32,078 research outputs found
Resilience markers for safer systems and organisations
If computer systems are to be designed to foster resilient
performance it is important to be able to identify contributors to resilience. The
emerging practice of Resilience Engineering has identified that people are still a
primary source of resilience, and that the design of distributed systems should
provide ways of helping people and organisations to cope with complexity.
Although resilience has been identified as a desired property, researchers and
practitioners do not have a clear understanding of what manifestations of
resilience look like. This paper discusses some examples of strategies that
people can adopt that improve the resilience of a system. Critically, analysis
reveals that the generation of these strategies is only possible if the system
facilitates them. As an example, this paper discusses practices, such as
reflection, that are known to encourage resilient behavior in people. Reflection
allows systems to better prepare for oncoming demands. We show that
contributors to the practice of reflection manifest themselves at different levels
of abstraction: from individual strategies to practices in, for example, control
room environments. The analysis of interaction at these levels enables resilient
properties of a system to be ‘seen’, so that systems can be designed to explicitly
support them. We then present an analysis of resilience at an organisational
level within the nuclear domain. This highlights some of the challenges facing
the Resilience Engineering approach and the need for using a collective
language to articulate knowledge of resilient practices across domains
Systematic evaluation of design choices for software development tools
[Abstract]: Most design and evaluation of software tools
is based on the intuition and experience of the designers.
Software tool designers consider themselves typical users
of the tools that they build and tend to subjectively evaluate their products rather than objectively evaluate them using established usability methods. This subjective approach is inadequate if the quality of software tools is to improve and the use of more systematic methods is advocated. This paper summarises a sequence of studies that
show how user interface design choices for software development tools can be evaluated using established usability engineering techniques. The techniques used included guideline review, predictive modelling and experimental studies with users
Modeling Human Visual Search Performance on Realistic Webpages Using Analytical and Deep Learning Methods
Modeling visual search not only offers an opportunity to predict the
usability of an interface before actually testing it on real users, but also
advances scientific understanding about human behavior. In this work, we first
conduct a set of analyses on a large-scale dataset of visual search tasks on
realistic webpages. We then present a deep neural network that learns to
predict the scannability of webpage content, i.e., how easy it is for a user to
find a specific target. Our model leverages both heuristic-based features such
as target size and unstructured features such as raw image pixels. This
approach allows us to model complex interactions that might be involved in a
realistic visual search task, which can not be easily achieved by traditional
analytical models. We analyze the model behavior to offer our insights into how
the salience map learned by the model aligns with human intuition and how the
learned semantic representation of each target type relates to its visual
search performance.Comment: the 2020 CHI Conference on Human Factors in Computing System
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Investigation of the use of navigation tools in web-based learning: A data mining approach
Web-based learning is widespread in educational settings. The popularity of Web-based learning is in great measure because of its flexibility. Multiple navigation tools provided some of this flexibility. Different navigation tools offer different functions. Therefore, it is important to understand how the navigation tools are used by learners with different backgrounds, knowledge, and skills. This article presents two empirical studies in which data-mining approaches were used to analyze learners' navigation behavior. The results indicate that prior knowledge and subject content are two potential factors influencing the use of navigation tools. In addition, the lack of appropriate use of navigation tools may adversely influence learning performance. The results have been integrated into a model that can help designers develop Web-based learning programs and other Web-based applications that can be tailored to learners' needs
NASA Space Human Factors Program
This booklet briefly and succinctly treats 23 topics of particular interest to the NASA Space Human Factors Program. Most articles are by different authors who are mainly NASA Johnson or NASA Ames personnel. Representative topics covered include mental workload and performance in space, light effects on Circadian rhythms, human sleep, human reasoning, microgravity effects and automation and crew performance
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Multimodal and ubiquitous computing systems: supporting independent-living older users
We document the rationale and design of a multimodal interface to a pervasive/ubiquitous computing system that supports independent living by older people in their own homes. The Millennium Home system involves fitting a resident’s home with sensors – these sensors can be used to trigger sequences of interaction with the resident to warn them about dangerous events, or to check if they need external help. We draw lessons from the design process and conclude the paper with implications for the design of multimodal interfaces to ubiquitous systems developed for the elderly and in healthcare, as well as for more general ubiquitous computing applications
Correcting menu usability problems with sound
Future human-computer interfaces will use more than just graphical output to display information. In this paper we suggest that sound and graphics together can be used to improve interaction. We describe an experiment to improve the usability of standard graphical menus by the addition of sound. One common difficulty is slipping off a menu item by mistake when trying to select it. One of the causes of this is insufficient feedback. We designed and experimentally evaluated a new set of menus with much more salient audio feedback to solve this problem. The results from the experiment showed a significant reduction in the subjective effort required to use the new sonically-enhanced menus along with significantly reduced error recovery times. A significantly larger number of errors were also corrected with sound
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