5,505 research outputs found

    IMPROVING REVISITATION IN LONG DOCUMENTS WITH TWO-LEVEL ARTIFICIAL-LANDMARK SCROLLBARS

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    Revisitation – returning to previously-visited locations in a document – is commonly done in the digital world. While linear navigation controls provide a spatial representation of the document and allow effective navigation in short documents, they are not effective in long documents, particularly for revisitation. Bookmarks, search and history dialogs, and “read wear” (visual marks left as the user interacts with the document) can all assist revisitation; however, for long documents all of these tools are limited in terms of effort, clutter, and interpretability. Inspired by visual cues such as coloured edges and “thumb indents” in hardcopy books, recent work has proposed artificial landmarks to help users build up natural spatial memory for the locations in a document; in long documents, however, this technique is also limited because of the number of pages each landmark represents. To address this problem, this thesis proposes a Double-Scrollbar design that uses two columns of artificial landmarks that can provide greater specificity for spatial memory and revisitation in long documents. We developed three versions of landmark-augmented Double-Scrollbar, using icons, letters, and digits as landmarks. To assess the performance and usability of the Double-Scrollbar design, two studies were conducted with 21 participants, each visiting and revisiting pages of a long document using each of the new designs, as well as a single-column design and a standard scrollbar. Results showed that two levels of icon landmarks were significantly better for assisting revisitation, and were preferred by participants. The two-level artificial-landmark scrollbar is a new way of improving revisitation in long documents by assisting the formation of more precise spatial memories about document locations

    Movement around real and virtual cluttered environments

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    Two experiments investigated participants’ ability to search for targets in a cluttered small-scale space. The first experiment was conducted in the real world with two field of view conditions (full vs. restricted), and participants found the task trivial to perform in both. The second experiment used the same search task but was conducted in a desktop virtual environment (VE), and investigated two movement interfaces and two visual scene conditions. Participants restricted to forward only movement performed the search task quicker and more efficiently (visiting fewer targets) than those who used an interface that allowed more flexible movement (forward, backward, left, right, and diagonal). Also, participants using a high fidelity visual scene performed the task significantly quicker and more efficiently than those who used a low fidelity scene. The performance differences between all the conditions decreased with practice, but the performance of the best VE group approached that of the real-world participants. These results indicate the importance of using high fidelity scenes in VEs, and suggest that the use of a simple control system is sufficient for maintaining ones spatial orientation during searching

    Movement around real and virtual cluttered environments

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    Two experiments investigated participants’ ability to search for targets in a cluttered small-scale space. The first experiment was conducted in the real world with two field of view conditions (full vs. restricted), and participants found the task trivial to perform in both. The second experiment used the same search task but was conducted in a desktop virtual environment (VE), and investigated two movement interfaces and two visual scene conditions. Participants restricted to forward only movement performed the search task quicker and more efficiently (visiting fewer targets) than those who used an interface that allowed more flexible movement (forward, backward, left, right, and diagonal). Also, participants using a high fidelity visual scene performed the task significantly quicker and more efficiently than those who used a low fidelity scene. The performance differences between all the conditions decreased with practice, but the performance of the best VE group approached that of the real-world participants. These results indicate the importance of using high fidelity scenes in VEs, and suggest that the use of a simple control system is sufficient for maintaining ones spatial orientation during searching

    Effects of spatial ability on multi-robot control tasks

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    Working with large teams of robots is a very complex and demanding task for any operator and individual differences in spatial ability could significantly affect that performance. In the present study, we examine data from two earlier experiments to investigate the effects of ability for perspective-taking on performance at an urban search and rescue (USAR) task using a realistic simulation and alternate displays. We evaluated the participants' spatial ability using a standard measure of spatial orientation and examined the divergence of performance in accuracy and speed in locating victims, and perceived workload. Our findings show operators with higher spatial ability experienced less workload and marked victims more precisely. An interaction was found for the experimental image queue display for which participants with low spatial ability improved significantly in their accuracy in marking victims over the traditional streaming video display. Copyright 2011 by Human Factors and Ergonomics Society, Inc. All rights reserved

