Variables Related to Academic Success in Pre-Engineering for Students At Risk

Abstract

Undergraduate engineering enrollment has shown signs of stagnation. The American Society for Engineering Education reported that, from 2001 through 2004, national enrollment remained virtually unchanged: 96,426 in 2001 and 96,978 in 2004. There are numerous explanations for this trend. They include a lack of information about engineering careers for prospective students, academically under prepared high school graduates, and individual differences among students as related their ability to complete the curriculum, their study habits, their strategies for learning, and their ability to manage their time. Student attrition at all collegiate levels has also been recognized as a major factor impacting engineering enrollment. During the past decade research focused on pre-engineering students, and most of it targeted predictive variables related to persistence and attrition. However, a gap existed in the literature. What was missing was a study of pre-engineering students who persisted into major, despite being predicted to drop out of engineering. The purpose of this study was to examine the relationship between non-cognitive variables and persistence for at-risk pre-engineering students who persisted, or failed to persist, into upper level engineering studies. From pre-existent data collected on 2,276 freshman pre-engineering students for a 4-year period (2000-2003), 848 participants with an ACT mathematics score = 24 were determine to be at-risk students. Those with missing data were excluded, which resulted in 491 complete cases for analyses. Results from a discriminant analysis indicated that at-risk students who persisted differed significantly from those who did not on a weighted combination of non-cognitive variables. Bivariate analyses showed that six non-cognitive variables significantly correlated with group membership: academic self-concept, math, study habits, intrinsic motivation, academic success, and work ethic. These findings provide insight into at-risk students who succeed in engineering and can assist in the creation of specialized interventions for those who might not otherwise.