A new method for interacting with multi-window applications on large, high resolution displays

Physically large display walls can now be constructed using off-the-shelf computer hardware. The high resolution of these displays (e.g., 50 million pixels) means that a large quantity of data can be presented to users, so the displays are well suited to visualization applications. However, current methods of interacting with display walls are somewhat time consuming. We have analyzed how users solve real visualization problems using three desktop applications (XmdvTool, Iris Explorer and Arc View), and used a new taxonomy to classify users’ actions and illustrate the deficiencies of current display wall interaction methods. Following this we designed a novel methodfor interacting with display walls, which aims to let users interact as quickly as when a visualization application is used on a desktop system. Informal feedback gathered from our working prototype shows that interaction is both fast and fluid

Addictive links: The motivational value of adaptive link annotation

Adaptive link annotation is a popular adaptive navigation support technology. Empirical studies of adaptive annotation in the educational context have demonstrated that it can help students to acquire knowledge faster, improve learning outcomes, reduce navigational overhead, and encourage non-sequential navigation. In this paper, we present our exploration of a lesser known effect of adaptive annotation, its ability to significantly increase students' motivation to work with non-mandatory educational content. We explored this effect and confirmed its significance in the context of two different adaptive hypermedia systems. The paper presents and discusses the results of our work

Improving the Analyst and Decision-Maker’s Perspective through Uncertainty Visualization

This thesis constructs the Taxonomy of Uncertainty and an approach for enhancing the information in decision support systems. The hierarchical categorization of numerous causes for uncertainty defines the taxonomy, which fostered the development of a technique for visualizing uncertainty. This technique is fundamental to expressing the multi-dimensional uncertainty that can be associated with any object. By including and intuitively expressing uncertainty, the approach facilitates and enhances intuition and decision-making without undue information overload. The resulting approach for enhancing the information involves recording uncertainty, identifying the relevant items, computing and visualizing uncertainty, and providing interaction with the selection of uncertainty. A prototype embodying this approach to enhancing information by including uncertainty was used to validate these efforts. Evaluation responses of a small sample space support the thesis that the decision-maker\u27s knowledge is enhanced with enlightening information afforded by including and visualizing uncertainty, which can improve the decision-making process. Although the concept was initially conceived to help decision support system users deal with uncertainty, this methodology and these ideas can be applied to any problem where objects with many potential reasons for uncertainty are the focus of the decision-making

Examining the strategic benefits of information systems: A global case study

In the context of the emerging evaluation of Information Systems (IS) as strategic enablers, this paper critically reviews the literature relating to the strategic benefits of IS. Understanding the importance of IS benefits can be significant in the development of strategy in an organisation, although most organisations have diverse environments and, likewise, diverse benefits for decision-makers. Thus, taxonomies of the benefits of IS are produced from both the academic literature and published case studies. In this way, a classification of benefits as they relate to organisational strategic focus has been developed to provide a greater understanding of the benefits needed to obtain a specific focus. The result of this paper is a taxonomy of IS benefits in the strategic focus of IS, using Y bank as a case study. This categorisation can support the evaluation of IS processes, which will, in turn, support decision-makers throughout the planning process

Designing an Adaptive Interface: Using Eye Tracking to Classify How Information Usage Changes Over Time in Partially Automated Vehicles

While partially automated vehicles can provide a range of benefits, they also bring about new Human Machine Interface (HMI) challenges around ensuring the driver remains alert and is able to take control of the vehicle when required. While humans are poor monitors of automated processes, specifically during ‘steady state’ operation, presenting the appropriate information to the driver can help. But to date, interfaces of partially automated vehicles have shown evidence of causing cognitive overload. Adaptive HMIs that automatically change the information presented (for example, based on workload, time or physiologically), have been previously proposed as a solution, but little is known about how information should adapt during steady-state driving. This study aimed to classify information usage based on driver experience to inform the design of a future adaptive HMI in partially automated vehicles. The unique feature of this study over existing literature is that each participant attended for five consecutive days; enabling a first look at how information usage changes with increasing familiarity and providing a methodological contribution to future HMI user trial study design. Seventeen participants experienced a steady-state automated driving simulation for twenty-six minutes per day in a driving simulator, replicating a regularly driven route, such as a work commute. Nine information icons, representative of future partially automated vehicle HMIs, were displayed on a tablet and eye tracking was used to record the information that the participants fixated on. The results found that information usage did change with increased exposure, with significant differences in what information participants looked at between the first and last trial days. With increasing experience, participants tended to view information as confirming technical competence rather than the future state of the vehicle. On this basis, interface design recommendations are made, particularly around the design of adaptive interfaces for future partially automated vehicles