The purpose of this ex post facto study was to describe completers and non-completers of associate’s degree programs in engineering and engineering technologies and determine whether and to what extent completion in these programs is a function of selected student-related variables and institutional variables. Data from the 2004/2009 Beginning Postsecondary Students Longitudinal Study (BPS: 04/09) of associate’s degree completers and non-completers in engineering and engineering technologies were accessed and analyzed through PowerStats, a web-based data analysis tool from National Center for Education Statistics (NCES). Descriptive data indicated that, proportionally, engineering and engineering technologies completers were mostly White, married, middle income, employed part-time, enrolled full-time, did not hold a high school diploma or certificate, completed Trigonometry/Algebra II, had a father who’s highest education level was an associate’s degree, but did not know their mother’s highest level of education, completed remedial coursework, and started college with the goal of earning an associate’s degree. While more males enrolled in the programs, males and females demonstrated similar completion rates, proportionally- with females showing a slightly higher percentage of completion. Results from the logistic regression further indicated that the variables significant to completion in associate’s degree programs in engineering and engineering technologies were gender and enrollment size. Findings suggested that female students were more likely to earn the degree, and that the larger the institution, the more likely the student would become a completer. However, since a major limitation of the study was the small weighted sample size, the results of the study are inconclusive in terms of the extent to which the findings can be generalized to the population of students in associate’s degree programs in engineering and engineering technologies. This study fills a gap in the literature of what is known about engineering and engineering technician students. It also contributes to the body of research on an understudied STEM educational and professional pathway, the associate’s degree in engineering and engineering technologies.

The present study examined the extent to which the U.S. STEM labor market is stratified in terms of quality of employment. Through a series of cluster analyses and Chi-square tests on data drawn from the 2008 Survey of Income Program Participation (SIPP), the study found evidence of segmentation in the highly-skilled STEM and non-STEM samples, which included workers with a subbaccalaureate diploma or above. The cluster analyses show a pattern consistent with Labor Market Segmentation theory: Higher wages are associated with other primary employment characteristics, including health insurance and pension benefits, as well as full-time employment. In turn, lower wages showed a tendency to cluster with secondary employment characteristics, such as part-time employment, multiple employment, and restricted access to health insurance and pension benefits. The findings also suggest that women have a higher likelihood of being employed in STEM jobs with secondary characteristics. The findings reveal a far more variegated employment landscape than is usually presented in national reports of the STEM workforce. There is evidence that, while STEM employment may be more resilient than non-STEM employment to labor restructuring trends in the new economy, the former is far from immune to secondary labor characteristics. There is a need for ongoing dialogue between STEM education (at all levels), employers, policymakers, and other stakeholders to truly understand not only the barriers to equity in employment relations, but also the mechanisms that create and maintain segmentation and how they may impact women, underrepresented minorities, and the foreign-born.