Supporting the Education of Children with Autism Spectrum Disorders

Yefim Kats Chestnut Hill College, USA

A volume in the Advances in Early Childhood and K-12 Education (AECKE) Book Series Published in the United States of America by IGI Global Information Science Reference (an imprint of IGI Global) 701 E. Chocolate Avenue Hershey PA, USA 17033 Tel: 717-533-8845 Fax: 717-533-8661 E-mail: [email protected] Web site: http://www.igi-global.com

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Names: Kats, Yefim, editor. Title: Supporting the education of children with autism spectrum disorders / Yefim Kats, editor. Description: Hershey PA : Information Science Reference, 2016. | Series: Advances in early childhood and K-12 education | Includes bibliographical references and index. Identifiers: LCCN 2016023699| ISBN 9781522508168 (hardcover) | ISBN 9781522508175 (ebook) Subjects: LCSH: Autistic children--Education--United States. | Autistic youth--Education--United States. | Learning disabled children--Education--United States. | Learning disabled youth--Education--United States. Classification: LCC LC4718 .S86 2016 | DDC 371.94--dc23 LC record available at https://lccn.loc.gov/2016023699

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Chapter 12 Social Stories in Robot-Assisted Therapy for Children with ASD

David Silvera-Tawil University of New South Wales, Australia

Iva Strnadová University of New South Wales, Australia

Therese M Cumming University of New South Wales, Australia

ABSTRACT Mobile technology devices are commonly used as assistive technology to support children with Autism Spectrum Disorder (ASD) in gaining skills in interpersonal communication. While considered generally safe and effective, there are concerns that a child that is taught to communicate through interactive technologies may become dependent on the virtual world and its rewards, while interpersonal skills are sacrificed or not generalized to real world settings (Bauminger-Zviely, Eden, Zancanaro, Weiss, & Gal, 2013). This chapter theorizes that the anthropomorphic embodiment of humanoid robots may provide a compromise between the real and the virtual worlds. The authors suggest that a humanoid robot can use social stories within an Applied Behavioral Analysis (ABA) framework to support the acquisition of social interaction skills of children with ASD. The objective of this chapter is to contribute to the current literature by providing a description of this intervention and make suggestions for its implementation using a case study approach.

INTRODUCTION

Children with autism spectrum disorder (ASD) tend to prefer non-social stimuli to social stimuli (Heflin & Alaimo, 2007). For over a decade, mainstream technologies (e.g., computers and tablets) have been used as assistive devices to facilitate interpersonal communication for this population (Bauminger-Zviely et al., 2013; Chen, 2012; DiGennaro Reed, Hyman & Hirst, 2011; Gay, Leijdekkers, Agcanas, Wong, & Wu, 2013; Grynszpan, Weiss, Perez-Diaz & Gal, 2014; Irish, 2013; Lee et al., 2013); including apps,

DOI: 10.4018/978-1-5225-0816-8.ch012

Copyright © 2017, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. Social Stories in Robot-Assisted Therapy for Children with ASD

computer games and virtual reality devices aimed to improve social engagement (Bauminger-Zviely et al., 2013) and emotion recognition (Beaumont & Sofronoff, 2008; Golan & Baron-Cohen, 2006), encourage positive interactions (Hourcade, Williams, Miller, Huebner & Liang, 2013), and enhance language development (Ploog, Scharf, Nelson & Brooks, 2013) and adaptive independence (Bian et al., 2013). These technologies offer safe, realistic-looking three-dimensional scenarios that can be built to depict everyday social scenarios, providing an environment that allows for self-paced learning and immediate feedback, while minimizing the need for ‘real world’ social interactions during the learning process (Golan & Baron-Cohen, 2006; Strnadová, Cumming & Draper Rodriguez, 2014), a common source of anxiety for many people with ASD. Although these technologies appear to be effective, significant concerns include: (1) the child becoming dependent on the virtual world while interpersonal skills are sacrificed, and (2) significant restrictions in elements of face-to-face communication (eye gaze, body movement). The large gap between the safe and structured environment of computer-based interventions and real world social behavior results in poor transfer of skills to real world interactions (Bauminger-Zviely et al., 2013). Although virtual reality systems have the potential to provide higher degrees of control and interactivity between the user and the computer, the need to wear special technology that interferes with the individual’s natural behavior is an additional concern. The aim of this chapter is to introduce a vision and plan of a new intervention approach aimed to contribute to the evidence base of using different forms of technology to enhance the social communication abilities of children with autism. This approach uses a humanoid robot and Social StoriesTM (Gray, 2000) within the Applied Behavioral Analysis (ABA) approach to teach social communication skills.

