The purpose of this study was to analyze the use of a course management system in relation to faculty characteristics and instructional environments at a rural community college in California. The use of the course management system, Blackboard, was the technology studied. This study used a nonexperimental quantitative ex post facto research design to analyze the use of Blackboard at all classes in fall semester 2008. This study used 10 faculty characteristics and five instructional environment conditions as the independent variables and the basis for analyses. The 10 faculty characteristics were age, gender, highest degree earned, discipline, number of faculty teaching in the discipline, number of courses teaching by an individual faculty member, average class size, number of years teaching, employment status, and hourly pay rate. The five instructional environmental conditions were teaching location, course delivery method, course type, career technical education status and course duration. The dependent variable was the use of a course management system. Elements of the course management system were placed into four general categories—activated, static, interactive and multimedia. Pearson's correlation analyses were calculated to identify any significant relationships between faculty characteristics and use of a course management system and between instructional environmental conditions and the use of a course management system. Cramer's V was used to determine the strength of those relationships. Faculty who were female, had more formal education, were tenured, earned more money, taught on campus, taught online or taught for the fill semester were more likely to use a course management system. There were moderate to strong relationships for faculty who were female, had more formal education, were tenured, earned more money, taught on campus, or taught online. Institutions of higher education are investing fiscal, human and technological resources in the purchase and deployment of course management systems. This study can be replicated by any college that has the ability to gather information about faculty and their use of a technology. Once the method by which the data is collected is determined, it can be repeated at regular intervals in order to track the progress of the adoption of the technology. This data can then be used by college leaders as an evaluative tool within the college's planning processes.

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In higher education institutions, virtual learning systems (VLSs) have been adopted, and are becoming increasingly popular among educators. However, despite this ubiquity of VLS use, there has not been widespread change in pedagogic practice to take advantage of the functionality afforded by VLSs. Knowledge of the actual usage of e-learning systems is limited in terms of what specific feature sets are deemed useful, and how this influences system usage. VLSs have a suite of tools with associated functions/features and properties, as well as non-functional system characteristics. In addition, these systems incorporate pedagogic features to cater for online teaching. Educators in higher education, who are the chief agents of e-learning, are confounded by system-related, pedagogic, organisational, user difference and demographic factors that influence VLS usage. Virtual learning system usage involves system feature usage extent and frequency, total system usage and usage clusters. The aim of this study is to develop a model representing the factors that influence usage of VLSs in higher education. The links between system usage and system-related factors, pedagogic factors, organisational factors, user-difference and demographic factors is researched. This research incorporated a literature study, a pilot study, interviews and surveys. A case study research strategy was combined with a mixed methods research design. The results of the qualitative analysis was triangulated with the findings of the quantitative analysis and compared to the findings of the literature study. The study was conducted at two residential higher education institutions (HEI), namely, University of KwaZulu-Natal and Durban University of Technology. The main contribution of this study is the Virtual Learning System Usage Model (VLSUM) representing the factors that influence VLS usage in residential higher education institutions. The proposed VLSUM is based on the empirical results of this study. VLSUM can be used by managers of educational technology departments and instructional designers to implement interventions to optimize usage. The constructs of VLSUM confirmed existing theories, replicated and synthesised theories from different fields, and extended existing models to produce a new model for understanding the factors that influence VLS usage in higher education. / Computing / D. LITT. et. Phil. (Information Systems)

In higher education institutions, virtual learning systems (VLSs) have been adopted, and are becoming increasingly popular among educators. However, despite this ubiquity of VLS use, there has not been widespread change in pedagogic practice to take advantage of the functionality afforded by VLSs. Knowledge of the actual usage of e-learning systems is limited in terms of what specific feature sets are deemed useful, and how this influences system usage. VLSs have a suite of tools with associated functions/features and properties, as well as non-functional system characteristics. In addition, these systems incorporate pedagogic features to cater for online teaching. Educators in higher education, who are the chief agents of e-learning, are confounded by system-related, pedagogic, organisational, user difference and demographic factors that influence VLS usage. Virtual learning system usage involves system feature usage extent and frequency, total system usage and usage clusters. The aim of this study is to develop a model representing the factors that influence usage of VLSs in higher education. The links between system usage and system-related factors, pedagogic factors, organisational factors, user-difference and demographic factors is researched. This research incorporated a literature study, a pilot study, interviews and surveys. A case study research strategy was combined with a mixed methods research design. The results of the qualitative analysis was triangulated with the findings of the quantitative analysis and compared to the findings of the literature study. The study was conducted at two residential higher education institutions (HEI), namely, University of KwaZulu-Natal and Durban University of Technology. The main contribution of this study is the Virtual Learning System Usage Model (VLSUM) representing the factors that influence VLS usage in residential higher education institutions. The proposed VLSUM is based on the empirical results of this study. VLSUM can be used by managers of educational technology departments and instructional designers to implement interventions to optimize usage. The constructs of VLSUM confirmed existing theories, replicated and synthesised theories from different fields, and extended existing models to produce a new model for understanding the factors that influence VLS usage in higher education. / Computing / D. LITT. et. Phil. (Information Systems)