The Importance of who and what in Interruption Management: Empirical Evidence from a Cell Phone Use Study

Interruption management in technology mediated communication is a key concern in collaborative work and social environments. Previous empirical and theoretical work in predicting interruptibility predominantly focuses on interruptee’s local context namely identifying cognitively and socially intruding contexts such as mental work load levels, activity, place of activity. They largely ignore the relational context namely “who” the interruption is from or “what” it is about. This paper addresses this issue by systematically investigating the use of the various contextual factors in interruption management practices of everyday cell phone use. Analysis of 1201 incoming calls from our experience sampling method study of cell phone use, shows that “who” is calling is used most of the time (87.4%) by individuals to make deliberate call handling decisions (N=834), in contrast to the interruptee’s current local social (34.9%) or cognitive (43%) contexts. We present implications of these findings for the design of interruption management tools for communication media

Rethinking the progress bar

ABSTRACT Progress bars are prevalent interface elements in modern software. Typically, a linear function is employed, in which the progress of the bar is directly proportional to how much work has been completed. However, numerous factors cause progress bars to proceed at non-linear rates. Additionally, humans perceive time in a non-linear way. This paper explores the impact of various progress bar behaviors on user perception of process duration. We present a comprehensive experiment that was devised and conducted to determine the user perception of different progress bar behaviors. The results are used to suggest several design considerations that can be applied to enhance progress bars and ultimately improve users' computing experience

Does “authority” mean quality? predicting expert quality ratings of Web documents

exploiting hyperlink structure For many topics, the World Wide Web contains hundreds or thousands of relevant documents of widely varying quality. Users face a daunting challenge in identifying a small subset of documents worthy of their attention. Link analysis algorithms have received much interest recently, in large part for their potential to identify high quality items. We report here on an experimental evaluation of this potential. We evaluated a number of link and content-based algorithms using a dataset of web documents rated for quality by human topic experts. Link-based metrics did a good job of picking out high-quality items. Precision at 5 is about 0.75, and precision at 10 is about 0.55; this is in a dataset where 0.32 of all documents were of high quality. Surprisingly, a simple content-based metric performed nearly as well; ranking documents by the total number of pages on their containing site

Constructing, Organizing, and Visualizing Collections of Topically Related Web Resources

For many purposes, the Web page is too small a unit of interaction and analysis. Web sites are structured multimedia documents consisting of many pages, and users often are interested in obtaining and evaluating entire collections of topically related sites. Once such a collection is obtained, users face the challenge of exploring, comprehending, and organizing the items. We report four innovations that address these user needs. . We replaced the web page with the web site as the basic unit of interaction and analysis. . We defined a new information structure, the clan graph, that groups together sets of related sites. . We augment the representation of a site with a site profile, information about site structure and content that helps inform user evaluation of a site. . We invented a new graph visualization, the auditorium visualization, that reveals important structural and content properties of sites within a clan graph. Detailed analysis and user studies document the utility o..

Seeing What Your Are Hearing: Coordinating

Real time team co-ordination is a central problem for CSCW, but previous attempts to build novel systems to support it have not been greatly successful. One reason for this is that teams have often evolved highly effective work practices involving paper. In contrast to these prior negative findings, we present an instance of a successful digital system to support real-time co-ordination. Our system is designed to co-ordinate rapid responses to serious network failures in a telecommunications company. A critical reason for our system's success is that (in contrast to many prior studies) the primary data in our setting is speech. The support team must co-ordinate responses to trouble reports sent in voicemail messages. Our fieldwork suggests that because speech is ephemeral and not inherently visual, existing paper practices make it hard to extract information from those messages in order to construct shared visual representations of the major elements of the work. This in turn makes it difficult to co-ordinate work. Our novel system makes visible the content of these messages along with the actions that team members are taking to deal with them. An 8-month system field trial showed that making important aspects of individual work visible enhanced awareness and team coordination

Specifying Preferences Based on User History

Many applications require users to specify preferences. We support users in this task by letting them define preferences relative to their personal history or that of other users. We implement this idea using a graphical technique called control shadows, which we have implemented on both a desktop computer and on a cell phone with a small, grayscale display. An empirical study compared user performance on the graphical interface and a text table interface with identical functionality. On the desktop, users completed their tasks more quickly and effectively and strongly preferred the graphical interface. On the cell phone, there was no significant difference between the graphical and table interfaces. Finally, personal history proved useful in specifying preferences, but history of other users was not helpful