CCE Theses and Dissertations

Date of Award

2012

Document Type

Dissertation

Degree Name

Doctor of Philosophy in Information Systems (DISS)

Department

Graduate School of Computer and Information Sciences

Advisor

Laurie P. Dringus

Committee Member

Eric S Ackerman

Committee Member

Steven R Terrell

Keywords

DeLone and McLean, E-Readiness, Online Instructor, Online Learning Environment, Technology Barriers, User Satisfaction

Abstract

A critical factor of e-learning success is the e-learning readiness of the online user. However, there is a scarcity of studies on online instructors' e-learning readiness (E-Readiness) in an online learning environment. The purpose of this study was to evaluate whether there were correlations among online instructor E-Readiness dimensions and factors at the design and delivery stages that affect system outcomes. In this study, the DeLone and McLean model was used as a framework for research to test E-Readiness with the System Design stage (comprising System Quality, Information Quality, and Service Quality), System Delivery stage (comprising System Use, and User Satisfaction) and Net Benefits stage (comprising Net Benefits).

A total of 113 online instructors at a Caribbean university system completed a Web-based questionnaire containing previously validated and adapted items. The questions were answered using a five-point Likert scale and the survey results were analyzed using aggregates and linear regression statistical methods. The results revealed that the e-learning systems success score of the university was 4.07 out of 5 or 81.4%, while the E-Readiness score of online instructors was 4.53 out of 5, or 90.6%. Linear regression analysis showed that E-Readiness was a significant and positive predictor of the System Design, System Delivery, and System Outcome stages and their associated dimensions. The results of multiple linear regression analysis showed that the constructs together accounted for 42.2% of the variance in Net Benefits. Of the six predictors in the model, User Satisfaction provided the largest unique contribution when the other predictors in the model were held constant. The other predictors in the model (System Quality, Service Quality, Information Quality, System Use and E-Readiness) were not statistically significant and provided no significant or unique contribution to Net Benefits. Further information is provided regarding factors affecting net benefits among online instructors using online learning environments. This information can be used to address online instructors' barriers to technology use.

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