LITERATURE REVIEW

Autism spectrum disorder (ASD) is a lifelong developmental disability that affects the way a person communicates and relates to other people. It is generally characterized by impairments in social communication, social interaction, and social imagination, along with patterns of repetitive behavior. The degree of the impairments related to ASD varies significantly across a spectrum, ranging from severe to near-typical social functioning. Relevant evidence-based practices and research-based therapies seek to improve the individual’s social and communication skills while, at the same time, promoting their engagement in interpersonal interactions. Although there is no cure for autism, early intervention programs are particularly beneficial and can lead to long-term gains in cognitive, social, emotional, and motor functioning (Bennett, 2012; Feil-Seifer & Matarić, 2008), providing considerable improvements to the individual’s quality of life and independence. A recent trend in robotics is the design and implementation of machines (robots) that provide assistance to humans through social interaction, rather than physical intervention. This field is known as socially assistive robotics (Feil-Seifer & Matarić, 2005). The use of robots as mediators, or assistive tools during therapy for children with Autism is one of the first applications of socially assistive robotics (SAR). This section will present a comprehensive review of research in SAR as tools for intervention for people with ASD. An introduction to Applied Behavioral Analysis (ABA), Social StoriesTM (Gray, 2000) and their potential for robot-assisted therapy is included.

226 Social Stories in Robot-Assisted Therapy for Children with ASD

Socially-Assistive Robots in Robot-Assisted Therapy for ASD

Play is an important element in the development of language skills, cognitive skills, and opportunities for social interaction (Pierucci, Barber, Gilpin, Crisler, & Klinger, 2015). Pierucci et al. (2015) rec- ommend that if a child does not typically engage in social reciprocal play, the intervention should be planned around his current level of performance and use object play to support the child in achieving social communication goals. For some time now it has been well known that children with ASD enjoy playing with computers and mechanical devices (Moore, 1998). Over the last decade, researchers have explored the use of robots as tools to supplement traditional therapy (Scassellati, Admoni & Matarić, 2012; Senland, 2014). These robots are often presented as ‘toys’ (Robins & Dautenhahn, 2014). These toys (robots) are novel, animated, are (or appear) autonomous, and set themselves apart from traditional toys, thereby further maintaining children’s interest (Scassellati, et al., 2012). Furthermore, the three-dimensional embodiment of robots provides a compromise between the virtual world—available through digital technologies—and the real world, by promoting a full body experience on the part of the child. A robot can provide complex behavior patterns, such as those available in human-to-human interactions, while appearing less intimidating and more predictable than humans (Michaud & Théberge-Turmel, 2002). Unlike digital technology, communication skills that are learned using robots have greater potential to be transferable to interpersonal communication (Giullian, et al., 2010; Jeon & Rayan, 2011). Studies in robot-assisted therapy (RAT) have demonstrated the potential of socially interactive robots in ASD therapy, showing high interest and positive engagement from children towards robots (Cabibihan, Javed, Ang & Aljunied, 2013; Feil-Seifer & Matarić, 2009; Kim, Paul, Shic & Scassellati, 2012; Kozima, Michalowski & Nakagawa, 2009; Michaud & Théberge-Turmel, 2002; Robins, Dautenhahn, Boekhorst & Billard, 2005). Others have demonstrated that children with autism interact more with robots than they do with computers, or even with other humans (Kim, et al., 2013). Some of these studies demonstrated that children interact more with other humans while engaged with a robot (Feil-Seifer & Matarić, 2009; Kozima, et al., 2009; Robins, et al., 2005). The main goal of socially-assistive robots for intervention in ASD, to date, has been the development of social and communication skills in children with this condition. Autonomous and remotely-operated robots have shown that RAT can promote, among other skills, imitative free-form play (Robins et al., 2005), facial expression recognition (Vanderborght, et al., 2012), joint attention (Aggarwal, Sehrawat & Charaya, 2013; Warren, et al., 2013), and turn taking (Robins & Dautenhahn, 2010). It also has the potential to foster triadic interactions (Robins, et al., 2005) and encourage associative, cooperative and social play (Wainer, Dautenhahn, Robins & Amirabdollahian, 2013; Wainer, Ferrari, Dautenhahn & Robins, 2010). After RAT intervention, children have demonstrated increased levels of eye contact during extended periods of time (Feng, Gutierrez, Zhang & Mahoor, 2013), improved performance in their social communication skill (Warren et al., 2013) and improvements in their imitation skill (Fujimoto, Matsumoto, Silva, Kobayashi & Higashi, 2011). For many individuals with ASD, tactile interaction presents difficulties that impede their ability to interact. For others, however, it is an important way of communication. It has been suggested that problems with verbal skills and eye gaze in individuals with autism spectrum disorder creates the need for touch to replace these sensing modalities (Caldwell, 1996). Even in the early stages of the development, tactile interaction in RAT has already shown to play an important role in providing physical and mental

227 Social Stories in Robot-Assisted Therapy for Children with ASD

improvements to children and adults (Robins, Dautenhahn & Dickerson, 2012; Shibata, Kawaguchi & Wada, 2012). The benefits of RAT have been demonstrated in short-term case studies with three to five children each, with very few demonstrations over large samples (Diehl, Schmitt, Villano & Crowell, 2012; Kim et al., 2013). Generalization and transfer of learned skills to real world situations remains to be seen. It is important to note, however, that although similarities exist in the way children with ASD respond to robots, not all children react exactly the same way. What works for some children might not work for others and the ability of the robot to adapt to the children’s needs is highly beneficial. For this reason, existing robotic systems are primarily remotely operated and are unable to perform autonomously.

