Additional Research and SourcesStudy out of Taiwan shows evidence of beneficial use of avatars
THERAPISTS LOOK TO SOFTEN ABA THERAPIES
As of Jan. 22, 2016
By Dr. Tom Buggey with Gary Jesch
Theoretical and empirical evidence. There are very few instructional strategies that have proven successful for working with children with autism. The method of choice over the last half century has been intense Applied Behavior Analysis (ABA). Although ABA has the most comprehensive treatment database, and there is evidence to suggest that the more intense the training, the better the outcomes, especially related to IQ and language (Virués-Ortega, 2010), there are still unresolved issues regarding the ethics of a 30 – 40 hr-per-week regimen for younger children. Additionally, a well-constructed study coming out of Sweden revealed that ABA treatments were effective, but there was no relationship between the intensity of ABA treatment and education outcomes (Fernel, et al., 2011). While ABA will probably always be an important part of autism treatment, it is important to continue the search for other effective treatments that have a “softer” impact on children with autism and their families.
The use of video-based interventions such as peer-modeling (e.g. Charlop, & Milstein, 1989), Point-of-view modeling (e.g. Hine & Wolery, 2006), self-modeling (e.g. Buggey & Ogle, 2013), and computer assisted instruction (e.g. Ayres, Maguire, & McClimon, 2009) has been gaining popularity in the field of autism. The research database has increased to the point where many video-based methods can be considered research-based (Bellini, Akulian, & Hopf, 2007). The commonality across these interventions is the video screen. The child focuses on a two-dimensional field rather than on an in-vivo adult.
Over the past 40 years, video modeling has relied on humans as the models whether they are peers, adults, or the viewers themselves. On the other hand, research into the use of animated avatars as video models for children with autism is in its infancy. The popularity of cartoon programming and “culture” is obvious among youngsters and has been used for modeling social and academic skills on shows like Sesame Street™, The Electric Company™, Dora the Explorer™, Sid the Science Kid™, and many computer-based programs. Sesame Street remains the most studied of all children’s programming with universally positive outcomes in social and academic skills found in studies conducted from 1970 through 2012 (Mares & Pan, 2013). Unfortunately, there are no studies that have examined Sesame Street’s impact on children with autism. Additionally, because Sesame Street contains both human actors and animation, it is difficult to make assumptions about the impact of the animated characters alone.
In order for any instructional strategy to be successful, it must be able to engage children and hold their attention (Chien, et al., 2010). Therefore, several researchers have looked at animated avatars to gauge their potential for assisting with learning. Moore, Cheng, McGrath, and Powell (2005) attempted to determine whether children with autism could recognize facial expressions as expressed by avatars. Over 90% of the 34 participants correctly identified emotions being displayed. The researchers did not address the educational potential of the virtual environments, but did state that their findings represented a first and important step on the road to that objective.
Hopkins and colleagues (2011) investigated the use of realistic, interactive avatar faces to train eye-gaze, discrimination of facial expressions, and recognition of faces and emotions using FaceSay™, a social skills training program designed for children with ASD. The avatars are static, but are interactive in the sense that users can add and replace features (e.g. exchange a pouty mouth for a smiling one). They recruited 49 participants who were then divided into groups of high and low functioning autism. Both groups improved in social interaction and emotional recognition. The high-functioning group also improved in facial recognition.
A logical next step in the use of avatars would be to provide them with animated movement and real-time voices. Cheng and Ye (2010) used a collaborative virtual learning environment (CVLE) system that utilized animated 3D avatars along with verbal and text communication to determine if social interactions could be increased. Each of the three participants was represented by an expressive avatar placed in a social scene. They were asked to communicate among each other for 17 days using texting and voice communication. All communication would pass through the avatar. Dependent variables included: 1. Responding to questions; 2. Manners; 3. Understanding of social behaviors. The latter two variables were evaluated using an oral exam. The authors noted that all participants made substantial gains across all areas and maintained the skills over a nine-day maintenance phase.
Researchers in Greece (Konstantinidis, Hitoglou-Antoniadou, Luneski, Bamidis, & Nikolaidou, 2009) used affective avatars (ones that could show emotion and produce speech with lip synchronization) to teach 50 children with autism the recognition of emotional states and select daily living skills. In addition, 13 teachers who used the system responded through a questionnaire regarding the usability, complexity, and value of the avatars. Results indicated success in student learning and teacher feedback was very positive related to usability and potential for instruction. Other studies have looked at training recognition of facial emotions with slightly more advanced technology. Orvalho, Miranda, and Sousa (2009) developed a system that allowed therapists to directly alter facial expressions in real time and to lip-sync exchanges with their patients with ASD. The avatars could take on the appearance of realistic humans, cartoons, or fantastical creatures; however, the screen only depicted the head and neck of the avatar. The authors reported promising results in trials, but had no empirical support.
The technology needed to allow avatars to become interactive and responsive, and to portray affective features has only recently become available. The 3D Digital Puppeteer program provides these innovations, including lip sync, real-time movement of the avatar, and a full-range of facial expressions. Therefore, in the Phase I aspect of the study we will determine whether the Invirtua 3D Digital Puppeteer™ program can hold the child’s attention, improve the behavior of responding to questions, help them succeed at language targets, expand skills learned and be rated highly on usability by users. Phase II objectives will focus on the users’ ability to control the avatar and the generalization of learned behaviors.
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