Off-campus WSU users: To download campus access dissertations, please use the following link to log into our proxy server with your WSU access ID and password, then click the "Off-campus Download" button below.

Non-WSU users: Please talk to your librarian about requesting this dissertation through interlibrary loan.

Access Type

WSU Access

Date of Award

January 2021

Degree Type

Dissertation

Degree Name

Ed.D.

Department

Educational Leadership and Policy

First Advisor

Ben Pogodzinski

Abstract

ABSTRACTEXAMINING ACADEMIC AND DEMOGRAPHIC CHARACTERISTICS TO RETAIN AND GRADUATE ENGINEERING STUDENTS AT A MID-WESTERN PUBLIC UNIVERSITY

Demand is high for engineering students and educators must identify factors affecting persistence and graduation of engineers. Retention and graduation rates remain problematic for many institutions. Higher education research focuses on these two issues as many students head to engineering programs with a wide range of attributes, characteristics, and abilities. This study focused on the retention and graduation rates of a Midwestern Urban University’s (MUU) College of Engineering students. Two cohorts of FTIAC (First Time In Any College) students, those starting in Fall 2007 and Fall 2013, were examined for pre-admission variables of academic preparation and demographic characteristics predicting first year retention and graduation. A quantitative analysis compared these two groups, in addition to a subset of at-risk pre-engineering students, to determine if there were significant predictors of persistence or non-persistence in the engineering college.The research design was quantitative with a logistic regression analysis applied to determine relationship among the independent variables (pre-admission, demographic and post-admission characteristics) and first year retention and graduation. Initial questions in the study addressed the association between the different admissions policies and retention and graduation of the two cohorts of engineering students. In addition, academic and demographic characteristics associated with graduation across the two cohorts was examined. The second part of this study examined two at-risk pre-engineering FTIAC student groups (Fall 2007 group was labelled the Bridge group while the Fall 2013 group was labelled the EOS group. Research questions guiding this subset group’s retention and graduation factors examined participation in these two groups and first year retention in and graduation from the Engineering program. Descriptive and inferential statistical analysis of the institutional data collected uncovered several factors predictive of first year retention and graduation. Generally, graduation rates showed noticeable increases in Fall 2013 versus Fall 2007 cohort which could be attributed to the increased standards in admission for the Fall 2013 cohort. Analyses of the research questions showed that if a student was retained in the first year, their graduation rate increased from 45% to 65% from Fall 2007 to Fall 2013; and if they took Calculus in their first year they graduated at a higher rate in Fall 2013 (51% to72%). Strikingly lesser number of African American students graduated in Fall 2013 (from 11% to 3%). Logistic regression analysis showed statistically significant results for first year retention of Bridge or EOS students if they took Calculus 1 or higher in the first year.For graduation from Engineering, the same regression analysis showed that having a HSGPA between 3.0 and 4.0 and taking their first math class at Calculus 1 or higher in the first term proved statistically significant for the Fall 2007 students. For the Fall 2013 cohort, completing Calculus 1 in the first year was the only statistically significant predictor for graduation. Students taking Calculus 1 in the first year was determined to be a statistically significant predictor of retention and graduation in the study. The findings from this study provide valuable information for engineering leaders within enrollment management and academic affairs. The models developed for predicting persistence based on HSPGA and math level can be used by advisors in focusing retention efforts and by deans for making resource allocation decisions. Based on the results in this study of freshman engineering student retention, where Calculus 1 was identified to be a significant factor, faculty members, administrators, advisors, and essentially anyone involved in the process of freshman engineering curriculum can use the predictor factors to identify students in jeopardy of being retained in engineering.

Off-campus Download

Share

COinS