Thesis (M.A.)--University of Alberta, 2009. / Title from PDF file main screen (viewed on Feb. 19, 2010). A thesis submitted to the Faculty of Graduate Studies and Research in partial fulfillment of the requirements for the degree of Master of Arts, [Department of] Humanities Computing, University of Alberta. Includes bibliographical references.

Context. Augmented Reality (AR) is a technique that provides additional and varied information to a real environment. The compatibility to smartphones makes AR applications suitable for location based, social, advertisement as well as education oriented applications. Objectives. This study explores if AR is a suitable method of information visualization that can enhance User Experience(UX) comparedto more traditional methods. The information this project focuses on is 3D model and animation information. Methods. This work utilizes a comparative experiment where subjects get to test and evaluate two prototypes, one consisting of static, rendered images and a video and the other being an interactive mobileAR application. Results. Results were gathered with the Attrakdiff™ User Experience questionnaire and an interview. Conclusions. The experiment showed that there is a possibility to enhance user experience when visualizing 3D model and animation information with the help of mobile AR applications.

published_or_final_version / abstract / Mechanical Engineering / Doctoral / Doctor of Philosophy

In decision theory the process of selecting the best option is called preferential choice. Many personal, business, and professional preferential choice decisions are made every day. In these situations, a decision maker must select the optimal option among multiple alternatives. In order to do this, she must be able to analyze a model of her preferences with respect to the objectives that are important to her. Prescriptive decision theory suggests several ways to effectively develop a decision model. However, these methods often end up too tedious and complicated to apply to complex decisions that involve many objectives and alternatives. In order to help people make better decisions, an easier, more intuitive way to develop interactive models for analysis of decision contexts is needed. The application of interactive visualization techniques to this problem is an opportune solution. A visualization tool to help in preferential choice must take into account important aspects from both fields of Information Visualization and Decision Theory. There exists some proposals that claim to aid preferential choice, but some key tasks and steps from at least one of these areas are often overlooked. An added missing element in these proposals is an adequate user evaluation. In fact, the concept of a good evaluation in the field of information visualization is a topic of debate, since the goals of such systems stretch beyond what can be concluded from traditional usability testing. In our research we investigate ways to overcome some of the challenges faced in the design and evaluation of visualization systems for preferential choice. In previous work, Carenini and Lloyd proposed ValueCharts, a set of visualizations and interactive techniques to support the inspection of linear models of preferences. We now identify the need to consider the decision process in its entirety, and to redesign ValueCharts in order to support all phases of preferential choice. We present our task-based approach to the redesign of ValueCharts grounded in recent findings from both Decision Analysis and Information Visualization. We propose a set of domain-independent tasks for the design and evaluation of interactive visualizations for preferential choice. We then use the resulting framework as a basis for an analytical evaluation of our tool and alternative approaches. Finally, we use an application of the task model in conjunction with a new blend of evaluation methods to assess the utility of ValueCharts.

In decision theory the process of selecting the best option is called preferential choice. Many personal, business, and professional preferential choice decisions are made every day. In these situations, a decision maker must select the optimal option among multiple alternatives. In order to do this, she must be able to analyze a model of her preferences with respect to the objectives that are important to her. Prescriptive decision theory suggests several ways to effectively develop a decision model. However, these methods often end up too tedious and complicated to apply to complex decisions that involve many objectives and alternatives. In order to help people make better decisions, an easier, more intuitive way to develop interactive models for analysis of decision contexts is needed. The application of interactive visualization techniques to this problem is an opportune solution. A visualization tool to help in preferential choice must take into account important aspects from both fields of Information Visualization and Decision Theory. There exists some proposals that claim to aid preferential choice, but some key tasks and steps from at least one of these areas are often overlooked. An added missing element in these proposals is an adequate user evaluation. In fact, the concept of a good evaluation in the field of information visualization is a topic of debate, since the goals of such systems stretch beyond what can be concluded from traditional usability testing. In our research we investigate ways to overcome some of the challenges faced in the design and evaluation of visualization systems for preferential choice. In previous work, Carenini and Lloyd proposed ValueCharts, a set of visualizations and interactive techniques to support the inspection of linear models of preferences. We now identify the need to consider the decision process in its entirety, and to redesign ValueCharts in order to support all phases of preferential choice. We present our task-based approach to the redesign of ValueCharts grounded in recent findings from both Decision Analysis and Information Visualization. We propose a set of domain-independent tasks for the design and evaluation of interactive visualizations for preferential choice. We then use the resulting framework as a basis for an analytical evaluation of our tool and alternative approaches. Finally, we use an application of the task model in conjunction with a new blend of evaluation methods to assess the utility of ValueCharts.

Thesis (M.S.)--Oregon State University, 2008. / Printout. Includes bibliographical references (leaves 82-84). Also available on the World Wide Web.

Thesis (Ph.D.)--Drexel University, 2007. / Includes abstract and vita. Includes bibliographical references (leaves 177-192).

Habilitation - Universität, Stuttgart. / Description based on print version record. Includes bibliographical references (p. [249]-275) and index.

Diss. Umeå : Univ., 2003.

Thesis (Ph.D.)--University of Western Australia, 2007.