Date of Award

May 2015

Degree Type

Dissertation

Degree Name

Doctor of Philosophy

Department

Communication

First Advisor

Nancy Burrell

Keywords

CMC, Course Design, Instructional Design, Learning, Online Instruction, Online Learning

Abstract

Traditionally, research that has examined online courses compared course modes, online and face-to-face (f2f). Studies tend to examine the two modes to determine whether online courses are as effective as online courses by comparing student outcomes, such as student learning and satisfaction. Seldom has research examined how the course communication in online and f2f courses impact student outcomes. Moreover, there is little examination of the relationship between the design of the course and the relationship with social processes, in particular, communication. In this study, t-tests indicated that there were no significant differences between antecedents (technological familiarity and instructional characteristics) and outcomes variables (learning, performance, and satisfaction) between online or face-to-face courses. However, there were significant differences in course communication constructs including richness, social presence, learning community, and active learning behaviors. Multiple regression analyses indicated assessment and evaluation in instructional characteristics explained 36% of the variance in social presence, 42% of the variance in richness, and 27% of the variance in a learning community. Two components in instructional characteristics, organization and instructional design and course support, did not contribute to the model predicting these communication variables. However, they did predict 55% of the variance in engagement. Assessment and evaluation did not contribute to the model for predicting engagement. Assessment and evaluation are key factors in predicting communication variables where organization and instructional design and course support are a key factor in predicting engagement. Finally, multiple regression analyses indicated that 67% of the variance of learning can be predicted by communication variables of social presence, richness, engagement, and learning community, 52% of the variance of performance can be predicted by richness and engagement, 72% of the variance of satisfaction can be predicted by richness, engagement, and presence. Self-reported active learning behaviors did not predict learning, performance, or satisfaction.

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