Introduction

Children suffering from autistic spectrum disorder exhibit qualitative impairments in social interaction and communication as well as repetitive and stereotyped patterns of behavior, interests, and activities. They often show a significant delay in the development of spoken language and a failure to reciprocate on a social or emotional level, and are often seen as inflexible and compulsive when it comes to schedules and routines (DSM-IV). Consequently, instruction of autistic children can be a frustrating – and expensive – undertaking. In order to be effective, instructors have to overcome communication barriers, engage a reluctant learner, and work in a world where the unexpected, no matter how inconsequential it may seem, can completely overwhelm the child. Intensive one-on-one instruction becomes a necessary requirement for a successful educational program despite the cost of the instructor’s already limited time and attention (Silver & Oakes, 2001).

Several methods have been developed over the past forty years to teach children with autism, including Applied Behavior Analysis (Bonvillian, Kissane, & Dooley, n.d.), the TEACCH program (Mesibov, n.d.), and sign training (Bonvillian, Kissane, & Dooley, n.d.). These methods have proven successful to varying degrees, but come at a high cost, in terms of both time and money, due to their intensive nature. In addition, these successes are often dependent on prior student ability, working better for some subpopulations than others (Bonvillian, Kissane, & Dooley, n.d.).

Recent studies have shown that autistic populations respond well to computer assisted instruction (CAI) programs; these programs offer predictable, stable results and never suffer from fatigue, unlike caregivers who invest much of their time and resources towards helping these children (Silver & Oakes, 2001). Autistic children tend to pay more attention to computer programs than they do to instructors in a traditional learning environment, and as a result their learning potential can actually increase when using CAI programs (Moore & Culvert, 2000). These programs also offer more basic benefits: they are much cheaper (in terms of money, time, and other resources) than intensive one-on-one programs are.

The current educational landscape is shifting in such a way that as to promote additional study of CAI with autistic populations. Increased awareness from clinicians, academics, and congressional leaders has led to record-high funding levels for autism research (Autism Speaks, n.d.), while federal education initiatives such as the No Child Left Behind Act of 2001 provide blanket support for increasing access to technology in schools and developing individualized instruction (NCLB, 2001).

Characteristics of Autism

There are three major diagnostic criteria for autism. The first involves impaired social interaction skills - difficulty understanding facial expressions, a lack of emotional reciprocity, and a failure to develop age-appropriate peer relationships are a few common impairments (DSM-IV). The second criterion involves impaired communication; it is a common characteristic among autistic children to have severely delayed speech or mutism (Bonvillian & Nelson, 1976; DSM-IV). The last deals with repetitive and stereotype patterns of behavior, such as a strict adherence to a specific, nonfunctional routine or ritual (DSM-IV). In addition, it is commonly believed that autistic individuals have difficulty screening out unnecessary sensory information, causing them to be overwhelmed in many situations and social settings.

The severity of these symptoms can fall into a very wide range of cases. Individuals with Asperger’s syndrome, a “mild” form of Autistic Spectrum Disorder, might appear to be very capable in their daily lives but have difficulty reading and interpreting the facial expressions of others (Silver & Oakes, 2001). An example of a more extreme case of autism involves a child who reaches his ninth birthday having failed to produce words or even to imitate sounds (Bonvillian & Nelson, 1976).

It is believed that autistic children have difficulties making visual-auditory cross-modal association (Fulwiler & Fouts, 1975) and do not react well to multiple sources of sensory input, a situation that can create an overpowering stimulation for the child (Strickland et al., 1996).

Common Approaches for Teaching Autistic Children

Though decades have passed since Leo Kanner first described autistic behaviors in children in 1943, and the intervening years have seen significant study on the nature of the condition, the root cause of autism remains a mystery. Kanner originally theorized that such behavior was the product of the child’s environment and upbringing, an idea that he himself abandoned a short time later. Contemporary theories point toward a neurological condition, and recent studies suggest a possible genetic factor. Whatever the cause, diagnoses of autism have increased steadily over the years – either due to an increased number of cases or simply greater awareness of the condition – from as few as 1 in 10,000 in the 1940s to as many as 1 in 166 in 2005 (Bonvillian, Kissane, & Dooley, n.d.).