Robot Appearance

The appearance of a robot is fundamental during the initial interaction, and has significant influence on its effectiveness throughout the therapy. Appropriate form factor, appearance, and behavior are likely to both engage a child and to improve social interactions. Based on their appearance, robots designed for ASD therapy can be divided into three main categories: anthropomorphic, zoomorphic and non- biomimetic robots (Figure 1). Anthropomorphic robots are those designed with a human-like resemblance, such as a head, eyes, torso, arms or legs. These include robots with highly realistic human-like facial features (Adams & Robinson, 2011), child-sized humanoid robots with simple stylized or cartoon-like features (Robins, et al., 2005; Costa, Soares & Santos, 2013), and simplified robots with non-anthropomorphic bodies but attributes (e.g., face, eyes or mouth) that provide some resemblance to human-like entities (Kozima, et al., 2009). Although these, and many other different robot shapes have been tested (Scassellati, et al., 2012), humanoid shapes seem to offer the most promise (Giullian, et al., 2010). Cabibihan, et al. (2013) suggest that to enhance simplicity and set robots apart from humans, complex facial expressions, alongside features such as eyebrows and eyelashes should be avoided. Zoomorphic robots, on the other hand, are non-threatening animal-like robots that allow for the expression of limited social cues that are appropriate to their physical form. The interactive behaviors of these robots are often simpler to those available in anthropomorphic robots. Zoomorphic robots, such as Probo (Van de Perre, Simut, Vanderborght, Saldien & Lefeber, 2012; Simut, Vanderfaeillie, Peca, Van de Perre & Vanderborght, 2015) and Pleo (Kim, et al., 2012), have been effective used during free-play and as mediators during therapy. Finally, non-biomimetic robots are robots designed without considering their resemblance to any biological species or typical socially interactive behaviors. Like zoomorphic robots, non-biomimetic robots are commonly used to engage children in free-play (Michaud & Théberge-Turmel, 2002), or as social mediators or catalysts for interaction with adults or children (Feil-Seifer & Matarić, 2009). A summary of some of the socially-assistive robots used in interventions for people with ASD is presented in Table 1.

Applied Behaviour Analysis

Applied Behavior Analysis (ABA) is an evidence-based, intensive education therapy that has been shown to be highly effective in educating children and youth with disabilities, particularly those with autism spectrum disorders (Kearney, 2007). ABA relies on the collection of behavioral and/or academic data, examining the interaction between antecedent variables and consequences, and using this information to

228 Social Stories in Robot-Assisted Therapy for Children with ASD

Table 1. Socially-assistive robots used in interventions for people with ASD

Name Appearance Targeted Behavior C-Pac (Michaud & Théberge-Turmel, 2002) Anthropomorphic Free-play and engagement CHARLIE (Boccanfuso & O’Kane, 2010, 2011) Anthropomorphic Imitative play Darwin-OP (Cheng, Wang & Mayer, 2013) Anthropomorphic Spontaneous, imaginary, and symbolic play FACE (Adams & Robinson, 2011) Anthropomorphic Imitative play and facial expression recognition iRobi (Yun, Park & Choi, 2014) Anthropomorphic Social skill training Isobot (Sudha Srinivasan, 2013) Anthropomorphic Joint attention and verbalization KASPAR (Robins & Dautenhahn, 2010, 2014; Robins et Anthropomorphic Triadic interaction, tactile interaction, turn taking, al., 2005; Wainer et al., 2013, 2010) imitative, associative, cooperative and social play Kepoon (Kozima et al., 2009) Anthropomorphic Engagement and triadic interaction NAO (Bekele, Crittendon, Swanson, Sarkar & Warren, Anthropomorphic Eye gaze, joint attention and establishing 2013; Feng et al., 2013; Shamsuddin et al., 2012; Warren relationship et al., 2013; Zhao et al., 2013) Robota (Billard et al., 2007; Robins, 2005) Anthropomorphic Imitation and coordination Rofina (Wong et al., 2012) Anthropomorphic Free play and interaction Tito (Duquette, Michaud & Mercier, 2008) Anthropomorphic Shared attention Troy (Giullian et al., 2010) Anthropomorphic Generalization of social skill training ZECA (Costa et al., 2013) Anthropomorphic Facial expression recognition Zeno (Ranatunga et al., 2012) Anthropomorphic Social skill training Jumbo (Michaud & Théberge-Turmel, 2002) Zoomorphic Free-play and engagement PABI (Dickstein-Fischer et al., 2011) Zoomorphic Social skill training Pleo (Jeon & Rayan, 2011; Kim et al., 2012) Zoomorphic Free-play and verbal participation Probo (Van de Perre et al., 2012; Vanderborght et al., Zoomorphic Facial expression recognition, social skill training 2012; Simut et al, 2015) Bubble-blowing robot (Feil-Seifer & Matarić, 2008, Non-biomimetic Social interaction 2009) Muu (Goan, Fujii & Okada, 2006) Non-biomimetic Engagement and verbal communication TOUCH PAD (Lee et al., 2012) Non-biomimetic Interpersonal touch Roball (Michaud & Théberge-Turmel, 2002) Non-biomimetic Free-play and engagement

