家中的机器人——在智能机器人公寓中,情感、技术承诺和个性特征如何影响用户体验

Jasmin Bernotat, F. Eyssel
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引用次数: 24

摘要

先前的研究表明,用户特征,如情感、人格特征、用户性别、技术承诺、技术使用的感知易用性和被观察的感觉影响人与技术交互(例如,[1],[2])。迄今为止,大多数研究都集中在与单一技术设备(如智能手机、音频播放器(如[3])或计算机(如[1])交互时用户特征的影响上。为了扩展这项工作,我们研究了个人用户特征、任务完成的感知容易程度以及被观察的感觉对人机交互和人机交互(HRI)的影响。我们探索了参与者如何在智能实验室公寓内解决七项任务。为此,我们收集了视频数据,并辅以调查数据来调查naïve用户对智能家居和机器人的态度。用户特征如亲和性、低负面影响、技术接受度、低技术使用感知能力和感知任务易用性是智能机器人公寓内积极用户体验的预测因子。回归分析显示,对机器人的积极评价是由积极影响预测的,在较小程度上是由技术接受度预测的。通过对机器人的积极评价来预测与机器人的实际互动,并在较小程度上通过技术接受度来预测。此外,我们的研究结果表明,在智能公寓中,用户特征和任务的容易程度会影响HRI。讨论了未来如何研究用户和进一步任务特征的相互作用以提高HRI的意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A robot at home — How affect, technology commitment, and personality traits influence user experience in an intelligent robotics apartment
Previous research has shown that user features like affect, personality traits, user gender, technology commitment, perceived ease of technology use, and the feeling of being observed impact human-technology interaction (e.g., [1], [2]). To date, most studies have focused on the influence of user characteristics while interacting with single technical devices such as smart phones, audio players (e.g., [3]), or computers (e.g., [1]). To extend this work, we investigated the influence of individual user characteristics, the perceived ease of task completion, and the feeling of being observed on human-technology interaction and human-robot interaction (HRI) in particular. We explored how participants would solve seven tasks within a smart laboratory apartment. To do so, we collected video data and complemented this analysis with survey data to investigate naïve users' attitudes towards the smart home and the robot. User characteristics such as agreeableness, low negative affect, technology acceptance, low perceived competence regarding technology use, and the perceived ease of task were predictors of positive user experiences within the intelligent robotics apartment. Regression analyses revealed that a positive evaluation of the robot was predicted by positive affect and, to a lesser extent, by technology acceptance. Actual interactions with the robot were predicted by a positive evaluation of the robot and, to a lesser degree, by technology acceptance. Moreover, our findings show that user characteristics and, by tendency, the ease of task impact HRI within an intelligent apartment. Implications for future research on how to investigate the interplay of user and further task characteristics to improve HRI are discussed.
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