As the number of children diagnosed with autism increased, new methods for educating this population became necessary. Because three quarters of autistics qualify as mentally retarded, and social and communication skills are often poor or non-existent, many of these individuals will require lifelong assistance from relatives or caregivers (Bonvillian, Kissane, & Dooley, n.d.). Instructional methods for these children, therefore, must be tailored to meet specific and highly demanding needs, often concentrating on developing skills most educators take for granted, such as speech or eye contact.

Beginning in the 1960s, Ivar Lovaas developed a model of instruction based on operant conditioning. Applied Behavior Analysis (or the “Lovaas Method” as it is sometimes referred to) uses a system of rewards and punishments to encourage a particular skill, such as speech, targeted by the instructor. This method has proven successful for a number of autistic children to varying degrees (Bonvillian, Kissane, & Dooley, n.d.), and has become popular among parents, educators, and researchers. According to the Lovaas Institute website, over 500 research studies between 1985 and 2000 investigated the use of ABA with autistic populations, and evidence suggests clear advantages of ABA over traditional special education programs (Lovaas Institute, n.d.). The Surgeon General’s report on mental health points to thirty years of research supporting the use of ABA to teach social, behavioral, and communication skills (HHS, 1999).

The success of the Lovaas Method is not without its price, however. The Lovaas Institute endorses a program of 40 instructional hours each week, claiming that no study to date using a less intensive course of treatment has approached the effectiveness reported in their 1987 study of the ABA model (Lovaas Institute, n.d.). Additionally, the success of the program is largely dependent on the child’s abilities when the program is initiated; in other words, it does not work equally well with all autistic subpopulations. Contrasting the results of using ABA to teach speech skills to a group of mute (non-speaking) and echolalic (capable of imitating speech sounds) autistic children, Lovaas noted:

“In general, our language program was not as successful for the mutes as for the echolalics. If the child was already echolalic, even though he did not know the meaning of his vocal expressions or how to arrange them in sentences, then it seemed easy for us to rearrange behavior (syntax) and bring it under appropriate stimulus control (semantics) (1997, p.118).”

Another approach to working with children with autism is the Treatment and Education of Autistic and related Communication-handicapped CHildren, or TEACCH. This approach, developed in the 1970s by University of North Carolina researcher Eric Schopler, focuses on the student as a whole, rather than attempting to apply rigid programs or focus on a particular symptom. TEACCH is based on the idea that autistic children need special accommodations for their condition, such as highly-structured environments and schedules, due to their inability to easily adapt to fluid situations. While ABA focuses on remediation, TEACCH concentrates on areas of the student’s interests and abilities – often including visual representations, memorization, and attention to details – to increase motivation and develop a positive, productive teacher-student relationship with the child. This approach carries over to the home life, with an effort to include and educate parents on how to develop communication and social skills in leisurely, non-academic settings (Mesibov, n.d.). The 1999 Surgeon General’s report on mental health points to findings indicating that TEACCH has been successful compared to control groups (HHS, 1999).

A third approach is to use sign training. Half of all children with autism are functionally mute, meaning that they acquire fewer than five spoken words, though they are able to produce non-speech sounds (Layton, 1988). This subpopulation is often referred to as “low-functioning.” Even after several years of speech therapy programs, many students fail to develop a minimal level of spoken language skills. To address the ineffectiveness of speech programs for this subpopulation, during in the 1970s there was a surge in the number of non-speaking students enrolled in sign language training programs (Bonvillian, 2002). There have been several cases where a low- to moderate-functioning autistic child has learned sign language and later developed some level of speech. Similarly, increased language skills have led to a corresponding decrease in behavioral problems in several cases (Bonvillian & Nelson, 1976; Creedon, 1973; Konstantareas, Webster, Oxman, 1979; Schaeffer, 1980).

