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A Design Strategy for Meaningful HRI Discussions in Elementary School

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Abstract

This position paper describes the experimental behavior design of the adaptable humanoid social robot Pepper in four different roles in class. In 2018 and 2019, we held English classes in seven Finnish elementary schools with a twofold mission. Our aim was both to showcase these four different social roles in an English class of 5th graders and to discuss future robot-assisted education and collaborative learning with the children. As a design strategy, we developed pedagogical robot applications and adopted the content to the curriculum of the 5 th grade and to cultural phenomena that Finnish children aged 10-12 were well familiar with. However, although one thoroughly designs for a meaningful experience of-and interaction with-a robot, other factors are at play that affect the perception of the robot and interaction with it. All things considered, we conclude that co-created robot applications, corresponding to the curriculum and contemporary youth culture that the children interact with co-present in class, offer an interesting and accessible opportunity for children to reflect on the use and design of socially assistive robots.
A Design Strategy for Meaningful HRI
Discussions in Elementary School
Susanne Hägglund
Experience Lab
Åbo Akademi University
Vaasa, 65101, FINLAND
susanne.hagglund@abo.fi
Sören Andersson
Experience Lab
Åbo Akademi University
Vaasa, 65101, FINLAND
soren.andersson@abo.fi
Yvonne Backholm-Nyberg
Experience Lab
Åbo Akademi University
Vaasa, 65101, FINLAND
ybackhol@abo.fi
Abstract
Thisposition paper describes
theexperimentalbehaviordesign
oftheadaptablehumanoid social
robotPepperinfourdifferent roles in class.In 2018 and
2019, we held English classes in
sevenFinnishelementary schoolswith a
twofoldmission.Our aim wasbothto showcase
thesefourdifferentsocial rolesin an English class of
5thgradersandtodiscussfuturerobot-assisted
educationand collaborative learningwith the
children.As a design strategy, we developed
pedagogical robot applications and adopted the content
to the curriculum of the 5thgrade and to cultural
phenomena thatFinnishchildren aged 10-12were well
familiar with.
However, although one thoroughly designs for a
meaningful experience of - and interaction with - a
robot, other factors are at play that affect the
perception of the robot and interaction with it. All
things considered, we conclude that co-created robot
applications, corresponding to the curriculum and
contemporary youth culture that the children interact
with co-present in class, offer an interesting and
accessible opportunity for children to reflect on the use
and design of socially assistive robots.
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uses, contact the owner/author(s).
NordiCHI 2020 Empowering Children’s Critical Reflections on AI, Robotics
and Other Intelligent Technologies workshop, October 26, 2020. Tallinn,
Estonia.
© 2020 Copyright is held by the owner/author(s).
Author Keywords
Human-robot interaction; Design methods; Socially
Assistive Robots in Education; Co-creation.
CSS Concepts
Human-centered computing -> Interaction
design -> Interaction design process and
methods -> Contextual design
1. Introduction
SociallyAssistiveRobots(SARs) supportstudents and
teachers in educational contexts through social
interaction in various roles. They serve as tutors,
companions or peers, and teachers with the aim of
supporting and enhancing learning outcomes[1]. We
set out to discuss robot-assisted education andwork life
with children and chose to designtrustworthy scenarios
of how robot-assisted education may be shaped as a
basis for reflection in class. Our background lies in
exploratory design research, using in particular
Research through Design methods, in human-computer
interaction. Therefore, we wanted to explore whether
designing curriculum aligned applications for a co-
located, socially present robot could be the right design
choice to makefor our purposes of a meaningful and
critical discussion of future robot-assisted education
together with10-12-year-oldFinnishpupils.
This position paper is not to be considered as a
formalcontentanalysisofthe discussion following the
children-robot interaction but rather as asubjective,
selectiveinterpretation of thechildren’sperceptions
of the experience design,andhow well it served our
purposes of a group discussionon robot-
assistededucation.We found thattherobotapplications
workedratherwell as a foundation fora lively, fruitful
and open-mindeddiscussion on robot-assisted
education with the children.Hence, we argue that
adesign strategythatinvolvesthe teachers prior to visit
in class, which supports co-creation of robot
applications with teachers and students, aligning them
with curriculum and youth culture, is well worth
consideringas a valuable path towards a rich
discussionwith children onSAR’spotential,use
casesandimplications. By sharing our experience of
child-robot interaction in class as a basis for reflection
on use of SARs, we hope to contribute to the discussion
on how children may be given opportunities to discuss
the topic and how to design for a relevant and
accessible experience.