systematically plan desired learning and behavior change programs (Alberto & Troutman, 2009). ABA is a personalized program designed to meet the individual requirements of each child to help support the development of their social, academic and behavioral skills. It is dependent upon strengthening and maintaining desired behaviors through the application of positive reinforcement and modeling (Kerr & Nelson, 2010). ABA has its roots in behaviorism, and as such is dependent upon data collection. A functional behavioral assessment (FBA) is the first step in this process. The FBA consists of observations, interviews with the child and those closest to him/her (parents/carers, teachers), checklists and tests. The purpose of the FBA is to determine the “why” or the function of the behavior. The results of the assessment are used to identify target behaviors to change and strategies and resources that can be used in the design of the intervention plan (Alberto & Troutman, 2009). Both the FBA and the behavior plan are highly

229 Social Stories in Robot-Assisted Therapy for Children with ASD

Figure 1. Anthropomorphic robots KASPAR (© 2015, University of Hertfordshire, U.K. Used with permission.) and NAO (Aldebaran Robotics); zoomorphic robot Probo (© 2015, VUB-Robotics Research Group. Used with permission.) and non-biomimetic robot Muu (© 2015, M. Okada, Toyohashi University of Technology. Used with permission.)

individualized, as problem behavior serves different functions for different children. The behavior plan is designed to reduce problem behaviors and increase appropriate replacement behaviors for the specific child it was created for. Strategies included in the behavior plan should be evidence-based (O’Neill, Albin, Storey, Horner & Sprague, 2015). Social skills training programs, such as social narratives and Social StoriesTM are often included in the behavior plans of children who exhibit deficits in social understanding and communication (Reynhout & Carter, 2007). An important component of the implementation any ABA strategy is reinforcement. Positive reinforcement of the child for correct responses will strengthen the desired response, and has been shown to be effective when paired with several ABA-based strategies, including discrete trial training, incidental teaching, and pivotal response training (Hall, 2009). Discrete trial training is an adult initiated contingency strategy that used has been used to teach communication, language, and many other skills to children with autism (Lovaas, 2003). Incidental teaching focuses on child-initiated interactions to increase language skills (Hall, 2009). This strategy uses carefully planned environmental cues to elicit initiation from the child, such as putting a preferred item out of reach, then using access to the item to reinforce the child for performing a specific skill. Pivotal response training is a child-initiated teaching interaction with choice making and turn taking embedded. Important elements of this strategy on the part of the child include motivation and responsivity to multiple cues. The adult’s focus is on: (a) following

230 Social Stories in Robot-Assisted Therapy for Children with ASD

the child’s lead, (b) giving the child choices, (c) reinforcing attempts as well as successes, (d) providing natural consequences, and (e) mixing maintenance tasks in with new tasks. Researchers have suggested that integrating robots into these and other ABA teaching strategies may increase their effectiveness (Diehl, et al., 2012; Tang, et al., 2011). In this vein, Barakova and Lourens (2013), Gillesen et al. (2011) and Yun et al. (2014) used an ABA-based approach to create individualized treatments that could enhance the learning capabilities of children. Yun et al. (2014) used a discrete trial teaching (DTT) protocol with three task modes of therapy, encouragement, and pause to improve the children’s social capabilities, while Barakova and Lourens (2013) and Gillesen, Barakova, Huskens and Feijs (2011) used a pivotal response treatment (PRT) approach and tailored interactive scenarios to promote self initiated social behaviors, language and communication, problem solving and appropriate social responses.

