Electronic Theses and Dissertations



Document Type


Degree Name

Doctor of Education



Committee Chair

Andrew Tawfik

Committee Member

Amanda Rockinson-Szapkiw

Committee Member

Scott Vann

Committee Member

Jenny B Jones

Committee Member

Clif Mims


With the increase in online course enrollments each year, there is a continued examination of online course persistence, particularly in accelerated online courses. This examination of online course persistence has typically examined individual learner factors as contributors to persistence. However, research examining the institutional and pedagogical factors of persistence can continue to further understanding what factors lead to learner persistence decisions. The purpose of this quantitative, predictive correlational study is to examine to what extent, if any, community college learners’ perceived online course cognitive load and motivation predict persistence in an accelerated online course. The theoretical framework for this study includes Cognitive Load Theory and Self-Determination Theory as predictive elements within a persistence model influenced by Rovai’s 2003 synthesis of Tinto’s Integration Framework and Bean and Metzner’s conceptual models. However, the model of this study uses these predictive elements with a focus on course design as a predictor for persistence. The perceived cognitive load includes extraneous, intrinsic, and germane load. Online course motivation includes extrinsic motivation, intrinsic motivation, and amotivation. Results from a binary logistic regression show a statistically significant model of persistence, including the interplay of cognitive load and motivation as a predictor for persistence. Germane cognitive load, intrinsic, and extrinsic motivation showed individual significance within the model. Findings suggest that cognitive and affective factors of course design can lead to learner persistence in accelerated online asynchronous courses. Further discussion of theoretical and practical implications are discussed, as well as limitations and areas of future research.


Data is provided by the student.

Library Comment

Dissertation or thesis originally submitted to ProQuest.


Open access