=Paper=
{{Paper
|id=Vol-3906/paper2_SCRITA
|storemode=property
|title=Trust “in the field": Reflections on a real-world lab deploying social robots in childcare settings (short paper)
|pdfUrl=https://ceur-ws.org/Vol-3906/paper2_SCRITA.pdf
|volume=Vol-3906
|authors=Nora Weinberger,Kathrin Gerling,Jan Ole Rixen,Barbara Bruno
|dblpUrl=https://dblp.org/rec/conf/ro-man/WeinbergerGRB24
}}
==Trust “in the field": Reflections on a real-world lab deploying social robots in childcare settings (short paper)==
https://ceur-ws.org/Vol-3906/paper2_SCRITA.pdf
Trust “in the field": Reflections on a Real-World Lab
Deploying Social Robots in Childcare Settings - Abstract
Nora Weinberger1 , Kathrin Gerling2 , Jan Ole Rixen2 and Barbara Bruno3,*
1
Institute for Technology Assessment and System Analysis (ITAS), Karlsruhe Institute of Technology (KIT), Germany
2
Human-Computer Interaction and Accessibility (HCI), Karlsruhe Institute of Technology (KIT), Germany
3
Socially Assistive Robotics with Artificial Intelligence (SARAI) Lab, Karlsruhe Institute of Technology (KIT), Germany
Abstract
Trust is highly relevant in human-robot interaction, particularly when it takes place in complex and dynamic
social environments. Here, we give an overview of our research within the Real-World Lab Robotics-AI, an inter-
and transdisciplinary research effort in which robots are embedded in society in long-term field research. We
focus on two particularly challenging research sites, a kindergarten and an inclusive daycare, and reflect upon
implications for researching and designing for trust in robots in this context.
Keywords
Child-Robot Interaction, Field Research, Trust
1. Introduction
Trust in robots is a concept as fundamental as it is elusive for Human-Robot Interaction (HRI) research
[1, 2]. A person’s trust in an AI-enabled technology, as most robots are, affects their intention to engage
with the technology [3] and thus ultimately determines whether the potential benefits associated with
the new technology will translate into real gains. Research on trust in HRI, following the same path as
robotics itself, initially focused on industrial automation contexts and adults directly interacting with
the robot [1] and only recently opened to socially assistive robots and their unique challenges [4].
The potential benefits of integrating socially assistive robots into kindergartens are well documented
in the literature: social robots can deliver personalised and interactive learning experiences [5], thereby
improving engagement and comprehension among young children [6], and they can act and be perceived
as non-judgemental companions, aiding in the development of critical social skills and emotional
regulation [7]. However, as expected, the effectiveness of social robots in these roles is heavily dependent
on the level of trust that children, educators, managers and parents place in them [8, 9]. The variety
of stakeholders is only one of the challenges facing the analysis of trust in social robots in childcare
settings, alongside the dynamic and unstructured nature of the environment in which the human-robot
interactions occur, the necessarily long-term nature of the interventions and the need to properly
account for the capabilities of the stakeholders (e.g., including 3-5 year old children) when developing
measurement tools [2, 4].
The possibility of conducting long-term research on socially assistive robotics in childcare settings
offered by the Real-World Lab Robotics-AI project provides us with a unique opportunity to contribute
to the understanding of trust (and its evolution) on socially assistive robots “in the field”. In this position
ALTRUIST, BAILAR, SCRITA, WARN 2024: Workshop on sociAL roboTs for peRsonalized, continUous and adaptIve aSsisTance,
Workshop on Behavior Adaptation and Learning for Assistive Robotics, Workshop on Trust, Acceptance and Social Cues in
Human-Robot Interaction, and Workshop on Weighing the benefits of Autonomous Robot persoNalisation. August 26, 2024,
Pasadena, USA
*
Corresponding author.
$ nora.weinberger@kit.edu (N. Weinberger); kathrin.gerling@kit.edu (K. Gerling); jan.rixen@kit.edu (J. O. Rixen);
barbara.bruno@kit.edu (B. Bruno)
https://www.itas.kit.edu/ (N. Weinberger); https://hci.iar.kit.edu/ (K. Gerling); https://hci.iar.kit.edu/ (J. O. Rixen);
https://sarai.iar.kit.edu/ (B. Bruno)
0000-0003-0953-7173 (B. Bruno)
© 2024 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR
ceur-ws.org
Workshop ISSN 1613-0073
Proceedings
Figure 1: Left: the partner kindergarten. Right: the robots.
paper, we outline the specific objectives we aim for and the methodology we intend to pursue to achieve
them.
