Thesis PlanB (M.S.)--University of Wisconsin--Stout, 2006. / Includes bibliographical references.

The field of adaptive hypermedia is a little over a decade old. It has a rich history in a range of fields such as artificial intelligence, user modelling, intelligent tutoring systems and hypertext. Early adaptive hypermedia work concentrated on application-led research; developing a range of systems for specific purposes. In 1996, Peter Brusilovsky reviewed the state-of-the-art and proposed a taxonomy of adaptive hypermedia techniques, thereby providing the means to categorise adaptive hypermedia systems. Since then, several practical frameworks for adaptive hypermedia applications have been produced, in addition to formal models for formalising adaptive hypermedia applications. This thesis presents a new framework for adaptive hypermedia systems based on agent technology, a field of research largely ignored within the adaptive community. Conceptually, this framework occupies a middle ground between the formal reference models for adaptive hypermedia and application-specific frameworks. This framework provides the means to implement formal models using variety of architectural approaches. Three novel adaptive hypermedia applications have been developed around this agent-based framework. Each system employs different architectural structures, they model the user with a variety of profiling techniques, and each provides a different set of adaptive features. The diversity of these three systems emphasises the flexibility and functionality of this proposed agent-based framework.

No description available.

Web-based learning has become an important component of education. Higher education institutions in Thailand have become increasingly aware of the widespread use and effectiveness of web-based learning systems. However, the adoption of such learning systems is growing at a slow pace in Thailand. The purpose of this study was to test the Unified Theory of Acceptance and Use of Technology (UTAUT), that performance expectancy, effort expectancy, social influence, and facilitating conditions have a positive effect on usage intention and adoption of web-based learning systems by instructors, in the Departments of Education at the Rajabhat Universities, Thailand; and to test whether experience of use, age, and gender have moderating effects in the adoption of web-based learning systems there. The research design used in this study was a cross-sectional survey design. Data were collected by means of a self-administered paper questionnaire. The study was conducted among the instructors in the departments of education at the Rajabhat Universities in Thailand. A total of 725 surveys were sent out, 454 questionnaires were returned by the respondents, and 14 were eliminated as outliers; thus, the final data set for the study was 440 samples. The two-step approach of SEM was used to test the model and the study's hypotheses; first, the measurement model was measured to examine the validity and reliability of the data; next, the structural model was measured to test the hypotheses of the study and the fitness of the data to the model. The results of this study revealed several factors that can affect instructors’ adoption of a web-based learning system and which can enhance the web-based learning performance of instructors in the Rajabhat Universities and throughout higher education in Thailand.

Thesis (Ph. D.)--University of Wyoming, 2006. / Title from PDF title page (viewed on Dec. 21, 2007). Includes bibliographical references.

Online courses and even degree programs are becoming a widespread phenomenon at universities across the United States. Research into the effectiveness of these courses is in the early stages. This qualitative study explored student perceptions of their online class experience using expectancy-value theory as a framework in an attempt to gain a better understanding of the criteria for designing an effective on-line course. The purpose of this case study was to describe the experience of students enrolled in online courses at two western universities in order to answer the following questions: 1. What do students value in terms of an outcome? 2. What do students value in terms of an online experience? 3. What do students consider to be negative factors (costs) in terms of an online experience? Data were collected using a variety of techniques. Twenty students in two online classes at one university participated in focus groups. Ten students from two universities participated in open-ended interviews, conducted either face-to-face or via telephone. Fifteen students, including those who were interviewed, maintained anecdotal records to capture real-time reactions to the experience. Participants represented a variety of disciplines, ages, and backgrounds. Transcripts from interviews and focus groups were pooled with information from anecdotal records and entered into QSR Nud*ist (qualitative analysis software) for coding. Categories represented in the data include orientation, course content, student-student interaction, student-teacher interaction, course interface and navigation, flexibility, hardware/software issues, and support systems. Students described both positive and negative factors in each of these categories. Negative factors identified by participants closely matched factors identified in cognitive load theory as extraneous cognitive load, suggesting that reducing negative factors in online courses may also reduce cognitive load, leading to improved learning. Additionally, findings from this study suggest that it may be possible to increase student motivation to participate and persist in online courses by adjusting the course design to enhance positive factors identified by participants and minimize factors they identified as negative. / Graduation date: 2003

