Effects of Motivational Beliefs and Instructional Practice on Students' Intention to Pursue Majors and Careers in Engineering

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Virginia Tech


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.



Domain Identification Model, Engineering Identification, Structural Equation Modeling (SEM), STEM, MUSIC Model, Major Intention, Career Intention