Identifying significant personal and program factors that predict online EdD students’ program integration

Abstract

Based on a synthesis of persistence theory and the empirical literature, an online doctoral program integration model was developed using data from 232 online EdD students. A predictive, correlation design and regression analysis were used to examine if personal factors (gender, race, age, marital status, and presence of children in the home) and program factors (stage in doctoral journey, synchronous interactions, cohorts, and orientations) could predict program integration. The entire model was significant. The variables of gender, race, participation in a cohort, and engagement in synchronous communication individually contributed to the variance in program integration.

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Online Learning Journal

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