As technology has advanced, corporations, government entities, and institutions of higher education have all begun experimenting with online classes and training. In colleges and universities around the world, everything from individual online classes to entire online degree programs are now offered. While many researchers and educators support this trend, many are concerned with whether online education is truly comparable to traditional, live instruction. The goal of this study was to evaluate an online version of a floral design course in comparison to the traditional version of the class. There were 140 students in the sample, including both the online and traditional classes. All were students at Texas A&M University in College Station, Texas. During the spring semester of 2003, the experimental group was enrolled in the online version of the course, while the control group was enrolled in the traditional version of the course. Students in both groups were asked to fill out surveys at the beginning and end of the semester to collect background information and to evaluate the course. Their floral designs were evaluated at the beginning and end of the class in order to measure design skill, and grades earned in the class were also collected at the end of the semester for comparison purposes. Statistically significant differences were noted in class grades, with traditional students outperforming the Web-based students in lecture points, lab points, and overall course grades. No statistically significant differences were noted in terms of student course satisfaction. In addition, students in the traditional class outperformed Web-based students in design skills. Besides class differences in performance, variables such as gender and distance course preparedness seemed to affect the outcome of some measures. Overall, females outperformed males in both classes. In the Web-based class, students found to be more prepared for distance learning courses fared better than students who were not as prepared. These results may indicate that certain students may do better in an online course than others, and it may be possible to screen these students in advance in order to maximize success in the online classroom.

Statistical software packages have been used for decades to perform statistical analyses. Recently, the emergence of the Internet has expanded the potential for these packages. However, none of the existing packages have fully realized the collaborative potential of the Internet. This medium, which is beginning to gain acceptance as a software development platform, allows people who might otherwise be separated by organizational or geographic barriers to come together and tackle complex issues using commonly available data sets, analysis tools and communications tools. Interestingly, there has been little work towards solving this problem in a generally applicable way. Rather, systems in this area have tended to focus on particular data sets, industries, or user groups. The Web-based statistical analysis model described in this thesis fills this gap. It includes a statistical analysis engine, data set management tools, an analysis storage framework and a communication component to facilitate information dissemination. Furthermore, its focus on enabling users with little statistical training to perform basic data analysis means that users of all skill levels will be able to take advantage of its capabilities. The value of the system is shown both through a rigorous analysis of the system’s structure and through a detailed case study conducted with the tobacco control community.

Statistical software packages have been used for decades to perform statistical analyses. Recently, the emergence of the Internet has expanded the potential for these packages. However, none of the existing packages have fully realized the collaborative potential of the Internet. This medium, which is beginning to gain acceptance as a software development platform, allows people who might otherwise be separated by organizational or geographic barriers to come together and tackle complex issues using commonly available data sets, analysis tools and communications tools. Interestingly, there has been little work towards solving this problem in a generally applicable way. Rather, systems in this area have tended to focus on particular data sets, industries, or user groups. The Web-based statistical analysis model described in this thesis fills this gap. It includes a statistical analysis engine, data set management tools, an analysis storage framework and a communication component to facilitate information dissemination. Furthermore, its focus on enabling users with little statistical training to perform basic data analysis means that users of all skill levels will be able to take advantage of its capabilities. The value of the system is shown both through a rigorous analysis of the system’s structure and through a detailed case study conducted with the tobacco control community.

There are three mail types of Botnet: IRC-based Botnet, P2P-based Botnet,Web-based Botnet and they have become major threat to the Internet recently. Web-based Botnet is popular and more harmful to users. The architecture of Web-based Botnet is simpler than P2P-based Botnet, and its malicious traffic can be hidden in a large number of normal traffic. In this study, we built an experimental environment of using malicious bot programs to detect suspicious traffic and malware features. Except network attacking and identity theft, Botnet could also be used by hackers to extend the life time of rouge websites by combining with the technology of Fast Flux Domain. Botnet and the technology of Fast Flux Domain closely link to each other in the real world. Both of Web-based Botnet and Fast Flux Domain technology use HTTP protocol to communicate, and Botnet provides a large number of infected hosts to be Fast Flux Agents which act like a relay station to block the direct link of malicious websites from clients, but completes the mutual connection. In the research, not only the analysis and detection of Web-based Botnet are focused, but also the impact of Fast Flux Domain technology is included. We expect to clear the architecture of Botnet and the technology of Fast Flux Domain, and make the detection mechanism more precisely.