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How to approximate users' values while preserving privacy: experiences with using attitudes towards work tasks as proxies for personal value elicitation

机译:如何在保护隐私的同时逼近用户价值:使用对工作任务的态度作为个人价值启发的经验

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摘要

Software users have different sets of personal values, such as benevolence, self-direction, and tradition. Among other factors, these personal values influence users' emotions, preferences, motivations, and ways of performing tasks-and hence, information needs. Studies of user acceptance indicate that personal traits like values and related soft issues are important for the user's approval of software. If a user's dominant personal value were known, software could automatically show an interface variant which offers information and functionality that best matches his or her dominant value. A user's dominant personal value is the one that most strongly influences his or her attitudes and behaviors. However, existing methods for measuring a user's values are work intensive and/or interfere with the user's privacy needs. If interface tailoring for very large groups of users is planned, value approximation has to be achieved on a large scale to assign individualized software to all users of the software. Our work focuses on approximating the dominant values of a user with less effort and less impact on privacy. Instead of probing for a user's values directly, we explore the potential of approximating these values based on the user's preferences for key tasks. Producing tailored versions of software is a separate topic not in the focus here. In this paper we rather describe a method to identify user values from task preferences and an empirical study of applying parts of this method. We are proposing the method in this paper for the first time except for a preliminary version orally presented at a workshop. The method consists of a research process and an application process. In the research process a researcher has to identify key tasks occurring in a context under investigation which have a relationship to personal values. These key tasks can be used in the application process to approximate the dominant values of new users in a similar context. In this empirical study we show that the research process of our method allows us to determine key tasks which approximate values in the shared context of nursing. The majority of the nurses were found to have one of the three following dominant values: benevolence, self-direction, or hedonism. Data confirmed common expectations: that nurses with the value of benevolence, when compared to all other nurses, had a higher preference for tasks which helped people immediately or improved their circumstances of the treatment. In relation to all other nurses, participants with self-direction disliked tasks which affected their personal freedom, and users with hedonism had a lower preference for tasks which involved physical work and preferred tasks which promised gratification. Our findings advance measurement of personal values in large user groups by asking questions with less privacy concern. However, the method requires substantial efforts during the initial research process to prepare such measurements. Future work includes replicating our method in other contexts and identifying value-dependent tasks for users with other values than the three values our empirical study mainly focused on.
机译:软件用户具有不同的个人价值观,例如仁慈,自我指导和传统。这些个人价值以及其他因素会影响用户的情绪,偏好,动机和执行任务的方式,从而影响信息需求。用户接受度的研究表明,诸如价值和相关软问题之类的个人特征对于用户批准软件很重要。如果知道用户的主要个人价值,则软件可以自动显示界面变体,该变体提供的信息和功能与他或她的主要价值最匹配。用户的主导个人价值是最强烈地影响其态度和行为的一种。但是,用于测量用户值的现有方法需要大量工作和/或干扰用户的隐私需求。如果计划为非常大的用户群定制界面,则必须大规模实现价值逼近,以将个性化软件分配给该软件的所有用户。我们的工作着重于以较少的努力和对隐私的影响来近似估计用户的主导价值。与其直接探索用户的值,不如探索基于用户对关键任务的偏好来近似这些值的潜力。制作定制版本的软件是一个单独的主题,这里没有重点介绍。在本文中,我们宁愿描述一种从任务偏好中识别用户价值的方法,以及对该方法的部分应用进行的实证研究。除了在研讨会上口头介绍的初步版本外,我们首次在本文中提出该方法。该方法包括研究过程和应用过程。在研究过程中,研究人员必须确定在被调查环境中发生的与个人价值观有关的关键任务。这些关键任务可以在应用程序过程中使用,以近似地估计新用户的主导价值。在这项实证研究中,我们证明了我们方法的研究过程使我们能够确定在共享护理环境下近似价值的关键任务。发现大多数护士具有以下三个主要价值观之一:仁慈,自我指导或享乐主义。数据证实了人们的普遍期望:与所有其他护士相比,具有仁慈价值的护士对能够帮助人们立即或改善治疗状况的任务具有更高的偏爱。与所有其他护士相比,具有自我指导性的参与者不喜欢会影响其个人自由的任务,而享乐主义的用户则不太喜欢那些涉及体力劳动的任务,而偏爱那些希望得到满足的任务。我们的发现通过询问较少关注隐私的问题,提高了在大型用户群体中的个人价值观的度量。但是,该方法在最初的研究过程中需要大量的精力来准备这种测量。未来的工作包括在其他情况下复制我们的方法,以及为用户确定与价值相关的任务,这些任务具有不同于我们的经验研究重点关注的三个价值的其他价值。

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