This study describes common online facilitator strategies of seven expert online facilitators and compares these facilitators' decision-making processes to general strategies and characteristics of experts in other domains. Specifically, this study focuses on how expert online facilitators decide to communicate with discussion participants for the purposes of increasing participant knowledge and skills in college-level online courses. Seven expert online facilitators -- identified by authoritative figures -- detailed their decision-making and composition process. Common facilitation strategies emerged from the interview data and contextual information. These common strategies were compared with characteristics and strategies of experts in other domains. Analysis of the data indicates that the participating facilitators: (a) share common decision-making strategies, and (b) demonstrate characteristics that align to characteristics of experts in other domains. / text

Research findings have shown that online learning has the potential to improve the quality of learning if it is designed effectively to embrace interactive, collaborative knowledge building among learners. Online learning has the capacity to facilitate efficient and enjoyable learning through skills acquisition in a context specific environment especially in Southern Africa but there are a number of challenges that designers of online learning need to factor in to the design of this pedagogy. This study explores how learner - learner; learner - course facilitator and learner - content interactions influenced and shaped learners' online learning experiences particularly satisfaction with a course facilitated from the University of Botswana for participants within the SADC region. These three forms of interactions were further explored through using 6 online learning evaluation dimensions to provide a guide to the analysis. The study employed a range of data collection methods that provided rich qualitative data including: Life world accounts, discussion forum entries, online surveys, expert reviews, and learners' grades. The findings suggest that the learners' level of interaction at the levels of the 6 dimensions could have influenced what they perceived to be valuable, effective and satisfactory. Other influencing variables were course design and community of learning presence. The findings also reveal that although the participants found the course to be very valuable to them, there were areas that could improve the learning experiences. Further longitudinal research and investigation into alternative technologies is also recommended. / Thesis (M.A.)-University of KwaZulu-Natal, Durban, 2009.

Policy analysis is a tool used by policy analysts to understand the complexity of policy. Different analysts use diverse models of policy analysis but they seldom agree on the model that is the most ideal for analysing policy. This study is geared towards a policy analysis of e-learning at the University of KwaZulu-Natal (UKZN). Using both quantitative and qualitative data, the study showed that the implementation of e-learning at UKZN has various characteristics that cannot be explained exhaustively within the framework of a single model of policy analysis. In the absence of an institutional e-learning policy framework, various actors and subsystems are actively implementing e-learning at UKZN. This negates the stagist model of policy analysis, according to which, policy is made up of logical and sequential stages with one stage – e.g. policy formulation – preceding the other – e.g. implementation. This is clearly not the case at UKZN where e-learning is being implemented in the absence of a formal policy framework. Due to the high ambiguity and low conflict that characterize the implementation of e-learning at UKZN, the study found that e-learning at UKZN could be situated within Matland’s ambiguity/conflict model. The need to contextualise e-learning is a key concern expressed by participants in the study. The study also found that the willingness to implement e-learning is significantly high with 84.6% of those surveyed expressing a willingness to implement e-learning. Similarly, more than half of respondents are of the view that UKZN needs to develop an e-learning policy framework. This approach fits into the incremental model according to which policy formulation is gradual and it is informed by the learning that emerges from implementation. / Thesis (M.Soc.Sc.)-University of KwaZulu-Natal, Pietermaritzburg, 2010.

Thesis (Ph. D.)--University of Sydney, 2005. / Title from title screen (viewed 23 March 2007). Submitted in fulfilment of the requirements for the degree of Doctor of Philosophy to the School of Policy and Practice, Faculty of Education and Social Work. Degree awarded 2005; thesis submitted 2004. Includes bibliographical references. Also issued in print.

Thesis (Ph.D. (Curriculum Studies))-University of Pretoria, 2005. / Abstract in English. Includes bibliographical references (leaves [235]-260). Available on the Internet via the World Wide Web.

Thesis (Ph.D.)--Ohio University, August, 2009. / Title from PDF t.p. Includes bibliographical references.

The use of blended learning to support teaching and learning is growing globally. Few studies, however, have investigated the relation between students’ learning styles and their perceptions of blended learning. This study used a case-study approach to investigate third year Environmental Science students’ learning styles and perceptions of the online component of blended learning at Rhodes University. Vermunt’s inventory of learning’s styles instrument was used to assess the students’ learning styles. Students’ perceptions of online learning were assessed using an 84-item online experience questionnaire. Multivariate cluster analyses based on students’ learning styles, perceptions of online learning and final coursework marks were done. The correlation between learning styles and perceptions of blended learning was assessed. Students had been using computers for about 10 years. About 91% of students owned computers and 50% had access to Internet at home or in their residences. Internet and email were the most commonly used tools for student learning averaging about at least six times per week. Three of Vermunt’s four learning styles were identified. These were the meaning-directed, application-directed and reproduction-directed styles. The undirected learning style was absent. A major finding of this study was the dissonance in learning styles of students. For example, students with the meaning-directed style also scored high on reproduction-directed style. Students combined deep approaches with memorisation when learning. I developed an instrument consisting of seven scales that described students’ perceptions of online learning. The scales were epistemological judgements, multiple sources of information, learning goals, relevance, Internet experience, appropriate tool and student interaction. There was high within scale variability in students’ perceptions of online learning. The perception that the Internet provided multiple sources of information was positively associated with advanced models of epistemology that support the construction of knowledge. There was dissonance between the perception of the Internet as enhancing epistemological judgements and some components of learning style. A perception of epistemological judgements was positively correlated with both deep and surface cognitive processing strategies.