    Use of Landmarks to Improve Spatial Learning and Revisitation in Computer Interfaces

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    Efficient spatial location learning and remembering are just as important for two-dimensional Graphical User Interfaces (GUI) as they are for real environments where locations are revisited multiple times. Rapid spatial memory development in GUIs, however, can be difficult because these interfaces often lack adequate landmarks that have been predominantly used by people to learn and recall real-life locations. In the absence of sufficient landmarks in GUIs, artificially created visual objects (i.e., artificial landmarks) could be used as landmarks to support spatial memory development of spatial locations. In order to understand how spatial memory development occurs in GUIs and explore ways to assist users’ efficient location learning and recalling in GUIs, I carried out five studies exploring the use of landmarks in GUIs – one study that investigated interfaces of four standard desktop applications: Microsoft Word, Facebook, Adobe Photoshop, and Adobe Reader, and other four that tested artificial landmarks augmented two prototype desktop GUIs against non-landmarked versions: command selection interfaces and linear document viewers; in addition, I tested landmarks’ use in variants of these interfaces that varied in the number of command sets (small, medium, and large) and types of linear documents (textual and video). Results indicate that GUIs’ existing features and design elements can be reliable landmarks in GUIs that provide spatial benefits similar to real environments. I also show that artificial landmarks can significantly improve spatial memory development of GUIs, allowing support for rapid spatial location learning and remembering in GUIs. Overall, this dissertation reveals that landmarks can be a valuable addition to graphical systems to improve the memorability and usability of GUIs

    Age-related cognitive decline and navigation in electronic environments

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    The older population is increasing, as is life expectancy. Technical devices are becoming more widespread and used for many everyday tasks. Knowledge about new technology is important to remain as an active and independent part of the society. However, if an old user group should have equal access to this technology, new demands will be placed on the design of interfaces and devices. With respect to old users it is and will be important to develop technical devices and interfaces that take the age-related decline in physical and cognitive abilities into account. The aim of this work was to investigate to what extent the age-related cognitive decline affects performance on different computer-related tasks and the use of different interfaces. With respect to the use of computer interfaces, two studies were conducted. In the first study, the information was presented with a hierarchical structure. In the second study the information was presented as a 3D-environment, and it was also investigated how an overview map could support navigation. The third study examined the age-related cognitive decline in the use of a small mobile phone display with a hierarchical information structure. The results from the studies showed that the most pronounced age-related difference was found in the use of the 3D-environment. Within this environment, prior experience was found to have the largest impact on performance. Regarding the hierarchical information structures, prior experience seemed to have a larger impact on performance of easy tasks, while age and cognitive abilities had a larger impact on performance of more complex tasks. With respect to navigation aids, the overview map in the 3D-environment did not reduce the age-differences; however, it contributed to a better perceived orientation and reduced the feeling of being lost

    To Drive or to Be Driven? The Impact of Autopilot, Navigation System, and Printed Maps on Driver’s Cognitive Workload and Spatial Knowledge

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    The technical advances in navigation systems should enhance the driving experience, supporting drivers’ spatial decision making and learning in less familiar or unfamiliar environments. Furthermore, autonomous driving systems are expected to take over navigation and driving in the near future. Yet, previous studies pointed at a still unresolved gap between environmental exploration using topographical maps and technical navigation means. Less is known about the impact of the autonomous system on the driver’s spatial learning. The present study investigates the development of spatial knowledge and cognitive workload by comparing printed maps, navigation systems, and autopilot in an unfamiliar virtual environment. Learning of a new route with printed maps was associated with a higher cognitive demand compared to the navigation system and autopilot. In contrast, driving a route by memory resulted in an increased level of cognitive workload if the route had been previously learned with the navigation system or autopilot. Way-finding performance was found to be less prone to errors when learning a route from a printed map. The exploration of the environment with the autopilot was not found to provide any compelling advantages for landmark knowledge. Our findings suggest long-term disadvantages of self-driving vehicles for spatial memory representations
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