Introduction to (Re)Using Questionnaires in Human-Robot Interaction Research

Rueben, Matthew; Elprama, Shirley; Chrysostomou, Dimitrios; Jacobs, An

doi:10.1007/978-3-030-42307-0_5

Cited by 15 publications

(10 citation statements)

References 15 publications

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“…The study was first pilot-tested with 10 naïve users to confirm the reliability of the constructed scale and get a sense of the time to complete it in order to inform pricing, following recommendations from [51]. These users were excluded from the full study.…”

Section: Methodsmentioning

confidence: 99%

Using Design Metaphors to Understand User Expectations of Socially Interactive Robot Embodiments

Changxiao¹,

Hadiwijoyo²,

Chen³

et al. 2022

Preprint

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The physical design of a robot suggests expectations of that robot's functionality for human users and collaborators. When those expectations align with the true capabilities of the robot, interaction with the robot is enhanced. However, misalignment of those expectations can result in an unsatisfying interaction. This paper uses Mechanical Turk to evaluate user expectation through the use of design metaphors as applied to a wide range of robot embodiments. The first study (N=382) associates crowd-sourced design metaphors to different robot embodiments. The second study (N=803) assesses initial social expectations of robot embodiments. The final study (N=805) addresses the degree of abstraction of the design metaphors and the functional expectations projected on robot embodiments. Together, these results can guide robot designers toward aligning user expectations with true robot capabilities, facilitating positive human-robot interaction.CCS Concepts: • Human-centered computing → HCI theory, concepts and models; Empirical studies in HCI; • Computer systems organization → Robotics.

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Section: Methodsmentioning

confidence: 99%

Using Design Metaphors to Understand User Expectations of Socially Interactive Robot Embodiments

Changxiao¹,

Hadiwijoyo²,

Chen³

et al. 2022

Preprint

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“…These issues can have implications for social robotics studies that should be addressed to improve assessment quality and results and advance robotic system designs and tasks accurately. More recently, the work shown in [204] proposed a standardized process for choosing and using scales and questionnaires used in human-robot interaction. For instance, the authors in [204] specified that a scale cannot be trusted in a certain study if not already validated in a similar study and that scales can be unfit or have limitations concerning a specific study.…”

Section: Metrics Of Human Perception and Acceptabilitymentioning

confidence: 99%

“…More recently, the work shown in [204] proposed a standardized process for choosing and using scales and questionnaires used in human-robot interaction. For instance, the authors in [204] specified that a scale cannot be trusted in a certain study if not already validated in a similar study and that scales can be unfit or have limitations concerning a specific study. In such a case, they should be modified and re-validated.…”

Section: Metrics Of Human Perception and Acceptabilitymentioning

confidence: 99%

A Survey on Recent Advances in Social Robotics

et al. 2022

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Over decades, social robotics has evolved as a concept that presently covers different areas of application, and interacts with different domains in technology, education, medicine and others. Today, it is possible to envision social robots in tasks that were not expected years ago, and that is not only due to the evolution of social robots, but also to the evolution of the vision humans have for them. This survey addresses recent advances in social robotics from different perspectives. Different contexts and areas of application of social robots are addressed, as well as modalities of interaction with humans. Different robotic platforms used in social contexts are shown and discussed. Relationships of social robotics with advances in other technological areas are surveyed, and methods and metrics used for the human evaluation of the interaction with robots are presented. The future of social robotics is also envisioned based on surveyed works and from different points of view.

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“…We have enhanced our VA with natural timing capabilities, and we performed a large-scale user study focused on tracking the comfortability of the users and the usability and cognitive requirements of our overall system. Based on the learnings from other researchers [33]- [35], and our lessons learned from standardising HRI and HRC experiments before [36], [37], we evaluated the system's usability with the SUS scale [38], the perceived mental load while working on the task, based on the NASA TLX index [39], the Perceived Competence, Performance Expectancy and Effort Expectancy metrics in-spired by [33] and Comfortability Scale based on our uniquely designed questionnaire.…”

Section: Related Workmentioning

confidence: 99%

Hey Max, can you help me? An Intuitive Virtual Assistant for Industrial Robots

Li¹,

Chrysostomou²,

Pinto³

et al. 2022

Preprint

Self Cite

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<p>Assisting employees in acquiring the knowledge and skills necessary to grasp and use new services and technologies on the shop floor is critical for manufacturers to adapt to Industry 4.0 successfully. In this paper, we employ a Learning, Training, Assistance (LTA) approach and propose a framework for a Language-enabled Virtual Assistant (VA) to facilitate this adaptation. In our system, the human-robot interaction is achieved through spoken natural language and a dashboard implemented as a web-based application. This type of interaction enables operators of all levels to control a collaborative robot intuitively in several industrial scenarios and use it as a complementary tool for developing their competencies. Our proposed framework has been extensively tested with 29 users who completed various tasks while interacting with the proposed VA and industrial robots. Through three different scenarios, we evaluated the usability of the system for LTA based on an established System Usability Scale and the cognitive effort required by the users based on the standardised NASA TLX questionnaire. The qualitative and quantitative results of the study show that users of all levels found the VA user friendly with low requirements for physical and mental effort during the interaction. Additionally, the study demonstrates that the VA enables operators to streamline the learning and training phases of new tasks and improve their user experience during the assistance phase for daily tasks. The source code of the proposed VA and the supplementary material of the user study are accessible at https://bit.ly/VA MAX to support the reproducibility of the proposed framework.</p>

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Introduction to (Re)Using Questionnaires in Human-Robot Interaction Research

Cited by 15 publications

References 15 publications

Using Design Metaphors to Understand User Expectations of Socially Interactive Robot Embodiments

Using Design Metaphors to Understand User Expectations of Socially Interactive Robot Embodiments

A Survey on Recent Advances in Social Robotics

Hey Max, can you help me? An Intuitive Virtual Assistant for Industrial Robots

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