This dissertation examined the differences in group mean scores of traditional and pilot groups on the students' motivational beliefs and their intention to pursue majors and careers in engineering. The difference between the two groups was in terms of instruction techniques used. The instructional techniques used for the traditional group was that of traditional engineering design (TED), while the technique used for the pilot group had more features of an active learning approach. Further, it tested the tenability of the domain identification model. The domain identification model was used to understand students' decision-making processes in committing to engineering majors and engineering careers. The data for this study was collected via online survey from first-year engineering students enrolled in an introductory engineering course at a research-intensive university located in southeastern US. The sample sizes of the traditional group and pilot group at the beginning of the semester were 875 and 188, respectively. The sample sizes of the traditional group and pilot group at the end of the semester were 812 and 242, respectively. The mean differences between the two groups were computed using t-tests via SPSS version 22.0. The causality hypothesized among variables in the domain identification model were tested using structural equation modeling (SEM) techniques. The measurement and structural models were estimated using LISREL version 9.1. This study followed the two-step SEM approach that Anderson and Gerbing (1988) suggested. A measurement model with an acceptable fit to the data was obtained followed by an estimation and evaluation of structural models. All the independent sample t-tests were not statistically significant indicating that the mean scores of students in the two groups did not differ significantly on any of the motivational and intention variables. The hypothesized measurement and structural models provided a good fit to the data. A few post-hoc revisions were made to the models. This study brought empirical evidence that the domain identification model can be used to understand students' major-and career-decision making processes. Engineering identification was a better predictor of major intention and career intention compared to engineering program utility, engineering program belonging, and engineering program expectancy. / Ph. D.

This dissertation examined the extent to which pre-high school students' motivation-related perceptions of their science class affected their science identification, which sequentially affected their future science-related career goals. The MUSIC® Model of Motivation (Jones, 2009, 2018) includes five components (i.e., eMpowerment, Usefulness, Success, Interest, and Caring) and is designed to help teachers design instruction to promote students' motivation. Domain identification (Osborne and Jones, 2011) is a concept closely related to students' motivation and academic outcomes. In this study, data was collected from 311 pre-high school students and Structural Equation Modeling (SEM) analysis was conducted to test the structure pattern among the MUSIC model components, science identification, and science-related career goals. Results indicate that with three of the MUSIC model components (i.e., usefulness, success, and interest) significantly related to students' science identification, students' science identification was highly correlated to their science career goals. Moreover, this study demonstrated the structure patterns among the MUSIC model components and science identification varied by gender by conducting multi-group SEM analyses for a separate female sample (N = 161) and male sample (N = 150). Consistently, students' science identification was a strong predictor of their science career goals in both female and male groups. These findings are important for STEM educators because they indicate that it may be possible for teachers to impact students' science identification and career goals by focusing on students' perceptions of the MUSIC model components in science class. Moreover, these results contribute to the study of the large gender gap in STEM careers. Teachers can focus on specific teaching strategies and help female students develop their science identification in ways that lead to their long-term science-related career goals. / Ph. D.