Several theories exist as to the best method for teaching sign language to autistic children. Some clinicians believe that due to the difficulty autistics have with information presented through multiple sensory modalities, presentation of signed language should be limited to signs only (Layton, 1988). Others think that training should alternate between signs and speech and later be synthesized into signed speech (simultaneously signing and speaking) after the child has developed mastery over the individual elements (Schaeffer et al., 1977). The preferred method has been to teach simultaneous communication (teaching children to sign and speak at the same time) based on the theory that it is better to receive both auditory and visual stimuli (Layton, 1988).

Layton (1988) conducted a study comparing four therapies for teaching autistic children language skills: speech-only, sign-only, simultaneous communication, and alternating between speech and sign. His results did not find any method to be superior to another; in fact, he found that autistic children with more advanced language skills actually performed equally well between all of the systems. However, lower functioning children who participated in his study did poorest in the speech-only condition, indicating that any program using sign language to teach low-functioning autistic children language skills is preferable to a traditional speech therapy program. Methodologies for teaching sign language to autistic children have varied widely (Fulwiler and Fouts, 1976; Konstantareas, Oxman, & Webster, 1977; Miller & Miller, 1973; Schaeffer et al., 1977).

Each of the approaches mentioned has been shown to be successful, to varying degrees, with certain autistic populations. There is an ongoing debate regarding the “best” approach for teaching autistic children, and it should be noted that these examples are not necessarily mutually exclusive, nor can they be easily compared in terms of efficacy. However, there is one measure by which all three are equal: they each require intensive, often one-on-one training over the course of many hours, days, weeks, and months. Time spent working with a single student with special needs is time that is unavailable to other students (Moore & Culvert, 2000). Ironically, traditional instruction, involving social interaction between the student and teacher, may actually make it more difficult for the student to learn due to his social impairments (Silver & Oates, 2001).

Computer Assisted Instruction

B.F. Skinner, a behaviorist perhaps best known for his work with operant conditioning with pigeons, began working with programmed instruction in the late 1950s. He believed that it was necessary to develop teaching machines capable of teaching students skills such as arithmetic and spelling, using his operant conditioning theories as a basis for his efforts. Though Skinner’s true message was of the need to develop programs of instruction, the initial attention was monopolized by the machines themselves, leading to the “teaching machine revolution.” Eventually, production of these machines far outpaced the development of the programs they were designed to run, and attention would ultimately turn toward the content itself, known as programmed instruction. Excitement grew quickly over Skinner’s grand promises of the effectiveness of this new approach (Saettler, 1990).

In spite of the popularity of Skinner’s theories, schools were slow to adopt teaching machines in the classrooms. Emerging research also began to question the validity of Skinner’s claims of success despite reports of success from schools which had adopted the method. Programmed instruction took a major blow with the development of the machine-program dichotomy, Borne out of earlier disagreements regarding the relative importance of hardware versus software, this dichotomy led to manufacturers of machines and programs alike pushing stereotypical products into the market without adequate testing or research, boasting largely unfounded claims as to their relative efficacy. The result was that programmed instruction stagnated at the very moment it was poised to take off, and meaningful advancements were nearly non-existent. Most problematic was the fact that most students reported being bored with their teaching machines, often to the point that they would damage or destroy them in order to avoid using them further (Saettler, 1990).

Ultimately, research failed to support any clear advantages of programmed instruction over traditional methods, pointing to mixed or inconsistent results and cases where successful completion of the program did not transfer to passing achievement tests. Skinner himself remarked that the movement had lost its focus and grounding in research, and had been misunderstood. In the early 1970s, publishers began to halt production of new programs, effectively ending the programmed instruction movement. Nevertheless, Skinner’s idea of teaching machines had pushed the idea of instruction based on behaviorist theories, and laid the groundwork for computer assisted instruction in the decades to come (Saettler, 1990).

