TY - JOUR
T1 - Predictable Robots for Autistic Children — Variance in Robot Behaviour, Idiosyncrasies in Autistic Children’s Characteristics, and Child–Robot Engagement
AU - Schadenberg, Bob R.
AU - Reidsma, Dennis
AU - Evers, Vanessa
AU - Davison, Daniel P.
AU - Li, Jamy Jue
AU - Heylen, Dirk K.J.
AU - Neves, Carlos
AU - Alvito, Paulo
AU - Shen, Jie
AU - Pantic, Maja
AU - Schuller, Björn
AU - Cummins, Nicholas
AU - Olaru, Vlad
AU - Sminchisescu, Cristian
AU - Dimitrijevic, Snezana Babovic
AU - Petrovic, Suncica
AU - Baranger, Aurélie
AU - Williams, Alria
AU - Alcorn, Alyssa M.
AU - Pellicano, Elizabeth
N1 - Funding Information:
This work was made possible through funding from the European Union’s Horizon 2020 research and innovation program under grant agreement no: 688835 (DE-ENIGMA). Authors’ addresses: B. R. Schadenberg, D. Reidsma, D. P. Davison, J. J. Li, and D. K. J. Heylen, University of Twente, Drienerlo-laan 5, 7522 NB Enschede, The Netherlands; emails: {b.r.schadenberg, d.reidsma, d.p.davison, j.j.li, d.k.j.heylen}@utwente.nl; V. Evers, University of Twente, Drienerlolaan 5, 7522 NB Enschede, The Netherlands and Nanyang Technological University, 50 Nanyang Ave, Singapore 639798, Singapore; email: [email protected]; C. Neves and P. Alvito, IDMind, Polo Tecnologico de Lisboa, Lt 1, 1600-546 Lisbon, Portugal; emails: {cneves, palvito}@idmind.pt; J. Shen and M. Pantić, Imperial College London, South Kensington Campus Exhibition Rd, South Kensington, London SW7 2AZ, United Kingdom; emails: {jie.shen07, maja.pantic}@imperial.ac.uk; B. W. Schuller, University of Augsburg, Universitätsstraße 2, 86159 Augsburg, Germany and Imperial College London, Exhibition Rd, South Kensington, London SW7 2BX, United Kingdom; email: [email protected]; N. Cummins, University of Augsburg, Universitätsstraße 2, 86159 Augsburg, Germany and King’s College London, Strand, London WC2R 2LS, United Kingdom; email: [email protected]; V. Olaru and C. Sminchisescu, Institute of Mathematics of the Romanian Academy, Calea Griviţei 21, Bucharest, Romania; emails: {vlad.olaru, cristian.sminchisescu}@imar.ro; S. B. Dimitrijević and S. Petrović, Serbian Society of Autism, Gundulicev venac street 38, Belgrade 11000, Serbia; email: [email protected]; A. Baranger, Autism Europe, Rue Montoyer 39, Brussels 100, Belgium; email: [email protected]; A. Williams and A. M. Alcorn, University College London, Gower St, London WC1E 6BT, United Kingdom; emails: {alria.williams, a.alcorn}@ucl.ac.uk; E. Pellicano, University College London, Gower St, London WC1E 6BT, United Kingdom and Macquarie University, Balaclava Rd, Macquarie Park NSW 2109, Australia; email: [email protected].
Publisher Copyright:
© 2021 held by the owner/author(s).
PY - 2021/8/21
Y1 - 2021/8/21
N2 - Predictability is important to autistic individuals, and robots have been suggested to meet this need as they can be programmed to be predictable, as well as elicit social interaction. The effectiveness of robot-assisted interventions designed for social skill learning presumably depends on the interplay between robot predictability, engagement in learning, and the individual differences between different autistic children. To better understand this interplay, we report on a study where 24 autistic children participated in a robot-assisted intervention. We manipulated the variance in the robot’s behaviour as a way to vary predictability, and measured the children’s behavioural engagement, visual attention, as well as their individual factors. We found that the children will continue engaging in the activity behaviourally, but may start to pay less visual attention over time to activity-relevant locations when the robot is less predictable. Instead, they increasingly start to look away from the activity. Ultimately, this could negatively influence learning, in particular for tasks with a visual component. Furthermore, severity of autistic features and expressive language ability had a significant impact on behavioural engagement. We consider our results as preliminary evidence that robot predictability is an important factor for keeping children in a state where learning can occur.
AB - Predictability is important to autistic individuals, and robots have been suggested to meet this need as they can be programmed to be predictable, as well as elicit social interaction. The effectiveness of robot-assisted interventions designed for social skill learning presumably depends on the interplay between robot predictability, engagement in learning, and the individual differences between different autistic children. To better understand this interplay, we report on a study where 24 autistic children participated in a robot-assisted intervention. We manipulated the variance in the robot’s behaviour as a way to vary predictability, and measured the children’s behavioural engagement, visual attention, as well as their individual factors. We found that the children will continue engaging in the activity behaviourally, but may start to pay less visual attention over time to activity-relevant locations when the robot is less predictable. Instead, they increasingly start to look away from the activity. Ultimately, this could negatively influence learning, in particular for tasks with a visual component. Furthermore, severity of autistic features and expressive language ability had a significant impact on behavioural engagement. We consider our results as preliminary evidence that robot predictability is an important factor for keeping children in a state where learning can occur.
KW - UT-Hybrid-D
KW - Autism spectrum condition
KW - Engagement
KW - Human-robot interaction
KW - Individual differences
KW - Variability
KW - Predictability
U2 - 10.1145/3468849
DO - 10.1145/3468849
M3 - Article
SN - 1073-0516
VL - 28
JO - ACM Transactions on Computer-Human Interaction
JF - ACM Transactions on Computer-Human Interaction
IS - 5
M1 - 3468849
ER -