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Predictable Robots for Autistic Children—Variance in Robot Behaviour, Idiosyncrasies in Autistic Children’s Characteristics, and Child–Robot Engagement

Schadenberg, Bob R.; Reidsma, Dennis; Evers, Vanessa; Davison, Daniel P.; Li, Jamy J.; Heylen, Dirk K. J.; Neves, Carlos; Alvito, Paulo; Shen, Jie; Pantić, Maja; Schuller, Björn W.; Cummins, Nicholas; Olaru, Vlad; Sminchisescu, Cristian; Dimitrijević, Snežana Babović; Petrović, Sunčica; Baranger, Aurélie; Williams, Alria; Alcorn, Alyssa M.; Pellicano, Elizabeth

Authors

Bob R. Schadenberg

Dennis Reidsma

Vanessa Evers

Daniel P. Davison

Dirk K. J. Heylen

Carlos Neves

Paulo Alvito

Jie Shen

Maja Pantić

Björn W. Schuller

Nicholas Cummins

Vlad Olaru

Cristian Sminchisescu

Snežana Babović Dimitrijević

Sunčica Petrović

Aurélie Baranger

Alria Williams

Alyssa M. Alcorn

Elizabeth Pellicano



Abstract

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.

Citation

Schadenberg, B. R., Reidsma, D., Evers, V., Davison, D. P., Li, J. J., Heylen, D. K. J., Neves, C., Alvito, P., Shen, J., Pantić, M., Schuller, B. W., Cummins, N., Olaru, V., Sminchisescu, C., Dimitrijević, S. B., Petrović, S., Baranger, A., Williams, A., Alcorn, A. M., & Pellicano, E. (2021). Predictable Robots for Autistic Children—Variance in Robot Behaviour, Idiosyncrasies in Autistic Children’s Characteristics, and Child–Robot Engagement. ACM transactions on computer-human interaction, 28(5), 1-42. https://doi.org/10.1145/3468849

Journal Article Type Article
Acceptance Date May 1, 2021
Online Publication Date Aug 20, 2021
Publication Date 2021-10
Deposit Date Mar 20, 2025
Publicly Available Date Mar 24, 2025
Journal ACM Transactions on Computer-Human Interaction (TOCHI)
Print ISSN 1073-0516
Electronic ISSN 1557-7325
Publisher Association for Computing Machinery (ACM)
Peer Reviewed Peer Reviewed
Volume 28
Issue 5
Article Number 36
Pages 1-42
DOI https://doi.org/10.1145/3468849
Keywords Predictability, variability, autism spectrum condition, human-robot interaction, engagement, individual differences
Public URL http://researchrepository.napier.ac.uk/Output/4181203

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