Social StoriesTM

For over a decade, Social StoriesTM have been successfully used during intervention programs to teach children with autism spectrum disorders appropriate social skills and behaviors across various situations and environments (Barry & Burlew, 2004; Gray, 1991, 1992; Reynhout & Carter, 2007; Swaggart et al., 1995). Social StoriesTM can be defined as social learning tools that describe appropriate behaviors in a given social situation (Gearin, Kaan, Shallita & Lau, 2011). They are tailored for each person, explain- ing the ‘who’, ‘what’, ‘where’, ‘when’ and ‘why’ of a given social situation. An ultimate goal of Social StoriesTM is to improve understanding of a social situation (Hall, 2009). There are four types of sentences used when creating a Social StoriesTM narrative: descriptive sentences, directive statements, affirmative sentences, and partial sentences (Hall, 2009). Suggested elements for the development of effective Social StoriesTM include: (a) age-appropriate vocabulary, (b) use of present tense, (c) story written from the individual’s perspective, and (d) use of and adherence to a recommended ratio of directive and perspective sentences (Gray, 2000). Social StoriesTM typically comprise short text, and are sometimes accompanied by illustrations. The use of illustrations depends on the age, level of disability and learning preferences of the person with ASD that the story is being developed for. Social StoriesTM can be written by different stakeholders, such as parents/carers, teachers, and therapists. They can be used to teach appropriate behaviors, social skills, routines and curriculum, as well as to increase independence. They are commonly used in combination with other evidence-based practices, such as reinforcement, prompting, priming and corrective feedback (Reynhout & Carter, 2007). It is important to introduce a social story in a setting that is comfortable for the person with ASD, and to read it often, especially prior to a situation in which the targeted skill can be practiced. Social StoriesTM are usually read by human therapists. Recent research, however, argues that the social performance of children with ASD can be improved when a robot is used as a storyteller instead of a human (Gillesen, et al., 2011; Vanderborght et al., 2012). Gillesen et al. (2011) suggest that replacing a real person with a robot can be preferable for a child with ASD, as it is more consistent and predictable. Simut, et al. (2012) used the robot Probo when using the Social StoriesTM intervention to address social skills deficits of four preschool-aged children with ASD. The social skills included sharing toys, saying hello, and saying thank you. The results of this study demonstrated that the social story told by the robot led to less prompting from the therapist in order for the children to perform the appropriate social response.

231 Social Stories in Robot-Assisted Therapy for Children with ASD

INTEGRATING ROBOTS INTO ABA-BASED SOCIAL STORY INSTRUCTION

The intervention approach proposed by the authors in this book chapter is structured as a cause-and-effect game. A set of scenarios representing “real-life” situations based on Gray’s Social Story construction guidelines (Gray, 2000) are designed based on the individual needs of the child. The intervention consists of Social StoriesTM told by a humanoid robot. The stories, as well as the robot behaviors, will be personalized based on ability, targeted social skill, gender and age of each child. When applying this intervention approach, it is essential to gain in-depth understanding of a child’s current social and communication skills (e.g., vocabulary), as well as his/her strengths and what motivates him/her. Parents/carers in discussion with professionals (teachers, therapists, etc.) decide on a goal for their child. This goal can be to learn how to share toys, express wants and needs, or saying thank you. Following this, the text of a social story is developed, respecting child’s strengths, interests, learning preferences and needs (Hall, 2009). It is important to make sure that description of the given social situation is accurate and written in a positive language. The authors propose that a humanoid robot acts as a storyteller, telling a child with ASD a social story, using relevant images and movements, with a professional (a parent, therapist, teacher, researcher, etc.) present to encourage and assist the child in any way needed. By using a humanoid robot as a storyteller as well as a participant in the story, a connection between the text, illustrations and the robot will be created, giving a child the opportunity to learn through repetition immediately after the story is told. It is important that a child is provided with an opportunity soon after the story being told to practice the social skill in question repeatedly. Proficiency is achieved when a child’s response is considered “comfortable” by the robot. The child’s behavior will be evaluated by a researcher, but communicated by the remote-controlled robot. The authors propose that the robot’s speech, movement, sound (music) and lights will be used for positive reinforcement and reward. Different levels of reinforcement/reward will be used in a progressive manner. Negative feedback due to inappropriate behaviors will be avoided and replaced with neutral robot responses (e.g. “Please try again”). The case study below demonstrates a possible future application of this approach. To improve generalization and transfer of skills, after completing the social story, the same robot with different appearance (e.g., different outfit and/or hair color/wig) would repeat the same social story.

