Robots and autistic children: a review

In accordance with the advancement in robotics and the scholarly literature, the extents of utilizing robots for autistic children are widened and could be a promising method for individual with Autism Spectrum Disorder (ASD) treatments, where the different form of robot (humanoid, non-humanoid, animal-like, toy, and kits) can be employed effectively as a support tool to augment the learning skills and rehabilitate of the individual with Autism Spectrum Disorder (ASD). Thus, the robots were exploited for ASD children in different aspects namely; modelling, teaching, and skills practicing; testing, highlighting and evaluating; providing feedback or encouragement; join Attention; eliciting social behaviours; emotion recognition and expression; imitation; vocalization; turn-taking; and diagnostic. The related literature published recently in journals and conferences is taken into account. In this paper, we review the use of robots that help in the therapy of individuals with Autism Spectrum Disorder (ASD). The articles on using robots for autistic children rehabilitation and education which reported results of experiments on a number of participants were implicated. After looking in digital libraries under this criteria, and excluding non-related, and duplicated studies, 39 studies have been found. The findings were focused mainly on the social communication skills of autistic children and how the extent of the robots mitigate their stereotyped behaviours. Deeper research is required in this area to cover all applications of robotic on autistic children in order to design feasible and low-cost robots that ensure provide high validity

Robots in special education: reasons for low uptake

Purpose: This paper identifies the main reasons for low uptake of robots in Special Education, obtained from an analysis of previous studies that used robots in the area, and from interviewing Special Education teachers about the topic. Design/methodology/approach: An analysis of 18 studies that used robots in Special Education was performed, and the conclusions were complemented and compared with the feedback from interviewing 13 Special Education teachers from Spain and UK about the reasons they believed caused the low uptake of robots in Special Education classrooms. Findings: Five main reasons why Special Education schools do not normally use robots in their classrooms were identified: the inability to acquire the system due to its price or availability; its difficulty of use; the low range of activities offered; the limited ways of interaction offered; and the inability to use different robots with the same software. Originality/value: Previous studies focused on exploring the advantages of using robots to help children with Autistic Spectrum Conditions and Learning Disabilities. This study takes a step further and looks into the reasons why, despite the benefits shown, robots are rarely used in real-life settings after the relevant study ends. The authors also present a potential solution to the issues found: involving end users in the design and development of new systems using a user-centred design approach for all the components, including methods of interaction, learning activities, and the most suitable type of robots

An Adaptive Teachable Robot For Encouraging Teamwork

Social robots used in education can take different roles, including tutor robots and peer robots. Peer robots (also called teachable robots) take the role of a novice in a teaching interaction while the students take the role of the teacher. Teachable robots leverage learning by teaching, which has been shown in prior research to increase the students’ learning effort and time spent on the learning activity, leading to enhanced student learning. The concept of teachable robots has previously been applied for one-to-one interaction, however, to date, few studies use teachable robots in a group setting. In this thesis, we developed an adaptive learning algorithm for a teachable robot that encourages a group of students to discuss their thoughts and teaching decisions during the tutoring session. We hypothesize that the robot's encouragement of group discussion can enhance the social engagement of group members, leading to improved task engagement, learning and enjoyment. The robot adapts to the students' talking activity and adjusts the frequency and type of encouragement. The robot uses reinforcement learning to maximise interaction between the students. The proposed approach was validated through a series of studies. The first pilot study was performed in an elementary school and observed the interactions between groups of students and teachable robots. The main study investigated the feasibility of an adaptive encouraging robot in a remote setting. We recruited 68 adults, who worked together in pairs online on a web application called Curiosity Notebook to teach a humanoid robot about the classification of rocks and minerals. We measured social engagement based on the communication between group-mates, while the metric for task engagement was generated based on the users’ activities in the Curiosity Notebook. The results show that the adaptive robot was successful in creating more dialogue between group members and in increasing task engagement, but did not affect learning or enjoyment. Over time, the adaptive robot was also able to encourage both members to contribute more equally to the conversation