Master's education is a quickly growing area of higher education that provides students higher lifetime earnings and lower levels of unemployment. Despite the benefits, the little research conducted over the past 20 years, using institutional, programmatic, and sociological student factors (e.g., age, race, and financial status) has had minimal success creating a universal model to understand what promotes the retention and graduation of master's students. C�t�'s identity capital model (ICM) holds that interactions of both sociological and agentic capital aid in the development of an individual's identity. While cultural capital is essential for building the foundation of identity, it is agentic capital that develops a strong sense of self, providing the ability to shift successfully between social contexts while remaining committed to life path goals despite inherent obstacles. The purpose of this study was to apply C�t�'s identity capital model to predict CACREP counseling and counseling psychology master's students' (n = 88) retention in their academic programs when the sociological factors of age and personal funding contributions were held constant. Using a quantitative, nonexperimental, survey study design, full-time students, in good standing, not enrolled in an online program completed the Multi-Measure Agentic Personality Scale20 assessment to measure the agentic characteristics of the ICM. The logistic regression analysis did not yield significant results, but data mining to discover data patterns did suggest future directions for research. A clearer understanding of the factors that promote retention could encourage institutions to create appropriate programmatic efforts to increase students' academic goal achievement and support their improved psychological well-being.
| Identifer | oai:union.ndltd.org:waldenu.edu/oai:scholarworks.waldenu.edu:dissertations-8616 |
| Date | 01 January 2019 |
| Creators | Smith, Tammison Rene |
| Publisher | ScholarWorks |
| Source Sets | Walden University |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Walden Dissertations and Doctoral Studies |
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