Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Engaging students with profound and multiple disabilities using humanoid robots

Standen, Penny, Brown, David, Roscoe, Jess, Hedgecock, Joseph, Stewart, David, Galvez Trigo, Maria Jose ORCID: and Elgajiji, Elmunir 2014. Engaging students with profound and multiple disabilities using humanoid robots. Presented at: 8th International Conference, UAHCI 2014, Held as Part of HCI International 2014, Heraklion, Greece, 22-27 June 2014. Universal Access in Human-Computer Interaction: Universal Access to Information and Knowledge. Lecture Notes in Computer Science , vol.8514 Springer, 10.1007/978-3-319-07440-5_39

[thumbnail of Engaging Students with Profound and Multiple Disabilities using Humanoid Robots AAM.pdf]
PDF - Accepted Post-Print Version
Available under License Creative Commons Attribution.

Download (262kB) | Preview


Engagement is the single best predictor of successful learning for children with intellectual disabilities yet achieving engagement with pupils who have profound or multiple disabilities (PMD) presents a challenge to educators. Robots have been used to engage children with autism but are they effective with pupils whose disabilities limit their ability to control other technology? Learning objectives were identified for eleven pupils with PMD and a humanoid robot was programmed to enable teachers to use it to help pupils achieve these objectives. These changes were evaluated with a series of eleven case studies where teacher-pupil dyads were observed during four planned video recorded sessions. Engagement was rated in a classroom setting and during the last session with the robot. Video recordings were analysed for duration of engagement and teacher assistance and number of goals achieved. Rated engagement was significantly higher with the robot than in the classroom. Observations of engagement, assistance and goal achievement remained at the same level throughout the sessions suggesting no reduction in the novelty factor.

Item Type: Conference or Workshop Item (Paper)
Status: Published
Schools: Computer Science & Informatics
Publisher: Springer
ISBN: 978-3-319-07440-5
Date of First Compliant Deposit: 11 April 2023
Date of Acceptance: 1 January 2014
Last Modified: 12 Apr 2023 11:00

Citation Data

Cited 18 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item


Downloads per month over past year

View more statistics