Applied Information Management

Practical ways to enhance mobile software applications by using readily available contextual data

In Brief: Mobile devices, such as wireless phones and PDAs, are now everyday tools―and certainly a near-essential part of the business world. They promise unmatched convenience and time-savings, giving users almost anywhere access to the Internet, personal and business information, numerous productivity tools, and, of course, people.

Mobile applications designers can improve device usability and intuitiveness by better-using contextual information.

Thanks to a vast array of available contextual information―data that devices and applications gather about how users interface with their devices, applications, and environments―these devices have the potential to become infinitely more intuitive, user-friendly, and useful. But this higher performance depends on mobile application designers taking this readily available contextual information and giving their applications the ability to use it.

Those who have implemented such data into their mobile device applications have improved user interfaces, reduced the need for user input, maximized the amount of useful information displayed on a small screens, and moderated the level of detail presented to the user, creating a much simpler and more useful interactive system.

User Interface Improvements
  • Automatically adapts the user interface for optimal display
  • Reduces user input required to find relevant information
  • Reduces user input required to find and format relevant information
  • Simplifies a task

Figure 1—Types of mobile device application user interface improvements

To achieve these results, application designers can follow a series of simple guidelines that help identify the three primary kinds of contextual information―location, time, and activity―and how they affect mobile application usability.

For example, location contextual information would offer insight into a user's physical location or proximity of the device to another object, such as the user himself. Activity relates to things like amount of ambient light, device movement and speed, and environmental noise. Finally, time information sheds light on time of day and type of environmental noise.

Thus, based on these cues, a device application could conceivably automatically adjust the display, backlighting, or sound depending on how far away the user was holding the device, how much noise is in the area, or what time of day it is.

By using these readily available clues, designers can better predict application usage and create programs that not only automatically react to the above contextual events when they occur, but proactively respond based on history, creating a much more intuitive, useful interface to enhance user experience.


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  • Barnard, L., Yi, J., Jacko, J. & Sears, A. (2006). Capturing the effects of context on human performance in mobile computing systems. Personal and Ubiquitous Computing. Retrieved November 3, 2006, from ACM Portal.
  • Dey, A. & Abowd, G. (1999). Toward a better understanding of context and context-awareness. GVU Technical Report GIT-GVU-99-22, College of Computing, Georgia Institute of Technology. Retrieved November 3, 2006, from Towards a Better Understanding of Context and Context-Awareness.
  • Lee, Y., & Benbasat, I. (2004). A framework for the study of customer interface design for mobile commerce. International Journal of Electronic Commerce, 8(3), 79-102. Retrieved October 31, 2006, from the Business Source Premier database.
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AIM alumnus Donald Davies

Research Paper Author: Donald J. Davies—2007 AIM Graduate

Abstract: The usability of mobile applications is threatened by limited input/output capabilities and varied access situations (Bertini et. al., 2005). Through context-awareness, applications are programmed to respond to contextual information as an input source (Schmidt et al., 1999). Based on analysis of literature published between 1998 and 2006, techniques to both interpret and apply contextual input to improve mobile application usability are identified among four primary context types: location, identity, time, and activity.

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