Other approaches to instruction during this period focused on an individualized course of study for each student. F.S. Keller, a Skinnerian behaviorist, proposed the a plan to free students to pursue their education at their own pace, focusing on texts and tutoring and using lectures as a motivational tool rather than a primary content delivery method. Interestingly, while students appreciated this added degree of self-determination, studies found that they had to study significantly more and had higher dropout rates. Another approach, Individually Prescribed Instruction, used a series of pre- and post-tests to determine which units each student should work on. Critics argued that this approach was too expensive and overly complicated for the instructor, and support was pulled after a few years that saw regular changes and corrections to the model. The Program for Learning in Accordance with Needs approach asked schools to select from a bank of behavioral objectives that would be pieced together to form lessons. Despite PLAN’s success and expanding participant pool, the cost of updating the bank of items proved to be prohibitive, resulting in the program’s early termination. By the late 1970s, these individualized instruction programs would fall out of favor for a variety of reasons, including problems resulting from poor implementation in the schools and inconclusive results regarding their efficacy relative to traditional approaches (Saettler, 1990).

Early Computer Assisted Instruction efforts carried on the tradition of using behaviorist models to shape the learner’s responses through a series of trials. These programs became known as “drill-and-practice” and “tutorial” applications, and gained in popularity during the rapid decline of programmed instruction. This fortuitous timing led to rapid funding of major CAI initiatives using resources originally designated for now-failed approaches, allowing CAI to quickly establish itself on the academic scene (Saettler, 1990).

Support for CAI dissipated rapidly in the late 1970s for several reasons. First of all, computers at that time were extremely expensive, often making their rapid adoption in schools prohibitively expensive despite significant interest and excitement from academics and government leaders (Saettler, 1990). Also, the prosperous market envisioned by computer makers and software companies never materialized, forcing several companies to close shop of reinvest their efforts elsewhere (Saettler, 1990; Morrison, Ross, & O’Dell, 1995). Finally, the instructional theories failed to anticipate the fundamental opposition posed by teachers and school administrators due to a lack of cultural diffusion (Venezky & Osin, 1991). Ultimately, CAI was doomed because it was oversold and improperly or incompletely implemented (Saettler, 1990; Venezky & Osin, 1991).

In the late 1970s and early 1980s, the appearance of the microcomputer revitalized the CAI movement. Because computers were now smaller and cheaper, and because they were beginning to find their way into the everyday lives of average individuals, they became more palatable to schools and districts almost overnight (Venezky & Osin, 1991; Saettler, 1990). During this time, CAI began to differentiate itself from some of its failed Skinnerian predecessors by changing its role, presence, and the relative ease of delivering instructional content (Saettler, 1990); however, it was still grounded in its behaviorist roots (Venezky & Osin, 1991). Additionally, Venezky and Osin (1991) go on to claim that the resurgence of CAI in the early 1980s did little, if anything, to solve the underlying problems with previous instructional efforts; rather, the relative simplicity of producing and delivering content on these byte-sized technological wonders encouraged publishers to go back to the well and develop new programs without any clear improvements or additional research.

In the two decades that have passed since the rebirth of CAI, the landscape of computer-based instruction has changed surprisingly little. Morrison, Ross, and O’Dell (1995) equate the claims of an impending computing revolution in education to the failed ambitions of 1970s efforts in programmed instruction. The National Educational Technology Plan of 2004 points to near ubiquitous presence of computers and internet access in schools today, yet acknowledges a significant lack of planning and preparation for teachers and schools to make full use of these advantages (DOE, 2004). Even in the event that large-scale planning and teacher training lead to increased use of computers in the classroom, it is unlikely that such a change will manifest itself as CAI; in an age where such programs are referred to as “drill-and-kill” software, institutional memory of previous failures works to inoculate schools and districts from widespread adoption of anything resembling 20th century CAI initiatives. Instead, schools will be more likely to exploit specific advantages of computers in an attempt to deliver instructional content based on modern educational theories and practices (Morrison, Ross, and O’Dell, 1995).