2. Experience Design Strategy
Within a national projecton future technologyand co-
learningin education,we set out todiscuss socially
assistive robots together with children aged 10-
12.Weascribedthe robot Pepperfourroles in the class,
that ofa study buddy/friend,a pupil thatthe child will
teach,a collaborative agent in a team with human
beings,and as asolitaryteacher.
In order to meet the goals of the set design strategy,
we decided to use a blend of proof-of-concept
demonstration and speed dating[2]as a basis for
theclassroomdiscussionwith the children. Theywere
voluntarily -interacting withsixadaptablerobot
programs where the robot assumesthree different
roles, those of a peer, a teacher and a pupil.The fourth
role of the robot was beingan adaptivepart of a
team,togetherwith two humans.Although the children
didn’t explore any of the content and scenarios in
depth, our hypothesis was thatthe likelihood of them
forming an opinion on the topic wouldbeincreased after
the opportunity to watch and/or try out interacting with
the robot in these contexts.
Theeducational robot applicationsderive from two
contexts. Firstly, the current curriculum of the 5thgrade
English subject in Finnish elementary school was at the
core of the robot application content. As an example,
we created a scenario where Pepper was acting out the
nouns and verbs in essence the homework of the
Englishsubjectmuch like in the gameCharadeswith
the children. The idea here was to explore the robot in
a peer role,mimicking a fellow pupilpracticingthe
homework with anotherchild.For instance, Pepper
pretended to fly like an airplane and asked the children,
in English,“What am I doing now?”The robot
adopteditsanswer to whether the response of the child
was correct or incorrect.
Another example is theadapted Basic
channelapplication, where the children
wereposingquestionstoPepper, ranging from social and
cognitive life of the robot to its personality. These
discussion topicshad been practiced in class together
with the teacher prior to our visit as examplesof how to
greetandto make conversation in English.
Secondly, several schoolshadactive daily life, dancing
and motion in everyday life as a special theme. We
chose to highlight thisthemeas well, and included
scenarios where dancing was taught in class with the
children and the robot, working together. At the time
of the group discussions held with the children, the
floss dance was immensely popular within this age
segment. Most had heard of it, and many knew how to
do the dance, popularized by digital games
andpopularculture. Thus, we designed a scenario
where Pepper asked the childrentoteach ithow to do
the dance and for feedback as the robot did the floss
dance. This work was co-created with students prior to
discussions in class.
Wealways startedeachschoolsessionwitha
presentation of Pepper,its abilities and pre-
programmed platform. Weoutlinedtogetherthe
framework of the lecture, in terms oftransparency and
trialability[3], voluntary interaction and the elements
ofthe lesson, i.e.introduction, interaction and then
finally, discussion.
Subsequent to the applications, an unstructured group
discussion with teachers, assistive teachers, and the
children took place. We tried tore-orientthe discussion
to social robots, in case the topic resided too much on
automation of say vehicles or space crafts. The main
focus was always to open a window to future
possibilities and to keep an open discussion on what
was on the children’s mind.
We conclude that the choice of showcasing many
shallow modes of interacting with a robotin various
roles, instead ofgoinginto depthin one single use
case,was pursuing our goal of having a lively discussion
on SARs with the children.
The robot content seemed to be appreciated and our
experience design managed well in most cases to
maintain the children engaged throughout 45-50
minutes.However, in several classes, the oldest
children were at timesdissociating themselves, perhaps
because they thought it was too childish, particularly
the storytellingapplication.Also,the whole continuum of
emotions and perceptions of the robotwaspresent in
almost each class, where some of the children were
enthusiastic and excited, others were
calmlycurious,and some were reluctant and hesitant
to interact. A fewchildrenwere very suspicious. Both
positive and negative emotions were discussed and
shared throughout the session and in the group
discussion afterwards as well.   