Case Study

Michael is a 4-year-old boy with autism spectrum disorder. He lives with his parent and an older sister. Michael was diagnosed with ASD when he was 2 years old, after his parents observed significant speech and language delays, as well as difficulties in developing interactive play skills. Michael avoids interaction with other children, and tends to be rather passive in social situations. He does not like to interact with other people than his parents and sister. He has difficulties to understand 3-step directions. Michael likes listening to music, especially to the song The Wheels on the Bus. He also enjoys watching light effects, such as changing colors of electric candles on a Christmas tree. Michael’s parents would like for their son to be able to greet a new person in a relevant social situation. Michael parents agreed to a therapy using Social StoriesTM told by a humanoid robot, supported by ABA approach. The humanoid robot selected for this therapy was KASPAR (Figure 1). The treatment session was determined to be five daily sessions lasting 45 minutes. A social story was developed (Table 2). During the first session KASPAR repeated the story (level 1) multiple times, until Michael responded

232 Social Stories in Robot-Assisted Therapy for Children with ASD

Table 2. How to greet a new person

Level Story Robot Behavior Michael’s Expected Behavior Level 1 There are many ways to greet someone new. Therapist introduces KASPAR. “Hello” or “hi” (smiles) Sometimes my parents or teachers introduce me to someone I don’t know. They may smile and say “hello”. I KASPAR: “Hello, my name is usually try to smile and say “hi” or “hello” back. KASPAR” (smiles) When I say “hi” or “hello” to someone, it makes them happy. People like to feel happy. Level 2 When someone smiles and says hello to me, I try to KASPAR: “Hello again, nice “Hello” (smiles, looks at respond. This is a very nice thing to do. to meet you” KASPAR’s face) Looking at the person who said hello when I respond is very helpful. That lets the person know that I’m talking to them. Usually people like it when I look at them while I greet them. Level 3 After you say hello, the person might ask you a question KASPAR: “I am KASPAR, My name is Michael (smiles, like, “What’s your name?” It is okay to answer the what is your name?” looks at KASPAR’s face) question. Sometimes, I might feel shy when saying hello to people. This is okay. My mom, dad, or teacher will stay with me to help me feel less sad. Level 4 Sometimes when I’m at school I meet a new child while KASPAR: “Hello, nice to meet “Hello” (smiles, looks at I’m playing in the playground. you” (smiles and waves hand) KASPAR’s face and waves They may smile and wave their hand at me. I usually try back) to look at them and wave back. Most people like it when I look and wave back at them.

correctly. When successfully completing level 1 on 3 out of 4 consecutive occasions, KASPAR congratu- lated Michael. For the first successful attempt, KASPAR would smile and say ‘well done!’, the second time KASPAR would smile, lift both arms and say ‘well done, you did it!’ and so on, until the fourth and last occasion when KASPAR would say ‘well done, you did it!’, play a celebratory musical tune (The Wheels on the Bus) and light up some colorful lights. After that, level 2 of the story was introduced, and the whole process was repeated again. Michael completed all four levels of the story by the end of day 3. On day four, KASPAR was dressed in a different outfit and had a different hair color (wig). This was surprising for Michael, who in turn struggled with the level 1 of the story told by KASPAR. It took several efforts before Michael completed level 1 without any prompts. Completing levels 2, 3 and 4 was achieved by the end of day 4. The last day of the intervention, KASPAR wore yet again a different outfit and a different wig. This time the change in KASPAR’s appearance did not influence Michael’s performance in the intervention. Following the five daily intervention with KASPAR, Michael had several opportunities to practice this new skill when meeting new people.

DISCUSSION

This book chapter presented the state-of-the-art in socially assistive-robots as tools for intervention for people with ASD. A new methodology based on applied behavior analysis was described. This meth-

233 Social Stories in Robot-Assisted Therapy for Children with ASD

odology aims to assist children with autism to improve their social communication skills by incorporating personalized Social StoriesTM into robot-assisted therapy. Although encouraging result suggest that robots can be used to improve various behaviors in children and adults with autism, significant research and is still required before they (robots) can be integrated effectively into evidence-based intervention and day-to-day child education. This section will present some of the challenges and directions in two main areas: (a) future development of assistive robots, and (b) how these robots can be integrated into intervention for people with ASD.

Future Development of Assistive Robots for Intervention for People with ASD

Achieving a step change in robotics capability requires advances in knowledge coupled with an appropriate technological realization. Most robot technology, to date, is only available to large institutions and research groups, limiting their use to short-term interventions with a limited number of children. More affordable, resilient and reliable robots would allow for a greater number of people to access this technology. These robots should be tough (durable), easy to clean and easy to maintain. 3-D printing technology has already shown to be effective in the development of affordable robots (Lapeyre et al., 2014), and will play a significant role in the development of more robots in the near future. As previously discussed, many different robots have been developed for intervention for people with ASD. These robots rely in their appearance and behavior to attract the children’s attention while, at the same time, engaging them in pro-social interactions. Although effective in short-term interactions, more research is needed to identify an appropriate balance between robot appearance/behavior and the therapeutic approach that would keep the children engaged, while providing a successful learning experience. A compromise between the use of robots together with music, lighting and/or a user interface developed using mainstream technology may be more effective in creating long-term engaging experiences that a robot alone. Considering that not all children respond to robots (and humans) in the same way, particular children with ASD (Scassellati et al., 2012), the ability of robots to adapt to the children’s needs and abilities would be highly beneficial. Autonomous robots with the ability to interpret human behaviors and emotions, and respond to them in appropriate ways could provide long-term, non-supervised, safe and non- restrictive learning experiences. Effective interpretation of emotions and social messages should draw on the combination of data obtained from multiple sensory modalities such as audio, vision and touch. Although systems that identify the mental/emotional state of children using physiological data have been proposed (Liu, Conn, Sarkar & Stone, 2008), for interventions with people with ASD it is important to use sensors that do not interfere on the child’s natural behavior.

