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Open Access Publications from the University of California

Collecting usage data and user feedback on a large scale to inform software development


The two most commonly used techniques for evaluating the fit between application design and use - namely, usability testing and beta testing with user feedback - suffer from a number of limitations that restrict evaluation scale (in the case of usability tests) and data quality (in the case of beta tests). They also fail to provide developers with an adequate basis for: (1) assessing the impact of suspected problems (and proposed solutions) on users at large, and (2) deciding where to focus scarce development and evaluation resources to maximize the benefit for users at large. This article describes an approach to usage data and user feedback collection that addresses these limitations to provide developers with a complementary source of usage - and usability-related information. This research has been subjected to a number of evaluative activities including: (1) the development of three research prototypes at NYNEX Corporation, the University of Colorado, and the University of California, (2) the incorporation of one prototype by independent third party developers as part of an integrated demonstration scenario performed by Lockheed Martin Corporation, abd (3) observation and participation in two industrial development projects, at NYNEX and Microsoft Corporations, in which developers sought to improve the application development process based on usage data and user feedback. The proposed approach involves a devlopment platform for creating software agents that are deployed over the Internet to observe application use and report usage data and user feedback to developers to help improve the fit between design and use. The data can be used to illuminate how applications are used, to uncover mismatches in actual versus expected use, and to increase user involvement in the evolution of interactive systems. This research is aimed at helping developers make more informed design, impact assessment, and effort allocation decisions, ultimately leading to more cost-effective development of software that is better suited to user needs.

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