scholarly journals Does a Computer-Assisted language training program improve social conversational skills in Autism spectrum disorder?

2019 ◽  
Vol 6 (1) ◽  
pp. 1
Author(s):  
Lawrence Welkowitz
Autism ◽  
2019 ◽  
Vol 23 (6) ◽  
pp. 1586-1595 ◽  
Author(s):  
Hirokazu Kumazaki ◽  
Taro Muramatsu ◽  
Yuichiro Yoshikawa ◽  
Blythe A Corbett ◽  
Yoshio Matsumoto ◽  
...  

Job interviews are significant barriers for individuals with autism spectrum disorder because these individuals lack good nonverbal communication skills. We developed a job interview training program using an android robot. The job interview training program using an android robot consists the following three stages: (1) tele-operating an android robot and conversing with others through the android robot, (2) a face-to-face mock job interview with the android robot, and (3) feedback based on the mock job interview and nonverbal communication exercises using the android robot. The participants were randomly assigned to the following two groups: one group received a combined intervention with “interview guidance by teachers and job interview training program using an android robot” ( n = 13), and the other group received an intervention with interview guidance by teachers alone ( n = 16). Before and after the intervention, the participants in both groups underwent a mock job interview with a human interviewer, who provided outcome measurements of nonverbal communication, self-confidence, and salivary cortisol. After the training sessions, the participants who received the combined interview guidance by teachers and the job interview training program using an android robot intervention displayed improved nonverbal communication skills and self-confidence and had significantly lower levels of salivary cortisol than the participants who only received interview guidance by teachers. The job interview training program using an android robot improved various measures of job interview skills in individuals with autism spectrum disorder.


Author(s):  
Vikas Khullar ◽  
Harjit Pal Singh ◽  
Manju Bala

In the area of psychosis, autism spectrum disorder (ASD) is a mental disorder included with the major deficits associated with social interaction, communication, and repetitive or stereotypical behavior. A large number of computer-assisted approaches have been developed over the last few decades to improve the lifestyle of the subject with ASD. The aim of this study is to provide a detailed review of computational advancements for ASD interventions. This chapter summarizes the basic theories in autism and also discusses the technological developments of autism in the present era. With the enrichment in technological developments, researchers and experts focused on the monitoring and improvement of the skills (social, communication, and behavioral) in individuals with autism-related disorders. In conclusion, the work presented in this chapter summarizes that the evolutionary computational interventions have a remarkable possibility for the monitoring and basic skills enhancement in ASD.


Autism ◽  
2020 ◽  
Vol 24 (7) ◽  
pp. 1713-1725 ◽  
Author(s):  
Melanie Pellecchia ◽  
Rinad S Beidas ◽  
Gwendolyn Lawson ◽  
Nathaniel J Williams ◽  
Max Seidman ◽  
...  

This study examines how the introduction of TeachTown:Basics, a computer-assisted intervention for students with autism spectrum disorder, influenced teachers’ use of other evidence-based practices. In a randomized controlled trial that enrolled 73 teachers nested within 58 schools, we used three-level hierarchical linear models to evaluate changes in teachers’ use of evidence-based practices across the school year for those who received TeachTown:Basics versus those assigned to control. Both groups received training and implementation support to deliver three well-established evidence-based practices for autism spectrum disorder. Qualitative interviews were conducted with 25 teachers who used TeachTown:Basics to better understand their experience. Compared with teachers in the control group, teachers in the TeachTown:Basics group reported significantly less growth over the 9-month period in their use of evidence-based practices that require one-to-one instruction ( ps < 0.05), but no difference in their reported use of evidence-based practices that do not involve one-to-one instruction ( p = 0.637). Qualitative interviews indicated that teachers viewed TeachTown:Basics as an effective substitute for one-to-one instruction because it was less burdensome, despite the lack of support for TeachTown:Basics’ effectiveness. Before introducing new practices, education leaders should carefully consider both evidence of effectiveness and the potential impact on the use of other evidence-based practices. Lay abstract Interventions for children with autism spectrum disorder are complex and often are not implemented successfully within schools. When new practices are introduced in schools, they often are layered on top of existing practices, with little attention paid to how introducing new practices affects the use of existing practices. This study evaluated how introducing a computer-assisted intervention, called TeachTown:Basics, affected the use of other evidence-based practices in autism support classrooms. We compared how often teachers reported using a set of evidence-based practices in classrooms that either had access to TeachTown:Basics or did not have the program. We found that teachers who had access to the computer-assisted intervention reported using the other evidence-based practices less often as the school year progressed. Teachers also reported that they liked the computer-assisted intervention, found it easy to use, and that it helped overcome challenges to implementing other evidence-based practices. This is important because the computer-assisted intervention did not improve child outcomes in a previous study and indicates that teachers may use interventions that are appealing and easier to implement, even when they do not have evidence to support their effectiveness. These findings support the idea of interventions’ complexity and how well the intervention fits within the classroom affect how teachers use it and highlight the need to develop school-based interventions that both appeal to the practitioner and improve child outcomes.


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