Large-scale collection of usage data to inform design

被引:0
作者
Hilbert, DM [1 ]
Redmiles, DF [1 ]
机构
[1] FX Palo Alto Lab, Palo Alto, CA 94304 USA
来源
HUMAN-COMPUTER INTERACTION - INTERACT'01 | 2001年
关键词
usability testing; beta testing; automated data collection; software monitoring; post-deployment evaluation;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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 on users at large, and (2) deciding where to focus development and evaluation resources to maximize the benefit for users at large. This paper describes an agent-based approach for collecting usage data and user feedback over the Internet that addresses these limitations to provide developers with a complementaty source of usage-and usability-related information. Contributions include: a theory to motivate and guide data collection, an architecture capable of supporting very large scale data collection, and real-word experience suggesting the proposed approach is complementary to existing practice.
引用
收藏
页码:569 / 576
页数:8
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