Thesis (MTech (Information Technology))--Cape Peninsula University of Technology, 2015. / Previous research work in the field of education has highlighted that technology plays an integral role in deepening and accelerating learning. New technologies are providing educators with new tools to support teaching. Cloud computing is one such new technology that promises to take the knowledge delivery process to greater heights. The integration of cloud computing into the teaching and learning environment will enhance the curriculum and creates an embedded learning environment known as cloud pedagogy. Cloud pedagogy has been defined as the art of teaching while encouraging omnipresence learning via cloud based applications (Barack, 2014). In simple terms, it refers to any form of teaching and learning that is done using cloud-based learning. Higher Learning Institutions (HLIs) around the world have already started integrating cloud pedagogy into their curriculum and reaping many benefits from this. While the adoption of cloud pedagogy is gaining popularity around the world, this has not been the case in Southern Africa. The region is lagging behind in the adoption of cloud pedagogy and the adoption rate is largely unknown. In addition, few studies have tried to identify the factors that are influencing the slow adoption rate of cloud pedagogy in the region. This study addresses these issues by investigating factors that influence the adoption of cloud pedagogy in Southern Africa. It also investigates the barriers that hinder the adoption process. This research is exploratory in nature and adopts a qualitative research approach. It therefore follows the interpretivist paradigm. The study was done at two universities in Southern Africa; Cape Peninsula University of Technology (CPUT) from South Africa and Great Zimbabwe University (GZU) from Zimbabwe. Survey questionnaires were used to collect data. The questionnaires were distributed online but printed copies were also made available to respondents who preferred hard copies. The study was guided by the Unified Theory of Acceptance and Use of Technology (UTAUT) in both data collection and analysis. It employed the convenience and purposive sampling methods to select the two institutions and the respondents. Literature on adoption of cloud computing was also explored to arrive at a deeper understanding of the adoption of technology. Thematic analysis was used to analyse the collected data. The themes were derived from the theoretical constructs of UTAUT. The aims and objectives of the study were conceptualised around the four main constructs from the theory (performance expectance, effort expectance, social influence and facilitating conditions). / Cape Peninsula University of Technology University Research Fund

The use of computers equipped with Internet access by students during face-toface (F2F) class sessions is perceived as academically beneficial by a growing number of students and faculty members in universities across the United States. Nevertheless, some researchers suggest unstructured computer use detached from the immediate class content may negatively influence student participation, increase distraction levels, minimize recall of recently presented information, and decrease student engagement. This study investigates graduate students’ beliefs about computer use with Internet access during graduate face-to-face lecture classes in which computer use is neither mandated nor integrated in the class and the effect of such use on student recall. Methods include a 44-item questionnaire to investigate graduate students’ beliefs about computers and two experiments to investigate the influence of computer use during a lecture on students’ memory recall. One experimental group (open laptop) used computers during a lecture while the other (closed laptop) did not. Both groups were given the same memory recall test after the lectures, and the resulting scores were analyzed. Two weeks later, a second phase of the experiment was implemented in which laptop groups were reversed. Results from the first experiment indicated no statistically significant difference in recall scores between the open laptop group (M = 54.90, SD = 19.65) and the closed laptop group (M = 42.86, SD = 16.68); t (29) = -1.82, p = .08 (two tailed). Conversely, the second experiment revealed statistically significant differences in scores between the open laptop (M = 39.67, SD = 15.97) and the iv closed laptop group (M = 59.29, SD = 26.88); t (20.89) = 2.37, p = .03 (two tailed). The magnitude of the difference in mean scores (mean difference = 19.62, 95% CI: 2.39 to 36.85) was large (eta squared = 0.17). Multiple regression analysis suggests two factors accounted for 10% of the variance in recall scores: (1) students’ beliefs about distractions from computer use, and (2) beliefs about the influence of computer use on memory recall. Based on survey findings, participants (N=116) viewed computers and Internet access in graduate classes as helpful academic tools, but distractions from computer use were major sources of concern for students who used computers in graduate classes and those who did not. Additionally, participants believed academic productivity would increase if instructors integrated computer use appropriately in the curricula. Results of the survey and experiments suggest unstructured computer use with Internet access in the graduate classroom is strongly correlated with increased student distractions and decreased memory recall. Thus, restricting unstructured computer use is likely to increase existing memory recall levels, and increasing unstructured computer use is likely to reduce memory recall. Recommendations include changes in the way students use computers, pedagogical shifts, computer integration strategies, modified seating arrangements, increased accountability, and improved interaction between instructors and students.

This monograph documents my effort as well as examines the process of developing sustainable support in the use of instructional technology in a consulting project over a ten month period. It is written in a narrative recording the occurrences and my interventions during this ten-month period, along wdth my reflections in italics in light of the review of the literature and the analysis of the narrative. This results in a deeper understanding and insights in the field of instructional technology, and leads to the elaboration of a mission statement, which represents my present thinking about instructional design and consultation.