Abstract
Introduction Fortunately, advances in behavior analytic intervention and treatment for children with autism and related disabilities have produced significant positive shifts in developmental trajectories and brighter futures for many children who receive such intervention (e.g., Lovaas, 1987; McEachin, Smith & Lovaas, 1993; Smith, Groen, & Wynn, 2000; Sallows, & Graupner, 2005). Unfortunately, despite these advances and despite the best efforts of caring and skilled interventionists, some children with autism do not learn to speak and do not gain enough spoken language for them to rely on speech to function well in the world. Studies estimate that between 25% and 61% of children with autism remain essentially non-speaking despite the intervention they receive (Weitz, Dexter, & Moore, 1997). For those children who do not develop effective and efficient speech, technology may provide assistance. Augmentative Communication and Children with Autism With such a significant number of students struggling to communicate their basic needs and opinions, augmentative and alternative communication (AAC) seems to be a natural place to turn for answers. AAC seeks to compensate, either temporarily or permanently , for the impairment and disability patterns of individuals with severe expressive communication disorders (American Speech-Language-Hearing Association, 1989, p.107)). While Mirenda (2003) summarized research that demonstrated the success of teaching learners with autism to use non-electric aided communication systems (e.g., pictures, line drawings), the research was restricted to teaching a single verbal operant (mands) rather than reporting the results of teaching a wider range of verbal operants that probably comprise fully developed and useful verbal repertoires such as tacts and intraverbal responses using such AAC systems. Mirenda (2003) concluded her paper by calling for more research that can direct teachers, Speech-Language Pathologists, and other service providers to specific answers about which systems will work best for particular learners with autism. She carefully noted that, instructional variables are also critically important, and can play pivotal roles in the success of AAC endeavors. Speech-Generating Devices and Autism Many children with autism are good candidates for having their spoken communication supported or replaced by technology such as AAC (Mirenda, 2003). While not all AAC systems produce machine-synthesized speech, some AAC devices can allow children and others to communicate by producing synthesized vocal responding following a series of motor responses. With such devices, the machine produces a string of words or other units of speech after the child has ordered those units by pressing corresponding buttons on the device. Studies on the effects of speech output as an independent variable are scarce and only a very few studies have examined the effects of speech output as an independent variable in interventions with children with autism (cf. Parsons & La Sorte, 1993; Scholosser, Blishchak, Belfiore, Bartley, & Barnett, 1998; Bock, Stoner, Beck, Hanley, & Prochnow, 2005). Parsons and La Sorte (1993) investigated the effects of including synthesized speech along with computer instruction on the spontaneous vocalizations in 6 children with autism, ages 4 to 6 years old. Parsons and La Sorte applied a design that they called an interactional single subject design with both additive (A-B-BC-B-BC) and reductive (A-BC-B-BC-B) sequence combinations to isolate whether synthesized speech increased the participants' spontaneous communication. Measuring spontaneous vocalizations, they found the computer-assisted communication intervention by itself produced no positive change on the participating children's spontaneous communication. However, when the researchers added synthesized speech to the intervention package, the participating children's spontaneous communication increased. …
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More From: The Journal of Speech and Language Pathology – Applied Behavior Analysis
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