Date of Completion
Vocational Interest, RIASEC, Creativity, Domain-General, Domain-Specific, Hierarchical Linear Regression, Latent Profile Analysis, ANOVA
James C. Kaufman
Melissa A. Bray
Field of Study
Doctor of Philosophy
Creativity has potential as a key element in understanding students’ vocational interests but has yet to be fully studied. Two questions were proposed: (1) Can potential predictors (demographics, academic achievements, domain-general and domain-specific creativity factors, and the interactions between gender and creativity-related factors) significantly predict vocational interests as derived from Holland’s RIASEC Model and (2) do domain-general and domain-specific creativity factors exhibit differential mean levels across distinct latent vocational profiles?
This dissertation drew on a dataset that collected 4,052 valid responses from grade 9 to 12 students who registered American College Testing (ACT) in the United States for the June 9, 2018. A series of Hierarchical Linear Regression analyses were conducted to answer question one, whereas Latent Profile Analysis (LPA) and univariate ANOVA analyses were used to answer question two. For question one of predicting vocational interests, the findings indicated that gender and ACT were better predictors than ethnicity and GPA. Creativity-related factors provided more significant effects than did demographics and academic achievements. Although interaction factors indicated small changes, some significant effects were found when predicting Realistic, Investigative, Artistic, Social, and Conventional. Compared to other interests, Artistic was best explained by creativity-related factors.
For question two, LPA generated eight profiles: Disinterested All, Interested-Social-Enterprising, Interested-Social, Interested-All, Neutral, Interested-Investigative-Social, Disinterested-Realistic-Conventional-Enterprising, and Disinterested-Realistic-Investigative-Artistic. Post-hoc multiple comparisons showed that the Neutral and disinterested-related profiles received lower scores on creativity-related measures and the Interested-All profile provided the highest scores. Among the three Interested-Social related profiles, domain-specific creativity factors provided more differentiated interpretation than domain-general creativity.
Liu, Xiaochen, "Domain-Specific Creativity and Vocational Interests: How Do Creativity and Related Factors Relate to Vocational Interests and Different Latent RIASEC Profiles?" (2020). Doctoral Dissertations. 2589.