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 J.
AU - Heylen, Dirk K.J.
AU - Neves, Carlos
AU - Alvito, Paulo
AU - Shen, Jie
AU - Pantić, Maja
AU - Schuller, Björn W.
AU - Cummins, Nicholas
AU - Olaru, Vlad
AU - Sminchisescu, Cristian
AU - Dimitrijević, Sneå3/4ana Babović
AU - Petrović, Sunčica
AU - Baranger, Aurélie
AU - Williams, Alria
AU - Alcorn, Alyssa M.
AU - Pellicano, Elizabeth
N1 - Publisher Copyright:
© 2021 held by the owner/author(s).
PY - 2021/10
Y1 - 2021/10
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 - Predictability
KW - autism spectrum condition
KW - engagement
KW - human-robot interaction
KW - individual differences
KW - variability
UR - http://www.scopus.com/inward/record.url?scp=85114473764&partnerID=8YFLogxK
U2 - 10.1145/3468849
DO - 10.1145/3468849
M3 - Article
AN - SCOPUS:85114473764
SN - 1073-0516
VL - 28
JO - ACM Transactions on Computer-Human Interaction
JF - ACM Transactions on Computer-Human Interaction
IS - 5
M1 - 3468849
ER -