Effective Integration of Robots into Interventions for People with ASD

Appropriate and progressive integration of socially-assistive robots as educational tools for children and adults with ASD is fundamental. As mentioned before, limited access to robots has resulted, particularly, in short-term qualitative studies. As the development of robots advances, we can expect an increasing number of researchers working on longitudinal studies that would provide quantitative data in addition to qualitative data. Results from these studies should be compared with current evidence-based practices and research-based therapies without the use of robots. In some cases, the same kind of evidence-based intervention (e.g. ABA-based therapy) can be used with and without a robot. Generalization and trans-

234 Social Stories in Robot-Assisted Therapy for Children with ASD

fer of new skills into real world situations should be fundamental during the evaluation of the different approaches. As robots become more affordable, they could be integrated more actively into every-day life al- lowing for supervised interventions in different environments, from schools and hospitals to homes, where children and adults could have the opportunity to practice new skills following the robot-assisted intervention. Alternatively, robots can be used to teach skills immediately after the occurrence of an event, for example: if a child gets upset after asked to share a toy, new skills can be though and practiced using a robot immediately after the incident. As robot autonomy increases, furthermore, robot-assisted intervention may be taken to a non-supervised approach in which robot-based games, such as those cur- rently available in mainstream technologies (Beaumont & Sofronoff, 2008), can be developed to provide additional opportunities to learn and practice new social skills.

ACKNOWLEDGMENT

The authors would like to thank Professor Kerstin Dautenhahn and Dr Ben Robins from the University of Hertfordshire for their ongoing support during this project.

REFERENCES

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ADDITIONAL READING

Alberto, P. A., & Troutman, A. C. (2012). Applied behavior analysis for teachers. Pearson Higher Ed. Cebula, K. R. (2012). Applied behavior analysis programs for autism: Sibling psychosocial adjustment during and following intervention use. Journal of Autism and Developmental Disorders, 42(5), 847–862. doi:10.1007/s10803-011-1322-x PMID:21725720 Cooper, J. O., Heron, T. E., & Heward, W. L. (2007). Applied behavior analysis (2nd ed.). Upper Saddle River, NJ: Pearson. Cornelius, K. E. (2013). Formative assessment made easy: Templates for collecting daily data in inclusive classrooms. Teaching Exceptional Children, 45(5), 14–21. doi:10.1177/004005991304500502

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Crosland, K., & Dunlap, G. (2012). Effective strategies for the inclusion of children with Autism in general education classrooms. Behavior Modification, 36(3), 251–269. doi:10.1177/0145445512442682 PMID:22563045 Fisher, W. W., & Piazza, C. C. (Eds.). (2011). Handbook of applied behavior analysis. New York: Guilford Press. Gammeltoft, L., & Nordenhof, M. S. (2007). Autism, play and social interaction. Jessica Kingsley Publishers. Grandin, T. (2009). Learning empathy: Emotion and autism. Thinking in pictures (84-100). London: Bloomsbury Publishing. Gray, C. (2010). The New Social Story Book. Arlington, TX: Future Horizons. Hart, J.E. & Whalon, K.J. (2011). Creating social opportunities for students with autism spectrum disorder in inclusive settings. Intervention in School and Clinic, 46(5), 273-279. 1053451210395382. Kulage, K. M., Smaldone, A. M., & Cohn, E. G. (2014). How will DSM-5 affect autism diagnosis? A systematic literature review and meta-analysis. Journal of Autism and Developmental Disorders, 1–15. PMID:24531932 Levine, K., & Chedd, N. (2007). Replays: Using play to enhance emotional and behavioral development for children with autism spectrum disorders. Jessica Kingsley Publishers. Marder, T., & deBettencourt, L. U. (2015). Teaching students with ASD using evidence-based practices: Why is training critical now? Teacher Education and Special Education: The Journal of the Teacher Education Division of the Council for Exceptional Children, 38(1), 5–12. doi:10.1177/0888406414565838 Matson, J. L., Adams, H. L., Williams, L. W., & Rieske, R. D. (2013). Why are there so many unsub- stantiated treatments in autism? Research in Autism Spectrum Disorders, 7(3), 466–474. doi:10.1016/j. rasd.2012.11.006 McClean, B., & Grey, I. (2012). An evaluation of an intervention sequence outline in positive behaviour support for people with autism and severe escape-motivated challenging behaviour. Journal of Intellectual & Developmental Disability, 37(3), 209–220. doi:10.3109/13668250.2012.704982 PMID:22873574 McDonald, M. E., Pace, D., Blue, E., & Schwartz, D. (2012). Critical issues in causation and treatment of Autism: Why fads continue to flourish. Child & Family Behavior Therapy, 34(4), 290–304. doi:10. 1080/07317107.2012.732849 Mohammadzaheri, F., Koegel, L. K., Rezaee, M., & Rafiee, S. M. (2014). A randomized clinical trial comparison between pivotal response treatment (PRT) and structured applied behavior analysis (ABA) intervention for children with autism. Journal of Autism and Developmental Disorders, 44(11), 2769–2777. doi:10.1007/s10803-014-2137-3 PMID:24840596 Murdock, L. C., & Hobbs, J. Q. (2011). Picture me playing: Increasing pretend play dialogue of children with autism spectrum disorders. Journal of Autism and Developmental Disorders, 41(7), 870–878. doi:10.1007/s10803-010-1108-6 PMID:20872061