Computer Assisted Instruction with Autistic Children

In recent years efforts have been made to introduce computer assisted instruction as a means of relieving part of the burden of one-on-one instruction with autistic children while creating a more efficient medium for intensive instruction. Studies have found that autistic children often find computer-based instruction as more interesting than teacher-based instruction; the children spend more time paying attention and are often more motivated to continue working when they are working with computers (Moore & Culvert, 2000). The development of computer assisted instruction for children with autism could lead to breakthroughs in overcoming the social, emotional, and communication difficulties associated with Autistic Spectrum Disorder, while simultaneously easing the burden of caregivers.

In addition to the many established benefits of computers in instructional technology, there are several additional reasons that computer intervention programs are an appropriate choice for autistic populations (Silver & Oakes, 2001). As mentioned above, one of the more common difficulties autistic children face is sensory-overload: the inability to filter out unneeded and irrelevant sensory input. Placing the child at a computer terminal and having him focus on the screen can help to avoid that problem because only important and necessary information needs to be displayed. The computer also provides an extremely stable and regular work environment; the computer has the ability to produce, without fear of fatigue or boredom, predictable and immediate feedback to any input the child provides for as long as the child wishes to participate. The goals and expectations are transparent to the child and the program moves at his own pace, not one set by the instructor or other children in the class. Skill sets can be customized to fit the student’s needs, and the structure of the program designed to increase in scope and difficulty as the child progresses (Silver & Oakes, 2001). In addition, computer intervention programs can be enhanced with multimedia (such as sound effects, graphics, and animation) designed to hold the attention of the children. These additions can make instructional sessions more interesting, and therefore more successful.

Not surprisingly, programs designed in such a fashion have been very successful among autistic children: Autistic students participating in a study by Moore and Culvert (2000) spent more time attending to the computer assisted instruction than they did to the teacher-based instruction and more than half wanted to continue the intervention. In contrast, no subjects in the control group, who received only teacher-based instruction, were interested in continuing. The program, designed to teach autistic children new vocabulary words, produced a strong correlation between time spent paying attention and post-test scores. This meant that students who participated in the computer assisted instruction were able to learn more, and the more time they spent at the computer the more words they were able to learn.

Blischak and Schlosser (2003) investigated the use of speech generating devices (SGDs), such as talking word processors, as a tool for improving spelling among non-speaking autistic children. When a word was produced, students received simultaneous feedback in the form of synthetic speech (the word spoken through the machine) and text (the word displayed on a screen). This dual feedback reinforced proper spelling with both aural and visual stimuli, increasing the rate at which the children were able to master the spelling tasks given to them. The authors point out that the students were able to continue practicing their spelling without the presence of an instructor, freeing the teacher from a demanding time commitment and allowing for greater flexibility in instruction. Autistic children in this study enjoyed using the SGDs and improved in other areas besides spelling. One surprising finding from this study is that, given feedback including print only, speech only, or print with speech, autistic subjects were split evenly: Half of the students did equally well on speech and speech with text and poorly on text only, while the other half did poorly on speech only and equally well in the other two categories. This is contrary to conventional wisdom that suggests that autistic individuals are overwhelmingly visual learners (Layton, 1988) and strongly suggests that multiple-feedback approaches (involving both audio and video feedback) will be more successful overall then any single approach.

Communication skills are not the only target of computer intervention programs. A Bernard-Opitz, Sriram, and Nakhoda-Saquan (2001) study investigated how well students would be able to learn about social problem-solving skills, a stereotypical weakness for autistic children. The program presented a series of problems and tracked creative responses among autistic children and normal-functioning children. Both groups improved significantly along similar lines, with the number of computer sessions correlating with increased success. Important to note, however, was that while normal children seemed to grow bored with the program after a while, autistic children seemed to enjoy the experience a great deal. This enjoyment translated into additional motivation and the resulting increase in test scores on a topic normally considered prohibitively difficult for autistic children (Bernard-Opitz, Sriram, & Nakhoda-Sapuan, 2001).

