Exploring College Engineering Students’ Choices, Effort, Persistence, and Continuation from Expectancy-Value Theory’s Perspective
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High attrition rate is one of the biggest challenges undergraduate STEM education faces (Gonzalez & Kuenzi, 2012). It is imperative for educators to understand the factors related to students’ choice, persistence, and continuation in engineering majors and careers (Eris et al., 2010; Lichtenstein et al., 2007; Lichtenstein et al., 2009). From the perspective of expectancy-value theory, this study sought to investigate how college engineering students’ perceptions (engineering self-efficacy, gender stereotype threat, and racial stereotype threat), expectancy for academic success in engineering, and engineering task values (attainment value, intrinsic value, utility value, and cost) relate to their choices (take more engineering courses in the future, delay, and miss deadlines), effort and persistence in engineering coursework, and continuation in the field of engineering. The researcher recruited 163 undergraduate engineering students from a large southern urban university who completed a paper-and-pencil survey in class. The researcher analyzed the data using IBM SPSS Statistics 22. The researcher created the Expectancy for Academic Success Scale based on the modified version of the Revised Generalized Expectancy for Success Scale (Hale, Fiedler, & Cochran, 1992) and used it in her candidacy research. In this dissertation, the researcher modified the Expectancy for Academic Success Scale and made it appropriate to use in engineering contexts. The modified scale was named as the Expectancy for Academic Success in Engineering Scale. Principle component analysis (PCA) with varimax rotation revealed a three-factor solution. The three factors are Expectancy for Successful Engineering Academic Relationships, Expectancy for Completion of Engineering Academic Tasks, and Expectancy for Completion of Engineering Education. PCA results showed that all the items had primary loadings over .7 and the communalities were all above .63. Analyses of the internal consistency yielded satisfactory results with adequate Cronbach’s alpha of .75, .94, and .89 for each scale respectively. Results showed that 1) academic level, self-reported GPA, and intrinsic value were negative predictors of delay; 2) self-reported GPA and expectancy for successful engineering academic relationships were negative predictors of missing deadlines, whereas cost was a positive predictor of missing deadlines; 3) academic level and stereotype threat were negative predictors of choice, whereas expectancy for completion of engineering academic tasks, expectancy for completion of engineering education, attainment value, and intrinsic value were positive predictors of choice; 4) academic level, expectancy for successful engineering academic relationships, expectancy for completion of engineering academic tasks, expectancy for completion of engineering education, intrinsic value, and cost were positive predictors of effort; 5) stereotype threat was a negative predictor of persistence, whereas academic level, self-reported GPA, and expectancy for completion of engineering academic tasks were positive predictors of persistence; and 6) underrepresented minority status was a negative predictor of continuation, whereas expectancy for completion of engineering academic tasks and expectancy for completion of engineering education were positive predictors of continuation.