ONE YEAR PERSISITENCE AND THREE YEAR GRADUATION OF ADULT STUDENTS AGE 30 TO 39 YEARS AT A FOUR YEAR PUBLIC INSTITUTION
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Higher education is a transformational process which assists adults age 30-39 years to address globalization of the work force, human resource development and re-tooling of skill sets, and a personal desire to join a learning community. Even though the number of adult students enrolling in higher education is predicted to increase nationally, a four year, public institution located between two metropolitan areas in the southwest has had a decrease in the percentage of students who are age 30-39 years over the past 10 years. Path analysis models were developed to evaluate the relationships between background characteristics: gender, ethnicity, first generation status and age, with academic integration: decision grade point average and enrollment pattern, and the dichotomous, endogenous parameters: one year persistence and three year graduation. The samples are drawn from four consecutive semesters. For each cohort of students age 30-39 years, a one to one comparative matched cohort of students from the same semester but were age 20-29 years was selected. Due to the categorical nature of the data and the limited sample size (n = 115; 60; 125; 69), Bayesian statistical analyses were used to calculate path coefficients and standard effects for each relationship. Directional hypotheses testing were conducted. To provide greater insight into the practical application to the models, the effect size and variance explained by the paths in the models were calculated. Little statistically significant results resulted from the analyses. However, the parameters of gender, ethnicity and first generation status along with decision grade point average provided practical significance. The results of the study do not indicate age is a factor in the persistence or graduation of adult students age 30-39 years. The practical significance for the other background characteristics and decision grade point average are supported by the literature as parameters to consider as contributing to the overall model. Additional quantitative and qualitative data will need to be collected to build more robust models.