Literature DB >> 33501122

Educators' Views on Using Humanoid Robots With Autistic Learners in Special Education Settings in England.

Alyssa M Alcorn1, Eloise Ainger1, Vicky Charisi2, Stefania Mantinioti1, Sunčica Petrović3, Bob R Schadenberg4, Teresa Tavassoli5, Elizabeth Pellicano1,6.   

Abstract

Researchers, industry, and practitioners are increasingly interested in the potential of social robots in education for learners on the autism spectrum. In this study, we conducted semi-structured interviews and focus groups with educators in England to gain their perspectives on the potential use of humanoid robots with autistic pupils, eliciting ideas, and specific examples of potential use. Understanding educator views is essential, because they are key decision-makers for the adoption of robots and would directly facilitate future use with pupils. Educators were provided with several example images (e.g., NAO, KASPAR, Milo), but did not directly interact with robots or receive information on current technical capabilities. The goal was for educators to respond to the general concept of humanoid robots as an educational tool, rather than to focus on the existing uses or behaviour of a particular robot. Thirty-one autism education staff participated, representing a range of special education settings and age groups as well as multiple professional roles (e.g., teachers, teaching assistants, speech, and language therapists). Thematic analysis of the interview transcripts identified four themes: Engagingness of robots, Predictability and consistency, Roles of robots in autism education, and Need for children to interact with people, not robots. Although almost all interviewees were receptive toward using humanoid robots in the classroom, they were not uncritically approving. Rather, they perceived future robot use as likely posing a series of complex cost-benefit trade-offs over time. For example, they felt that a highly motivating, predictable social robot might increase children's readiness to learn in the classroom, but it could also prevent children from engaging fully with other people or activities. Educator views also assumed that skills learned with a robot would generalise, and that robots' predictability is beneficial for autistic children-claims that need further supporting evidence. These interview results offer many points of guidance to the HRI research community about how humanoid robots could meet the specific needs of autistic learners, as well as identifying issues that will need to be resolved for robots to be both acceptable and successfully deployed in special education contexts.
Copyright © 2019 Alcorn, Ainger, Charisi, Mantinioti, Petrović, Schadenberg, Tavassoli and Pellicano.

Entities:  

Keywords:  autism; children; education; humanoid robots; schools; social robots; special education; teachers

Year:  2019        PMID: 33501122      PMCID: PMC7805648          DOI: 10.3389/frobt.2019.00107

Source DB:  PubMed          Journal:  Front Robot AI        ISSN: 2296-9144


  23 in total

1.  The Clinical Use of Robots for Individuals with Autism Spectrum Disorders: A Critical Review.

Authors:  Joshua J Diehl; Lauren M Schmitt; Michael Villano; Charles R Crowell
Journal:  Res Autism Spectr Disord       Date:  2012-01

2.  Can Robotic Interaction Improve Joint Attention Skills?

Authors:  Zachary E Warren; Zhi Zheng; Amy R Swanson; Esubalew Bekele; Lian Zhang; Julie A Crittendon; Amy F Weitlauf; Nilanjan Sarkar
Journal:  J Autism Dev Disord       Date:  2015-11

3.  Understanding 'anticipatory governance'.

Authors:  David H Guston
Journal:  Soc Stud Sci       Date:  2014-04       Impact factor: 3.885

4.  A Survey of Expectations About the Role of Robots in Robot-Assisted Therapy for Children with ASD: Ethical Acceptability, Trust, Sociability, Appearance, and Attachment.

Authors:  Mark Coeckelbergh; Cristina Pop; Ramona Simut; Andreea Peca; Sebastian Pintea; Daniel David; Bram Vanderborght
Journal:  Sci Eng Ethics       Date:  2015-04-17       Impact factor: 3.525

Review 5.  Designing Serious Game Interventions for Individuals with Autism.

Authors:  Elisabeth M Whyte; Joshua M Smyth; K Suzanne Scherf
Journal:  J Autism Dev Disord       Date:  2015-12

6.  When the world becomes 'too real': a Bayesian explanation of autistic perception.

Authors:  Elizabeth Pellicano; David Burr
Journal:  Trends Cogn Sci       Date:  2012-09-07       Impact factor: 20.229

Review 7.  Robots for use in autism research.

Authors:  Brian Scassellati; Henny Admoni; Maja Matarić
Journal:  Annu Rev Biomed Eng       Date:  2012-05-09       Impact factor: 9.590

8.  Naturalistic Developmental Behavioral Interventions: Empirically Validated Treatments for Autism Spectrum Disorder.

Authors:  Laura Schreibman; Geraldine Dawson; Aubyn C Stahmer; Rebecca Landa; Sally J Rogers; Gail G McGee; Connie Kasari; Brooke Ingersoll; Ann P Kaiser; Yvonne Bruinsma; Erin McNerney; Amy Wetherby; Alycia Halladay
Journal:  J Autism Dev Disord       Date:  2015-08

9.  An aberrant precision account of autism.

Authors:  Rebecca P Lawson; Geraint Rees; Karl J Friston
Journal:  Front Hum Neurosci       Date:  2014-05-14       Impact factor: 3.169

10.  Making the future together: Shaping autism research through meaningful participation.

Authors:  Sue Fletcher-Watson; Jon Adams; Kabie Brook; Tony Charman; Laura Crane; James Cusack; Susan Leekam; Damian Milton; Jeremy R Parr; Elizabeth Pellicano
Journal:  Autism       Date:  2018-08-10
View more
  4 in total

Review 1.  Artificial Intelligence Enabled Personalised Assistive Tools to Enhance Education of Children with Neurodevelopmental Disorders-A Review.

Authors:  Prabal Datta Barua; Jahmunah Vicnesh; Raj Gururajan; Shu Lih Oh; Elizabeth Palmer; Muhammad Mokhzaini Azizan; Nahrizul Adib Kadri; U Rajendra Acharya
Journal:  Int J Environ Res Public Health       Date:  2022-01-21       Impact factor: 3.390

2.  IoT and AI-Based Application for Automatic Interpretation of the Affective State of Children Diagnosed with Autism.

Authors:  Aura-Loredana Popescu; Nirvana Popescu; Ciprian Dobre; Elena-Simona Apostol; Decebal Popescu
Journal:  Sensors (Basel)       Date:  2022-03-25       Impact factor: 3.576

3.  Socially-Assistive Robots to Support Learning in Students on the Autism Spectrum: Investigating Educator Perspectives and a Pilot Trial of a Mobile Platform to Remove Barriers to Implementation.

Authors:  David Silvera-Tawil; Susan Bruck; Yi Xiao; DanaKai Bradford
Journal:  Sensors (Basel)       Date:  2022-08-16       Impact factor: 3.847

4.  The use of social robots with children and young people on the autism spectrum: A systematic review and meta-analysis.

Authors:  Athanasia Kouroupa; Keith R Laws; Karen Irvine; Silvana E Mengoni; Alister Baird; Shivani Sharma
Journal:  PLoS One       Date:  2022-06-22       Impact factor: 3.752

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.