Silver and Oakes (2001) investigated computer assisted instruction in teaching about the emotions of others, another common impairment in autistic children. The program presented short stories and asked the student to identify the emotion the character experienced. For example, the child might be told that Sally won the race, and show a picture of a runner crossing a finish line, and ask if Sally is happy, sad, or angry. Correct answers were rewarded with positive feedback, whereas a wrong answer caused the computer to provide help until the correct answer was chosen. The program, called the Emotion Trainer, provided three separate types of cues asking the child to identify the correct emotion, including trials having to do with predicting emotion based on external stimuli and mental states. The study showed significant improvement among the students in these two areas.

Strickland and her colleagues (1996) take a different approach to using computer assisted instruction for teaching autistic children. Rather than providing an exercise to be repeated over and over again until a fixed outcome is achieved, this study is designed to create an open-ended instructional experience where the child has complete control over the outcomes. Virtual reality, the immersion of the user into a computer-generated environment, is being investigated as a potential tool to teach autistic children. The goal in this study was to investigate the tolerance of autistic children to the virtual reality experience. Ultimately, the researchers hoped to use the system to teach the children how to cross the street safely. While this study was more interested in the viability of using virtual reality than in quantifying the outcomes of its use, it is nonetheless worth studying the reactions of the two children; although one child was clearly trying to understand how it worked by looking around the room for the source of the images, both children were generally accepting of this new world.

Changing Landscape

As awareness of autism has increased, especially over the past decade, more and more opportunities to research new treatment methods are becoming available. The Combating Autism Act, currently in committee in both chambers of the U.S. Congress, seeks to add an additional $176 million per year over the next five years to fight autism through research, screening, education, and intervention (H.R. 2421, 2006; S. 843, 2006). If successful, these additional funds would double the existing resources set aside by the National Institute of Health for combating autism (Autism Speaks, n.d.). This legislation represents a major attitudinal shift at the highest levels of government, where lawmakers are beginning to treat autism as a major disability worth the effort to treat and, hopefully, cure (HHS, 1999).

At the same time, the No Child Left Behind Act of 2001 has provided increased federal funding to provide a series of services to schools including, among other items, CAI applications (NCLB, 2001). The National Educational Technology Plan for 2004 calls for schools to “encourage ubiquitous access to computers and connectivity for every student” and a “systemic approach to creating [digital] resources for students to customize learning to their individual needs” (DOE, 2004, p.43).

This collision of imperatives – to develop new educational methods for autistic populations and to employ the use of technology to meet the needs of individual students – creates an environment ripe for creating new computer-based approaches for teaching autistic populations. Increased awareness of autism (Bonvillian, Kissane, & Dooley, n.d.), combined with the systemic integration of technology in schools (DOE, 2004), provides a unique opportunity for schools and researchers to come together and develop new techniques and technologies aimed at relieving the burden placed on instructors of autistic students.

References

Autism Speaks at Work in the Nation’s Capital. (n.d.). Retrieved May 18, 2006 from http://www.autismspeaks.org/supportlegislation/legislation.php

Bernard-Opitz, V., Sriram, N. & Nakhoda-Sapun, S. (2001) Enhancing social problem-solving in children with autism and normal children through computer-assisted instruction. Journal of Autism and Developmental Disorders, 31, 377-384.

Blischak, D. & Schlosser, R. (2003) Use of technology to support independent spelling by students with autism. Topics in Language Disorders, 23, 293-304.

Bonvillian, J. & Nelson, K. (1976) Sign language acquisition in a mute autistic boy. Journal of Speech and Hearing Disorders, 41 (3), 339-347.

Bonvillian, J. (2002) Sign communication training and motor functioning in children with autistic disorder and other populations. In D. Armstrong, M. Karchmer, & J. Van Cleve (Eds.), The study of signed languages: essays in honor of William C. Stokoe. Washington, D.C.; Gallaudet University Press.

Bonvillian, J. D., Kissane, N. A., & Dooley, T. T., with F. T. Loncke. (n.d.). Simplified signs: A manual sign communication system for special populations. Mahwah, NJ: Lawrence Erlbaum Associates. (Approved for publication and contract extended)

Clarke, S., Remington, B., & Light, P. (1988) The role of referential speech in sign learning by mentally retarded children: a comparison of total communication and sign-alone training. Journal of Applied Behavioral Analysis, 21, 419-426.