2. The Real-World Lab "Robotics-AI"
The Real-World Lab Robotics-AI project involves multiple research sites, including a kindergarten and a
daycare, and follows the “Real-World Lab” paradigm [10] which seeks to bring research outside of its
usual controlled settings to enable involving society in research and mutual learning.
2.1. Research Site 1: Robot-Mediated learning activities for a Kindergarten Setting
One of the project partners is a kindergarten operated by a state-recognised provider of youth welfare
services, which offers 50 spots for children aged 3 years up to school entry (see Figure 1-left). The
pedagogical focus of the kindergarten is on science and technology, as well as movement and sports. Ad-
ditionally, the kindergarten provides a cross-group bilingual program through native English-speaking
teachers. Through a years-long collaboration with KIT, the kindergarten regularly incorporates socially
assistive robots (NAO and Pepper, shown in Figure 1-right) into their activities with children. Under
teacher guidance, these robots engage children through playful activities, such as guiding them through
language learning games and physical exercises.
2.2. Research Site 2: Supporting Children in an Inclusive Daycare Setting
Within the project we also cooperate with an inclusive daycare centre that cares for approximately 75
children. As an inclusive institution, the daycare is looking after both disabled and non-disabled children
who spend their daily lives together. While this inclusive approach can lead to different development
stages between children of similar ages, a wide age range - of one to six years - further introduces a
plethora of different needs and desires managed by the caregivers. Caregivers put great effort toward
the inclusion of all by e.g. including lessons in sign language in their interactions with the children
equipping both non-verbal and verbal children alike with tools to communicate with them and amongst
each other. The daycare also routinely incorporates a NAO robot to engage the children in physical
activities or storytelling sessions.
3. Research Objectives
Since trust (by all involved stakeholders) is a pre-requisite for a successful robot integration in any
educational context and since the “Real-World Lab Robotics-AI" project ultimately aims at developing
and deploying social robots that can support the activities and objectives of the partner research sites,
a key objective of the project is to understand how trust in robots evolves in the two complex social
environments. Referring to established findings and naming conventions on trust in HRI settings [1],
we specifically aim to consider:
• environmental factors, namely the impact of the deployment context, including its social setting
and dynamics;
• human-related factors, including ability-based factors such as prior experience with robots and
technical competence and personal characteristics such as demographics, attitude towards robots
and, specifically, disabilities;
• robot-related factors, including the robot’s behaviour and role in the interactive activity, as well
as the perceived individual and/or community benefit.
To address these research objectives, we have formulated the following key questions that guide our
investigation:
1. To what extent does the social environment within a kindergarten, including peer and teacher
interactions, affect children’s trust in social robots?
2. How do disabled children engage in interaction with social robots, and are there specific adapta-
tions that can enhance trust?
3. How do perceived educational and developmental benefits influence children’s, educators’ and
parents’ trust in social robots in early childhood education?
4. How does the nature and quality of interaction experiences between children and social robots
influence the development of trust over time?
4. Research Methodology
The striking diversity among our stakeholders suggests that a portfolio of research methods should be
favoured over a "one-fits-all" solution, to take into account and adjust to different abilities, roles and
requirements [2, 4]. The use of different instruments and methods, while promoting the validity of the
results, brings up the challenge of ensuring their comparability.
Alongside the problem of how to measure trust, stands the challenge of identifying what else we
need to measure, since the real-world, peculiar and dynamic conditions of our research sites make
it non-trivial to identify the environmental and social factors that need to be modelled to obtain an
accurate picture of user trust.
To address our research questions and overcome the afore-identified challenges, our project will
undertake an exploration of trust at the two research sites, examining each context both separately and
comparatively. We envision to leverage the multidisciplinary expertise within the project consortium
(including our practice partners) to utilise a mixed-methods approach attuned to each of the sites and
capture the multifaceted nature of trust by combining day-to-day observations and robot logs with
questionnaires and semi-structured interviews.
Given the embedded nature of our research approach, day-to-day observations of participant interac-
tions with robots in combination with robot activity logs and metrics of use will lay the foundation
for work; such real-time behavioural observations (conducted and analysed by qualified experts) will
offer insight into non-verbal indicators of trust, e.g., body language, and allow for identifying potential
correlations with contextual, social and/or robot-related events.
