Leon Barnard

Bio: Leon Barnard is an academic researcher from Georgia Institute of Technology. The author has contributed to research in topics: Mobile computing & Mobile device. The author has an hindex of 8, co-authored 10 publications receiving 521 citations.

Capturing the effects of context on human performance in mobile computing systems

Abstract: Many real world mobile device interactions occur in context-rich environments. However, the majority of empirical studies on mobile computing are conducted in static or idealized conditions, resulting in a deficit of understanding of how changes in context impact users’ abilities to perform effectively. This paper attempts to address the disconnect between the actual use and the evaluation of mobile devices by varying contextual conditions and recording changes in behavior. A study was performed to investigate the specific effects of changes in motion, lighting, and task type on user performance and workload. The results indicate that common contextual variations can lead to dramatic changes in behavior and that interactions between contextual factors are also important to consider.

An empirical comparison of use-in-motion evaluation scenarios for mobile computing devices

Abstract: There is a clear need for evaluation methods that are specifically suited to mobile device evaluation, largely due to the vast differences between traditional desktop computing and mobile computing. One difference of particular interest that needs to be accounted for is that mobile computing devices are frequently used while the user is in motion, in contrast to desktop computing. This study aims to validate the appropriateness of two evaluation methods that vary in representativeness of mobility, one that uses a treadmill to simulate motion and another that uses a controlled walking scenario.The results lead to preliminary guidelines based on study objectives for researchers wishing to use more appropriate evaluation methodologies for empirical, data-driven mobile computing studies. The guidelines indicate that using a treadmill for mobile evaluation can yield representative performance measures,whereas a controlled walking scenario is more likely to adequately simulate the atual user experience.

Older adults and visual impairment: what do exposure times and accuracy tell us about performance gains associated with multimodal feedback?

Abstract: This study examines the effects of multimodal feedback on the performance of older adults with different visual abilities. Older adults possessing normal vision (n=29) and those who have been diagnosed with Age-Related Macular Degeneration (n=30) performed a series of drag-and-drop tasks under varying forms of feedback. User performance was assessed with measures of feedback exposure times and accuracy. Results indicated that for some cases, non-visual (e.g. auditory or haptic) and multimodal (bi- and trimodal) feedback forms demonstrated significant performance gains over the visual feedback form, for both AMD and normally sighted users. In addition to visual acuity, effects of manual dexterity and computer experience are considered.

Toward achieving universal usability for older adults through multimodal feedback

Abstract: This experiment examines the effect of combinations of feedback (auditory, haptic, and/or visual) on the performance of older adults completing a drag-and-drop computer task. Participants completed a series of drag-and-drop tasks under each of seven feedback conditions (3 unimodal, 3 bimodal, 1 trimodal). Performance was assessed using measures of efficiency and accuracy. For analyses of results, participants were grouped based on their level of computer experience. All users performed well under auditory-haptic bimodal feedback and experienced users responded well to all multimodal feedback. Based on performance benefits for older adults seen in this experiment, future research should extend investigations to effectively integrate multimodal feedback into GUI interfaces in order to improve usability for this growing and diverse user group.

The effects of multimodal feedback on older adults' task performance given varying levels of computer experience

Abstract: This experiment examines the effect that computer experience and various combinations of feedback (auditory, haptic, and/or visual) have on the performance of older adults completing a drag-and-drop task on a computer. Participants were divided into three computer experience groups, based on their frequency of use and breadth of computer knowledge. Each participant completed a series of drag-and-drop tasks under each of seven feedback conditions (three unimodal, three bimodal, one trimodal). Performance was assessed using measures of efficiency and accuracy. Experienced users responded well to all multimodal feedback while users without experience responded well to auditory-haptic bimodal, but poorly to haptic-visual bimodal feedback. Based on performance benefits for older adults seen in this experiment, future research should extend investigations to effectively integrate multimodal feedback into GUI interfaces in order to improve usability for this growing and diverse user group.

Learning and Memory

Abstract: Experimental Psychology Its Scope and Method. IV. Learning and Memory. By Jean-Francois Le Ny, G. De Montpellier, G. Oleron and Cesar Flores. Translated by Louise Elkington. Edited by P. Fraisse and Jean Piaget. Pp. viii + 376. (Routledge and Kegan Paul: London, April 1970.) 80s.

Universal access in the information society

Abstract: ▶ Addresses the accessibility, usability, and, ultimately, acceptability of Information Society Technologies by anyone, anywhere, at anytime, and through any media and device. ▶ Focuses on theoretical, methodological, and empirical research, of both technological and non-technological nature. ▶ Features papers that report on theories, methods, tools, empirical results, reviews, case studies, and best-practice examples.

Context-aware systems

Abstract: Nowadays, numerous journals and conferences have published articles related to context-aware systems, indicating many researchers' interest. Therefore, the goal of this paper is to review the works that were published in journals, suggest a new classification framework of context-aware systems, and explore each feature of classification framework. This paper is based on a literature review of context-aware systems from 2000 to 2007 using a keyword index and article title search. The classification framework is developed based on the architecture of context-aware systems, which consists of the following five layers: concept and research layer, network layer, middleware layer, application layer and user infrastructure layer. The articles are categorized based on the classification framework. This paper allows researchers to extract several lessons learned that are important for the implementation of context-aware systems.