Concise Personas Based on Tacit Knowledge - How Representative Are They?

Ravi Mahamuni, Pramod Khambete, R. Punekar, Sylvan Lobo, Shivani Sharma, Ulemba Hirom
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引用次数: 7

Abstract

Personas have become integral to the user-centered design process, enabling designers to acquire empathy for the users, and guiding the design. Effective personas need to be representative of the user population. Persona creation based on immersive data collection and integrative analysis is recommended. In practice though, constraints of time, resources and access to end users often result in insufficient data. Augmenting the limited data with tacit knowledge can be effective in persona creation, although the representativeness of such personas must be established. We created concise personas through two action research inspired cycles leveraging tacit knowledge of a cross-functional, multidisciplinary team designing a service for their own organization. The representativeness of these personas was statistically validated using paired comparison method and Kolmogorov-Smirnov test. The approach can be valuable in similar situations for creating valid personas.
基于隐性知识的简洁人物角色——它们的代表性如何?
人物角色已经成为以用户为中心的设计过程中不可或缺的一部分,使设计师能够获得对用户的同情,并指导设计。有效的人物角色需要能够代表用户群体。建议基于沉浸式数据收集和综合分析来创建角色。但在实践中,时间、资源和访问终端用户的限制往往导致数据不足。用隐性知识扩充有限的数据在人物角色创建中是有效的,尽管必须建立这些人物角色的代表性。我们通过两个行动研究启发周期,利用跨职能、多学科团队为自己的组织设计服务的隐性知识,创建了简洁的人物角色。采用配对比较法和Kolmogorov-Smirnov检验对这些角色的代表性进行统计验证。在类似的情况下,该方法对于创建有效的角色很有价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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