Combating Autism Act of 2005, H.R. 2421, 109th Cong. (2006).

Combating Autism Act of 2005, S. 843, 109th Cong. (2006).

Creedon, M. (1973, March) Language development in nonverbal autistic children using a simultaneous communication system. Paper presented at the Society for Research in Child Development meeting, Philadelphia, PA.

Diagnostic and Statistical Manual of Mental Disorders: DSM-IV-TR. (2000) Fourth edition text revision. Washington D.C.: American Psychiatric Association.

Fulwiler, R. & Fouts, R. (1976) Acquisition of American Sign Language by a noncommunicating autistic child. Journal of Autism and Childhood Schizophrenia, 6 (1), 43-51.

Konstantareas, M., Oxman, J., & Webster, C. (1977) Simultaneous communication with autistic and other severely dysfunctional nonverbal children. Journal of Communication Disorders, 10, 267-282.

Konstantareas, M., Webster, C., & Oxman, J. (1979) Manual language acquisition and its influence on other areas of functioning in four autistic and autistic-like children. Child Psychology and Psychiatry, 20, 337-350.

Layton, T. (1988) Language training with autistic children using four different modes of presentation. Journal of Communication Disorders, 21, 333-350.

Lovass, O.I. (1977). The autistic child: Language development through behavior modification. New York, NY: Irvington Publishers, John Wiley & Sons

Lovass Institute – Frequently Asked Questions. (n.d.). Retrieved May 18, 2006 from http://www.lovaas.com/faq.php

Mesibov, G. (n.d.). What is TEACCH? Retrieved May 18, 2006, from http://www.teacch.com/whatis.html

Miller, A. & Miller, E. (1973) Cognitive-developmental training with elevated boards and sign language. Journal of Autism and Childhood Schizophrenia, 3 (1), 65-85.

Moore, M. & Culvert, S. (2000) Brief report: Vocabulary acquisition for children with autism: teacher or computer instruction. Journal of Autism and Developmental Disorders, 30, 359-362.

Morrison, G., Ross, S. & O’Dell, J. (1995). Applications of Research to the Design of Computer-Based Instruction. In Anglin, G. (Ed.). Instructional Technology: Past, Present, and Future. (pp 216 – 221). Englewood, CO: Libraries Unlimited.

No Child Left Behind. (2001). Retrieved May 18, 2006 from http://www.ed.gov/nclb/landing.jhtml

Saettler, P. (1990). The Evolution of American Educational Technology. Englewood, CO: Libraries Unlimited.

Schaeffer, B., Kollinzas, G., Musil, A., & McDowell, P. (1977). Spontaneous verbal language for autistic children through signed speech. Sign Language Studies, 17, 287-328.

Schaeffer, B. (1980) Teaching signed speech to nonverbal children: theory and method. Sign Language Studies, 26, 29-63.

Silver, M. & Oakes, P. (2001) Evaluation of a new computer intervention to teach people with autism or Asperger syndrome to recognize and predict emotions in others. Autism, 5, 299-316.

Strickland, D., Mesibov, G., & Hogan, K. (1996) Two case studies using virtual reality as a learning tool for autistic children. Journal of Autism and Developmental Disorders, 26, 651-659.

U.S. Department of Education, Office of Educational Technology. (2004). Toward a New Golden Age in American Education: How the Internet, the Law, and Today’s Students are Revolutionizing Expectations. Washington, D.C.

U.S. Department of Health and Human Services. (1999). Mental Health: A Report of the Surgeon General—Executive Summary. Rockville, MD: U.S. Department of Health and Human Services, Substance Abuse and Mental Health Services Administration, Center for Mental Health Services, National Institutes of Health, National Institute of Mental Health

Venezy, R. & Osin, L. (1991). The Intelligent Design of Computer-Assisted Instruction. White Plains, NY : Longman Publishing Group.