IEEE Robotics & Automation Magazine - June 2016 - 57

the child. By building on the learning by teaching para-
digm, not only does the child practice handwriting, but
also, as they take on the role of the teacher, they positively
reinforce their self-esteem and motivation: their social
role shifts from the underperformer to the one who
knows and teaches. In addition, by relying on a robot, we
can tailor the exercises and the learning curve individual-
ly to each child's needs as we will show in this article.
Learning by Teaching Handwriting
The learning by teaching paradigm, which engages the stu-
dent in the act of teaching another, has been shown to pro-
duce motivational, metacognitive, and educational benefits in
a range of disciplines [14]. The application of this paradigm to
handwriting intervention remains, however, unexplored. One
reason for this may be due to the requirement of an appropri-
ately unskilled peer for the child to tutor: this may prove diffi-
cult if the child is the lowest performer in the class. In some
cases, it may be appropriate for a peer or a teacher to simulate
a naive learner for the child to teach. For handwriting, howev-
er, where one's skill level is visually evident, this acting is likely
to be rapidly detected. This motivates the use of an artificial
teachable agent that can be configured for a variety of skill
levels and for which children do not have preconceptions
about its handwriting ability.
Robots have been used as teachers or social partners to
promote children's learning in a range of contexts, most com-
monly related to language skills [4] and less often to physical
skills (such as calligraphy [12]). Looking at the converse
(humans teaching robots), Werfel notes in [18] that most of
the work focuses on the robot's benefits (in terms of language
[15] or physical [13] skills, for example) rather than the learn-
ing experienced by the human tutor themselves. Our work
concentrates on this latter aspect: by demonstrating handwrit-
ing to a robot, we aim at improving the child's performance. A
robotic learning agent that employs the learning by teaching
paradigm has previously been developed by Tanaka and Mat-
suzoe [17]. In their system, children learn vocabulary by
teaching the NAO robot to act out verbs. The robot is teleop-
erated (Wizard of Oz) and mimics the actions that the chil-
dren teach it but with no long-term memory or learning
algorithm in place. Our project significantly extends this line
of work in two ways. First, by investigating the context of the
children's acquisition of a challenging physical skill (handwrit-
ing) and second by proposing a robotic partner that is fully
autonomous in its learning.
Agency and Commitment
We also investigate a particular role for a robot in the educa-
tion of handwriting: not only is the robot actively performing
the activity by drawing letters, but it also does so in a way
that engages the child in a very specific social role. The child
is the teacher in this relationship, and the robot is the learner:
the child is to engage in a (meta) cognitive relationship with
the robot to try to understand why the robot fails and how to
best help it. Here, the robot is more than just an activity facil-

itator or orchestrator-its physical presence and embodi-
ment induce agency and anthropomorphizing and
cognitively engage the child into the learning activity (be it
consciously or not).
The commitment of the child into the interaction builds on a
psychological effect known as the protégé effect [2]: the teacher
feels responsible for his
student, commits to the
student's success, and pos-
The learning by teaching
sibly experiences the stu-
dent's failure as his own
paradigm, which engages
failure to teach. Teachable
computer-based agents
the student in the act of
have previously been used
to encourage this protégé
teaching another, has
effect, wherein students
invest more effort into
been shown to produce
learning when it is for a
teachable agent than for
motivational, metathemselves [2]. We rely on
this cognitive mechanism
cognitive, and educational
to reinforce the child's
commitment into the
benefits in a range
robot-mediated handwrit-
ing activity, and we show
of disciplines.
sustained child-robot
engagement over extend-
ed periods of time (several hours spread over a month).
For these two reasons, our approach is to be distinguished
from previous works on educational robotics. Most of these
do not consider the agency induced by the robot beyond its
motivational aspect (playing with an interactive partially
autonomous device induces excitement-at least, for the
short term). In our case, the role of agency is stronger: it
induces metacognition ("I am interacting with an agent, so I
need to reflect on how to best teach him"), which is benefi-
cial for the learning process; it also induces a protégé effect
("I want my robot-agent to succeed!"), which also supports
the commitment of the child into the interaction for longer
periods of time. These initial considerations can be turned
into a set of research questions:
● How to develop a fully autonomous robotic system that
produces believable handwriting, fosters interaction, and
adequately learns from the children's demonstration?
● Can such a system be accepted by children and practitio-
ners alike and eventually be integrated in existing educative
and therapeutic practices?
● Can we build and evidence interactions that sustain chil-
dren's engagement over extended periods of time?
● Is this novel approach effective?
● Do we evidence actual handwriting improvements by chil-
dren facing difficulties?
Implementation of the Interaction
Figures 1 and 2 illustrate our general experimental setup: a
face-to-face child-robot interaction with an autonomous
june 2016

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