These data will be supplemented by questionnaires and semi-structured interviews, regularly explor-
ing user trust levels. This will provide additional insight into subjective experiences and the underlying
reasons for user trust or distrust in the robots. Since valid and reliable questionnaire only exist for
adults directly interacting with robots [11], semi-structured interviews will be particularly useful with
all the adults indirectly involved in the human-robot interaction. To overcome the lack of validated
questionnaires for children [2], while looking forward to advancements from the community, we will
explore research approaches that are accessible to verbal and non-verbal children alike, facilitating
modes of participation that align with individual children’s preferences (e.g., drawing upon augmenta-
tive and alternative communication, employing visual methods [12], and working closely with carers
and parents/guardians), and generally building on previous work on inclusive participation in our
research community [13].
5. Conclusions
Measuring trust in socially assistive robots is an open challenge due to the varying perspectives and
expectations among different stakeholders, the long interaction required for the robot to reveal its
benefits and the dynamic and unstructured environment in which the human-robot interaction occurs.
The Real-World Lab approach pursued in the “Real-World Lab Robotics-AI" project allows us to study
the full complexity of human-robot trust beyond the dyadic relationship between humans and robots,
particularly in the dynamically changing environments of the two different childcare settings.
Through the project we aim to develop accessible methods to explore what trust in socially assistive
robots means to our different stakeholders groups, with a special emphasis on the needs of the children.
We hope that by identifying and contextualising factors of relevance, real-world labs can provide deeper
insights into the dynamics of trust in human-robot interactions in realistic social and assistive settings.
Acknowledgments
This work was funded by the Baden-Württemberg Ministry of Science, Research and Art (MWK), via
the state digitalisation strategy digital@bw.
References
[1] P. A. Hancock, D. R. Billings, K. E. Schaefer, J. Y. Chen, E. J. De Visser, R. Parasuraman, A
meta-analysis of factors affecting trust in human-robot interaction, Human factors 53 (2011)
517–527.
[2] R. Stower, N. Calvo-Barajas, G. Castellano, A. Kappas, A meta-analysis on children’s trust in social
robots, International Journal of Social Robotics 13 (2021) 1979–2001.
[3] H. Choung, P. David, A. Ross, Trust in ai and its role in the acceptance of ai technologies,
International Journal of Human–Computer Interaction 39 (2023) 1727–1739.
[4] A. Langer, R. Feingold-Polak, O. Mueller, P. Kellmeyer, S. Levy-Tzedek, Trust in socially assistive
robots: Considerations for use in rehabilitation, Neuroscience & Biobehavioral Reviews 104 (2019)
231–239.
[5] P. Vogt, M. De Haas, C. De Jong, P. Baxter, E. Krahmer, Child-robot interactions for second
language tutoring to preschool children, Frontiers in human neuroscience 11 (2017) 73.
[6] D. Conti, C. Cirasa, S. Di Nuovo, A. Di Nuovo, “robot, tell me a tale!” a social robot as tool for
teachers in kindergarten, Interaction Studies 21 (2020) 220–242.
[7] R. Caceffo, D. A. Gonçalves, R. Bonacin, J. C. dos Reis, J. A. Valente, M. C. C. Baranauskas, Children’s
social interactions within a socioenactive scenario, Computers & Education 176 (2022) 104324.
[8] K. A. Brink, H. M. Wellman, Robot teachers for children? young children trust robots depending
on their perceived accuracy and agency., Developmental Psychology 56 (2020) 1268.
[9] M. H. Smakman, E. A. Konijn, P. Vogt, P. Pankowska, Attitudes towards social robots in education:
Enthusiast, practical, troubled, sceptic, and mindfully positive, Robotics 10 (2021) 24.
[10] O. Parodi, A. Steglich, J. Bylund, Real-world lab, Handbook transdisciplinary learning (2023)
287–296.
[11] K. E. Schaefer, Measuring trust in human robot interactions: Development of the “trust perception
scale-hri”, in: Robust intelligence and trust in autonomous systems, Springer, 2016, pp. 191–218.
[12] K. Gerling, K. Hicks, M. Kalyn, A. Evans, C. Linehan, Designing movement-based play with young
people using powered wheelchairs, in: Proceedings of the 2016 CHI Conference on Human Factors
in Computing Systems, CHI ’16, Association for Computing Machinery, New York, NY, USA, 2016,
p. 4447–4458. URL: https://doi.org/10.1145/2858036.2858070. doi:10.1145/2858036.2858070.
[13] J. Falk, A. Blumenkranz, M. Kubesch, R. Vetter, L. Hofer, C. Frauenberger, Designing diverse
pathways for participation, in: Proceedings of the CHI Conference on Human Factors in Computing
Systems, CHI ’24, Association for Computing Machinery, New York, NY, USA, 2024. URL: https:
//doi.org/10.1145/3613904.3642240. doi:10.1145/3613904.3642240.