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Ozdemir, S. (2008). The effectiveness of social stories on decreasing disruptive behaviors of children with autism: Three case studies. Journal of Autism and Developmental Disorders, 38(9), 1689–1696. doi:10.1007/s10803-008-0551-0 PMID:18373187 Phillips, N., & Beavan, L. (2012). Teaching Play to Children with Autism: Practical Interventions Using Identiplay. London: Sage Publications. Rodman, J. L., Gilbert, K. A., Grove, A. B., Cunningham, M., Levenson, S., & Wajsblat, L. (2010). Efficacy of brief quantitative measures of play for screening for autism spectrum disorders. Journal of Autism and Developmental Disorders, 40(3), 325–333. doi:10.1007/s10803-009-0880-7 PMID:19798562 Scott, T. M., Alter, P. J., & McQuillan, K. (2010). Functional behavior assessment in classroom settings: Scaling down to scale up. Intervention in School and Clinic, 46(2), 87–94. doi:10.1177/1053451210374986 Stiegler, L. N., & Davis, R. (2010). Understanding sound sensitivity in individuals with autism spectrum disorders. Focus on Autism and Other Developmental Disabilities, 25(2), 67–75. doi:10.1177/1088357610364530 Torres, C., Farley, C. A., & Cook, B. G. (2012). A special educator’s guide to successfully implementing evidence-based practices. Teaching Exceptional Children, 45(1), 64–73. doi:10.1177/004005991204500109 Virués-Ortega, J. (2010). Applied behavior analytic intervention for autism in early childhood: Meta- analysis, meta-regression and dose–response meta-analysis of multiple outcomes. Clinical Psychology Review, 30(4), 387–399. doi:10.1016/j.cpr.2010.01.008 PMID:20223569 Wolfberg, P. J. (2009). Play and imagination in children with autism. Lenexa, KS: AAPC Publishing. Wong, C., Odom, S. L., Hume, K. A., Cox, A. W., Fettig, A., Kucharczyk, S., & Schultz, T. R. et al. (2015). Evidence-based practices for children, youth, and young adults with autism spectrum disorder: A comprehensive review. Journal of Autism and Developmental Disorders, 45(7), 1951–1966. doi:10.1007/ s10803-014-2351-z PMID:25578338

KEY TERMS AND DEFINITIONS

Applied Behaviour Analysis (ABA): An evidence-based, intensive education therapy that has been shown to be highly effective in educating children and youth with disabilities, particularly those with autism spectrum disorders. Autism Spectrum Disorders (ASD): Lifelong developmental disability characterised by marked difficulties in social communication and interaction, restricted and repetitive behaviours, and sensory sensitivities. Evidence-Based Practices (EBP): Include intervention strategies, programs or models that, via well-designed quality research, have been shown to produce improvement in academic and behavioral functioning, when implemented with fidelity. Play: The way children organize and make sense of their worlds, through engagement with people, objects, and concepts.

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Play-Based Learning: Using play to allow children to express their uniqueness, enhance creativity and curiosity, and make connections between prior knowledge and new learning. Robot-Assisted Therapy (RAT): Using physical interaction with robots to assist individuals with disabilities. Socially-Assistive Robotics (SAR): Using robots to provide assistance to human users through social interaction. Social StoriesTM: Descriptions of appropriate behaviours in a given social situation, presented in a story format, with or without pictures. They are individualized and used to improve a person’s understanding of a social situation.

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