An Examination of Undergraduate Credit Hour Tuition Models at Four-Year Public and Not-for-Profit, Private Higher Education Institutions in the United States
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| Publicado en: | ProQuest Dissertations and Theses (2025) |
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| Acceso en línea: | Citation/Abstract Full Text - PDF |
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| 035 | |a 3248493166 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
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| 100 | 1 | |a Hacker, Ethan Glen | |
| 245 | 1 | |a An Examination of Undergraduate Credit Hour Tuition Models at Four-Year Public and Not-for-Profit, Private Higher Education Institutions in the United States | |
| 260 | |b ProQuest Dissertations & Theses |c 2025 | ||
| 513 | |a Dissertation/Thesis | ||
| 520 | 3 | |a This dissertation examines credit hour tuition models, a type of tuition policy designed to influence student course load behavior. It investigates the broader landscape of undergraduate credit hour tuition policies across U.S. public and private not-for-profit 4-year institutions. It explores the predictive relationship between state- and institutional-level factors and the selection of these tuition models. The study applies the demand theory, resource dependency theory, and the revenue theory of cost to interpret findings.Quantitative methods, including descriptive and data analysis, are utilized. Descriptive approaches involve tabulations and cross-tabulations to examine credit hour tuition model utilization and explore relationships between tuition models and various state and institutional factors. Binary logistic regression analysis assesses whether these factors predict the adoption of fixed fee or incremental credit hour tuition models.Data collection was conducted through a web survey, yielding 195 responses with a 11.7% response rate. A total of 158 institutions were included in the final analysis after excluding institutions considered out-of-scope and containing missing data. These 158 institutions, combined with data from the Integrated Postsecondary Educational Data System (IPEDS) and other sources, are leveraged to respond to research questions.Results showed that 83.5% of the sample used a fixed fee model, aligning with credit hour literature, while only 16.5% employed incremental models. Cross-tabulated findings revealed that 92.3% of institutions using incremental models were public, while 97.3% of private, not-for-profit institutions used fixed fee models. The binary logistic regression model was statistically significant; however, none of the state or institutional variables were significant predictors of tuition model selection. Institutional control came closest to significance with a p value of .088.This study contributes to the limited research on credit hour tuition policy in higher education and suggests avenues for future research. Further studies could investigate other units of analysis, trends, the effectiveness of credit hour tuition policies, and the motivations for their adoption. Insights from this study and future research can inform policymakers and influencers in various spaces about tuition policies impacting students and institutions alike. | |
| 653 | |a Higher education administration | ||
| 653 | |a Higher education | ||
| 653 | |a Education finance | ||
| 653 | |a Educational administration | ||
| 653 | |a Instructional design | ||
| 773 | 0 | |t ProQuest Dissertations and Theses |g (2025) | |
| 786 | 0 | |d ProQuest |t ProQuest Dissertations & Theses Global | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3248493166/abstract/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3248493166/fulltextPDF/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |