Date

3-10-2026

Department

School of Education

Degree

Doctor of Philosophy in Higher Education Administration (PhD)

Chair

Nathan Street

Keywords

artists, annual income, education, entrepreneurship, entrepreneurial knowledge and skills, income satisfaction, success

Disciplines

Art and Design | Arts and Humanities

Abstract

The purpose of this quantitative, predictive correlational study was to determine how accurately income satisfaction could be predicted from a linear combination of annual income and inclusion of entrepreneurial knowledge and skills curricula in liberal arts education programs among public college graduates within the past ten years. A purposive sample of 87 graduates was drawn from universities with established art programs who graduated one to ten years ago. The planned behavior theory formed the logic model that guided the thought process, attitude, and reasoning behind this study. The research instrument, The Strategic National Arts Alumni Project: Survey Questionnaire, served as the instrument used to measure income and income satisfaction. The study was conducted through an online survey. Each participant was able access the survey remotely from the personal device of the participant's choice. Data were analyzed using descriptive statistics, collinearity diagnostics, and multiple regression analysis to test the predictive power of the independent variables. Results indicated that the combined predictors did not significantly explain variance in income satisfaction, and the null hypothesis was not rejected.This study was limited by its reliance on proxy indicators of entrepreneurial knowledge and skills, a cross-sectional design, self-reported data, and purposive sampling, all of which restricted causal inference and generalizability. In conclusion, the study determined that entrepreneurial education, as measured in this context, was not a significant predictor of income satisfaction among graduates. Future research should directly measure entrepreneurial education, use longitudinal methods, and consider factors such as job-person fit, mentorship, professional identity, and student loan debt to better understand income satisfaction.

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