User experience of industrial robots over time

Buchner, Roland; Wurhofer, Daniela; Weiss, Astrid; Tscheligi, Manfred

doi:10.1145/2157689.2157712

Cited by 15 publications

(6 citation statements)

References 6 publications

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“…Users’ acceptance of robots is largely influenced by their feelings of security during HRI, and an understanding of the factors that could influence their sense of security would contribute to the development of more context-sensitive robots (Buchner et al , 2012; Dautenhahn et al , 2006; Jindai and Watanabe, 2007). In HRI, feelings of security not only refer to physical safety, but also include feelings of comfort and fears of harm from robotic errors when human and robots co-exist in the same environment.…”

Section: Literature Reviewmentioning

confidence: 99%

Exploring customer experiences with robotics in hospitality

Tung

2018

IJCHM

320

272

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Purpose The purpose of this study is to explore consumer reviews with robotics based on the five dimensions for evaluating user experiences (i.e. embodiment, emotion, human-oriented perception, feeling of security and co-experience), as derived from research in human-robot interactions (HRI). Design/methodology/approach The study first reviews the five dimensions for evaluating user experiences in HRI and then analyzes user experiences with robotics at four hotels (i.e. Yotel New York, Aloft Cupertino, Henn-na Hotel Japan and Marriott Residence Inn LAX) based on reviews on TripAdvisor, Agoda, Yelp and Booking.com. Findings The findings highlight the influence of robotic embodiment and human-oriented perceptions on consumer experiences. The findings also suggest that users and robots can co-create novel experiences, with some guests even proactively seeking new opportunities to interact and communicate with robots to develop a certain level of “relationship” with them. Research limitations/implications An understanding of user experiences from HRIs can inform future hospitality and tourism research and management. Practical implications This study contributes to hospitality and tourism management by highlighting current practices with robotics to suggest areas of improvements for enhancing future consumer experiences. Social implications Consumer experiences will change rapidly as hospitality and tourism management deploys robotics in the future. Originality/value This is one of the early studies in the field to explore consumer experiences with robotics based on the five dimensions for evaluating user experiences from research in HRI. In doing so, this study provides a number of theoretical and managerial implications relevant for hospitality and tourism research and practice.

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Section: Literature Reviewmentioning

confidence: 99%

Exploring customer experiences with robotics in hospitality

Tung

2018

IJCHM

320

272

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“…As novel robotic systems are the most influential change for working routines in the production. It was relevant to understand on a behavioral and reflective level how the cooperation with these systems looks like Buchner et al (2012Buchner et al ( , 2013a operators and maintainers and are crucial for successful cooperation and production, but have very limited technology support for their work ). Finally, we explored human-robot collaboration in the factory in order to find out how the increasing deployment of robots in the factory is experienced by the operators and to identify possible changes in the cooperation between them (Buchner et al , 2013a.…”

Section: Exploring the Factorymentioning

confidence: 99%

Designing Socially Embedded Technologies in the Real-World

Wulf¹,

Schmidt²,

Randall³

2015

Computer Supported Cooperative Work

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The CSCW series examines the dynamic interface of human nature, culture, and technology. Technology to support groups, once largely confined to workplaces, today affects all aspects of life. Analyses of "Collaboration, Sociality, Computation, and the Web" draw on social, computer and information sciences, aesthetics, and values. Each volume in the series provides a perspective on current knowledge and discussion for one topic, in monographs, edited collections, and textbooks appropriate for those studying, designing, or engaging with sociotechnical systems and artifacts.Titles published within the Computer Supported Cooperative Work series are included within Thomson Reuters' Book Citation Index.More information about this series at

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“…Gordon et al studied affective personalization, using reinforcement learning to determine the affective states preferred by each child during a learning interaction [4]. Likewise, Henkemans et al presented a health education robot that personalized its behavior by referring to a child's name, favorite activity, and color during conversation [6]. In our study, we focus on personalizing the timing of breaks during tutoring to enhance learning outcomes.…”

Section: Introductionmentioning

confidence: 99%

Optimizing Learning in Robot-Child Tutoring through Personalized Timing Strategies

Sinha¹,

Pendharkar

Thrigulla³

et al. 2023

Preprint

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This research focuses on exploring personalized timing strategies to optimize learning in robot-child tutoring. Non-task breaks are commonly used in education to address children's limited attention spans and promote cognitive rejuvenation. Robots provide a valuable opportunity to deliver personalized breaks tailored to the specific needs of individual students, enhancing their learning experiences. We develop an autonomous robot tutoring system that assesses students' performance and administers breaks based on personalized schedules aligned with their individual progress. Through a field study, we compare the effectiveness of different break strategies, including a fixed timing approach, a reward strategy that aligns break timing with performance improvements, and a refocus strategy that aligns break timing with performance declines. Our results demonstrate that personalized strategies significantly enhance children's learning outcomes compared to the fixed strategy. Furthermore, we observe immediate benefits in terms of improved efficiency and accuracy in completing educational tasks following personalized breaks, underscoring the restorative effects of breaks when provided at optimal moments. These findings contribute to the understanding of how personalized timing strategies can optimize learning in the context of robot-child tutoring.

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User experience of industrial robots over time

Cited by 15 publications

References 6 publications

Exploring customer experiences with robotics in hospitality

Exploring customer experiences with robotics in hospitality

Designing Socially Embedded Technologies in the Real-World

Optimizing Learning in Robot-Child Tutoring through Personalized Timing Strategies

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