A challenge in presenting augmenting information in outdoor augmented reality (AR) settings lies in the broad range of uncontrollable environmental conditions that may be present, specifically large-scale fluctuations in natural lighting and wide variations in likely backgrounds or objects in the scene. In this paper, we present a user-based study which examined the effects of outdoor background textures, changing outdoor illuminance values, and text drawing styles on user performance of a text identification task with an optical, see-through augmented reality system. We report significant effects for all of these variables, and discuss design guidelines and ideas for future work.

We present a comparative study of user performance with tasks involving navigation, visual search, and geometric manipulation, in a map-based battlefield visualization virtual environment (VE). Specifically, our experiment compared user performance of the same task across four different VE platforms: desktop, cave, workbench, and wall. Independent variables were platform type, stereopsis (stereo, mono), movement control mode (rate, position), and frame of reference (egocentric, exocentric). Overall results showed that users performed tasks fastest using the desktop and slowest using the workbench. Other results are detailed in the article. Notable is that we designed our task in an application context, with tasking much closer to how users would actually use a real-world battlefield visualization system. This is very uncommon for comparative studies, which are usually designed with abstract tasks to minimize variance. This is, we believe, one of the first and most complex studies to comparatively examine, in an application context, this many key variables affecting VE user interface design.

Social data mining systemsenable people to share opinions and benefit from each other's experience. They do this by mining and redistributing information from computational records of social activity such as Usenet messages, system usage history, citations, or hyperlinks. Some general questions for evaluating such systems are: (1) is the extracted information valuable? and (2) do interfaces based on the information improve user task performance? We report here onTopicShop, a system that mines information from the structure and content of Web pages and provides an exploratory information workspace interface. We carried out experiments that yielded positive answers to both evaluation questions. First, a number of automatically computable features about Web sites do a good job of predicting expert quality judgments about sites. Second, compared to popular Web search interfaces, the TopicShop interface to this information lets users select significantly more high-quality sites, in less time and with less effort, and to organize the sites they select into personally meaningful collections more quickly and easily. We conclude by discussing how our results may be applied and considering how they touch on general issues concerning quality, expertise, and consensus.

Article Free Access Share on Development and evaluation of a taxonomical model of behavioral representation techniques Authors: J. D. Chase Department of Computer Science, Virginia Tech, Blacksburg VA Department of Computer Science, Virginia Tech, Blacksburg VAView Profile , Robert S. Schulman Department of Statistics, Virginia Tech, Blacksburg VA Department of Statistics, Virginia Tech, Blacksburg VAView Profile , H. Rex Hartson Department of Computer Science, Virginia Tech, Blacksburg VA Department of Computer Science, Virginia Tech, Blacksburg VAView Profile , Deborah Hix Department of Computer Science, Virginia Tech, Blacksburg VA Department of Computer Science, Virginia Tech, Blacksburg VAView Profile Authors Info & Claims CHI '94: Proceedings of the SIGCHI Conference on Human Factors in Computing SystemsApril 1994 Pages 159–165https://doi.org/10.1145/191666.191730Online:24 April 1994Publication History 3citation406DownloadsMetricsTotal Citations3Total Downloads406Last 12 Months20Last 6 weeks8 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF

Little or no empirical validation exists for many of software engineering's basic assumptions. While some of these assumptions are intuitive, the need for scientific experimentation remains clear. Several assumptions are made about the factors affecting software reuse, and in particular, the role of the object-oriented paradigm. This paper describes the preliminary results of a controlled experiment designed to evaluate the impact of the object-oriented paradigm on software reuse. The experiment concludes that (1) the object-oriented paradigm substantially improves productivity, although a significant part of this improvement is due to the effect of reuse, (2) reuse without regard to language paradigm improves productivity, (3) language differences are far more important when programmers reuse than when they do not, and (4) the object-oriented paradigm has a particular affinity to the reuse process.