连接点:用户如何理解和诊断智能家居生态系统

IF 5.1 2区 计算机科学 Q1 COMPUTER SCIENCE, CYBERNETICS
Mikołaj P. Woźniak , Anna Walczak , Krzysztof Grudzień , Heiko Müller , Jan Borchers , Marion Koelle , Susanne Boll
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引用次数: 0

摘要

智能家居正在演变成复杂的生态系统,但它们的内部工作原理对用户来说往往是不透明的,这限制了他们对技术进行故障排除和定制的能力。分布式和隐藏的组件使得用户很难理解这些系统的工作原理。为了设计能够为非专家提供直观故障排除的界面,我们首先需要清楚地了解它们是如何形成心理模型并本能地诊断问题的。我们对现实智能家居场景进行了三次迭代小研究,以探索用户如何感知智能家居生态系统中的互联性,以及系统复杂性如何影响他们的故障排除方法。我们确定了用户设想的常见智能家居拓扑,并对他们的诊断策略进行了分类。我们的研究结果表明,虽然用户认为他们的智能家居是分层的,但他们的心智模型往往是不完整的,目前的界面倾向于功能模型,隐藏了系统中的连接。我们为设计界面提供了七个可操作的要点,以提高用户的理解和故障排除能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Connecting the dots: How users understand and diagnose smart home ecosystems
Smart homes are evolving into complex ecosystems, but their inner workings often remain opaque to users, limiting their ability to troubleshoot and customise the technology. The distributed and hidden components make it challenging for users to understand how these systems work. To design interfaces that enable intuitive troubleshooting for non-experts, we first need a clear understanding of how they form mental models and instinctively diagnose issues. We conducted three iterative vignette studies with realistic smart home scenarios to explore how users perceive interconnectivity in smart home ecosystems and how system complexity impacts their troubleshooting approaches. We identified common smart home topologies envisioned by users and categorised their diagnostic strategies. Our findings show that while users view their smart homes as hierarchical, their mental models are often incomplete, and current interfaces favour functional models, hiding the connections in the system. We provide seven actionable takeaways for designing interfaces that improve user understanding and troubleshooting capabilities.
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来源期刊
International Journal of Human-Computer Studies
International Journal of Human-Computer Studies 工程技术-计算机:控制论
CiteScore
11.50
自引率
5.60%
发文量
108
审稿时长
3 months
期刊介绍: The International Journal of Human-Computer Studies publishes original research over the whole spectrum of work relevant to the theory and practice of innovative interactive systems. The journal is inherently interdisciplinary, covering research in computing, artificial intelligence, psychology, linguistics, communication, design, engineering, and social organization, which is relevant to the design, analysis, evaluation and application of innovative interactive systems. Papers at the boundaries of these disciplines are especially welcome, as it is our view that interdisciplinary approaches are needed for producing theoretical insights in this complex area and for effective deployment of innovative technologies in concrete user communities. Research areas relevant to the journal include, but are not limited to: • Innovative interaction techniques • Multimodal interaction • Speech interaction • Graphic interaction • Natural language interaction • Interaction in mobile and embedded systems • Interface design and evaluation methodologies • Design and evaluation of innovative interactive systems • User interface prototyping and management systems • Ubiquitous computing • Wearable computers • Pervasive computing • Affective computing • Empirical studies of user behaviour • Empirical studies of programming and software engineering • Computer supported cooperative work • Computer mediated communication • Virtual reality • Mixed and augmented Reality • Intelligent user interfaces • Presence ...
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