Abstract
The next evolutionary step in wireless Internet information management is to provide support for tasks, which may be collaborative and may include multiple target devices, from desktop to handheld. This means that the information architecture supports the processes of the task, recognizes group interaction, and lets users migrate seamlessly among internet-compatible devices without losing the thread of the session. If users are free to migrate amongst devices during the course of a session then intelligent transformation of data is required to exploit the screen size and input characteristics of the target appliance with minimal loss of task effectiveness. In this paper we first review general characteristics related to the performance of users on small screens and then examine the navigation of full tables on small screens for users in multi-device scenarios. We examine the methodologies available for access to full tables in environments where the full table cannot be viewed in its entirety. In particular, we examine the situation where users are collaborating across platform and referring to the same table of data. We ask three basic questions: Does screen size affect the performance of table lookup tasks? Does a search function improve performance of table lookup based tasks on reduced screen sizes? Does including context information improve the performance of table lookup based tasks on reduced screen sizes? The answers to these questions are important as individual and intuitive responses are used by the designers of small screen interfaces for use with large tables of data. We report on the results of a user study that examines factors that may affect the use of large tables on small display devices. The use of large tables on small devices in their native state becomes important in at least two circumstances. First, when collaboration involves two or more users sharing a view of data when the individual screen sizes are different. Second, when the exact table structure replication may be critical as a user moves quickly from a larger to a smaller screen or back again mid-task. Performance is measured by both effectiveness, correctness of result, and efficiency, effort to reach a result.
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