusola Adesope, Oluwafemi J. Sunday, Ebenezer Rotimi Ewumi, Angela Minichiello P.E., Muhammad Asghar P.E., and Candis S. Claiborn.  "Investigating Factors that Predict Academic Success in Engineering and Computer Science".  2021 ASEE Virtual Annual Conference Content Access, Virtual Conference, 2021, July.  ASEE Conferences, 2021.  https://peer.asee.org/37393 Internet.  18 Apr, 2024

\bibitem{asee_peer_37393}
  Olusola Adesope, Oluwafemi J. Sunday, Ebenezer Rotimi Ewumi, Angela Minichiello P.E., Muhammad Asghar P.E., and Candis S. Claiborn.
  "Investigating Factors that Predict Academic Success in Engineering and Computer Science".
  \emph{2021 ASEE Virtual Annual Conference Content Access, Virtual Conference, 2021, July}.
  ASEE Conferences, 2021.
  https://peer.asee.org/37393 Internet.  18 Apr, 2024

@INPROCEEDINGS{asee_peer_37393
author = "Olusola Adesope, Oluwafemi J. Sunday, Ebenezer Rotimi Ewumi, Angela Minichiello P.E., Muhammad Asghar P.E., and Candis S. Claiborn"
title = "Investigating Factors that Predict Academic Success in Engineering and Computer Science"
booktitle = "2021 ASEE Virtual Annual Conference Content Access"
year = "2021"
month = "July"
address = "Virtual Conference"
publisher = "ASEE Conferences"
note = {https://peer.asee.org/37393}
number = {10.18260/1-2--37393}
}

TY  - CPAPER
AB  - Over the years, researchers have found that student engagement facilitates  desired academic success outcomes for college undergraduate students. Much research on student engagement has focused on academic tasks and classroom context. High impact engagement practices (HIEP) have been shown to be effective for undergraduate student academic success. However, less is known about the effects of HIEP specifically on engineering and computer science (E/CS) student outcomes.  Given the high attrition rates for E/CS students, student involvement in HIEP could be effective in improving student outcomes for E/CS students, including those from various underrepresented groups. 

More generally, student participation in specific HIEP activities has been shown to shape their everyday experiences in school, both academically and socially. Hence, the primary goal of this study is to examine the factors that predict academic success in E/CS using multiple regression analysis. Specifically, this study seeks to understand the effects of high impact engagement practices (HIEP), coursework enjoyability, confidence at completing a degree on academic success of the underrepresented and nontraditional E/CS students. We used exploratory factor analyses to derive “academic success” variable from five items that sought to measure how students persevere to attain academic goals. 

A secondary goal of the present study is to address the gap in research literature concerning how participation in HIEP affects student persistence and success in E/CS degree programs. Our research team developed and administered an  online survey to investigate and identify factors that affect participation in HIEP among underrepresented and nontraditional E/CS students. Respondents (N = 531) were students enrolled in two land grant universities in the Western U.S. Multiple regression analyses were conducted to examine the proportion of the variation in the dependent variable (academic success) explained by the independent variables (i.e., high impact engagement practice (HIEP), coursework enjoyability, and confidence at completing a degree). We hypothesized that (1) high impact engagement practices will predict academic success; (2) coursework enjoyability will predict academic success; and (3) confidence at completing a degree will predict academic success. Results showed that the multiple regression model statistically predicted academic success , F(3, 270) = 33.064, p = .001, adjusted R2 = .27. This results indicate that there is a linear relationship in the population and the multiple regression model is a good fit for the data.

Further, findings show that confidence at completing a degree is significantly predictive of academic success. In addition, coursework enjoyability is a strong predictor of academic success.  Specifically, the result shows that an increase in high impact engagement activity  is associated with an increase in students’ academic success. In sum, these findings suggest that student participation in High Impact Engagement Practices might improve academic success and course retention. Theoretical and practical implications are discussed.


AU  - Olusola Adesope
AU  - Oluwafemi J. Sunday
AU  - Ebenezer Rotimi Ewumi
AU  - Angela Minichiello P.E.
AU  - Muhammad Asghar P.E.
AU  - Candis S. Claiborn
CY  - Virtual Conference
DA  - 2021/07/26
PB  - ASEE Conferences
TI  - Investigating Factors that Predict Academic Success in Engineering and Computer Science
UR  - https://peer.asee.org/37393
DO  - 10.18260/1-2--37393
ER  -