Naturally, we identified many factors influencing the
children’s attitudes towards the robot’s performance,
abilities and possible adoptions, reflecting the group
discussion afterwards. We note that factorson a
subjective, environmental, technical, and cultural level
all affect the outcome of the child-robot interaction.
These includeprior work in class; context based issues
such as lighting, buzz and sound in the surroundings;
the children’s prior experience of social
robotics;children’s and teachers’attitudes towards
technology and robots in general;group dynamics in
the classand the more or lesssupportive role of the
teacher in the group interaction; the message, feeling
and sense ofsecurity of the researchers working
together with Pepper andholdingthe sessions;
technicalchallengesand so forth.  
3. Conclusion
The chosen design strategy served our goalratherwell.
It’s our experience that it was the right thing to design
several educational, adaptableapplications to be
interacted with a co-located, socially present robot in a
group setting in class, in order to have a lively and
insightful discussion on robot-assisted education in the
future with10-12-year-oldpupils.  
We support co-designing the applications serving as
basis for discussion with children on the one hand, for
relevant and meaningful topics and teachers on the
other, who can point to meaningful content in current
curriculum as well as introduce the topic prior to
collaborative learning scenarios in class and assist in
the discussion afterwards.  
Acknowledgements
We’d like to thank the Ministry ofEducation and
Culturefor funding our work.We’re grateful for the
workonthe technical development of the applications
provided byMenggeHu,WenhaoZhu, and Yi Zhou.
References
[1] CaitlynClabaugh, Kartik Mahajan,ShomikJain,
RoxannaPakkar, David Becerra,ZhonghaoShi, Eric
Deng, Rhianna Lee, Gisele Ragusa &
MajaMatarić.2019.Long-Term Personalization of
an In-Home Socially Assistive Robot for
ChildrenwithAutism Spectrum Disorders.Front.
Robot. AI6:110.doi: 10.3389/frobt.2019.00110.
[2] Scott E. Hudson & Jennifer Mankoff.2014.
Concepts, Values, And Methods for Technical
Human-computer Interaction. In Ways of Knowing
inHCI, Olson, J. S and Kellogg, W. A (Eds.).
Springer, New York. 69-93.
[3] Sebastian Schneider & FranzKummert.
2020.  Comparing Robot and Human guided
Personalization: Adaptive Exercise Robots are
Perceived as more Competent and Trustworthy.
International Journal of Social
Robotics.https://doi.org/10.1007/s12369-020-
00629-w
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Article
Full-text available
Socially assistive robots (SAR) have shown great potential to augment the social and educational development of children with autism spectrum disorders (ASD). As SAR continues to substantiate itself as an effective enhancement to human intervention, researchers have sought to study its longitudinal impacts in real-world environments, including the home. Computational personalization stands out as a central computational challenge as it is necessary to enable SAR systems to adapt to each child's unique and changing needs. Toward that end, we formalized personalization as a hierarchical human robot learning framework (hHRL) consisting of five controllers (disclosure, promise, instruction, feedback, and inquiry) mediated by a meta-controller that utilized reinforcement learning to personalize instruction challenge levels and robot feedback based on each user's unique learning patterns. We instantiated and evaluated the approach in a study with 17 children with ASD, aged 3–7 years old, over month-long interventions in their homes. Our findings demonstrate that the fully autonomous SAR system was able to personalize its instruction and feedback over time to each child's proficiency. As a result, every child participant showed improvements in targeted skills and long-term retention of intervention content. Moreover, all child users were engaged for a majority of the intervention, and their families reported the SAR system to be useful and adaptable. In summary, our results show that autonomous, personalized SAR interventions are both feasible and effective in providing long-term in-home developmental support for children with diverse learning needs.
Chapter
Technical HCI research seeks to improve the world by expanding the set of things that can be done with computational systems. This chapter considers this work as invention—the creation of new things—contrasted with activities of discovery which are concerned more with understanding the world. We discuss the values, goals, and criteria for success in this approach. Technical HCI research includes both directly contributing to some human need and indirectly contributingby enabling other technical work with things like toolkits.