The uses of technology for and with children with Autism Spectrum Disorders

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In: Handbook of Technology in Psychology, Psychiatry and Neurology:
Theory, Research, and Practice ISBN 978-1-62100-004-4
Editor: Luciano L'Abate © 2011 Nova Science Publishers, Inc.
Chapter 9
THE USES OF TECHNOLOGY FOR AND WITH
CHILDREN WITH AUTISM SPECTRUM DISORDERS
Olga Solomon
‘Throughout history and everywhere in the present, children live, learn, and play in
homes, streets and other places, using the objects that come to hand and the spaces they inherit
from adults”.
Marta Gutman and Ning De Coninck-Smith
“Designing Modern Childhoods: History, Space and the Material Culture of Children”
Contemporary humans living in post-industrial societies are surrounded by technology
and transformed by it in often-unpredictable ways. Cell phones and iPads have shifted the
ways in which humans use their hands as our opposable thumbs are put to new uses in texting
and video-gaming, and as our index fingers are used to move objects on touch screens of cell
phones, iPads and laptops. At a popular-culture level, an IBM super-computer “Watson”
competes with human experts and wins in a televised game of Jeopardy watched by millions
of the program’s fans. In different guises, from digital medical records to the use of robotics
in surgery to streaming live video in long-distance psychological evaluations, technology has
become part of our lives at work, school and home, and in health care, from diagnosis to
intervention.
This chapter reviews the technological advances relevant to the diagnosis and
interventions for Autism Spectrum Disorders (ASD) that have been developed through the
collaborations of researchers, clinicians, families and the industry, and that are currently used
by practitioners, teachers, and families. The goal of this chapter is to inform the reader about
the technologies used across clinical disciplines and across home, community, clinic, and
school settings, so that practitioners, parents and teachers can gain access to information on
ASD-relevant technologies. This chapter builds upon the recent reviews of technological
advances specific to clinical psychology (Harwood and L’Abate, 2010) and low-cost
approaches to promote physical and mental health (L’Abate, 2007). It also draws upon the
author’s involvement in an Innovative Technology for Autism initiative originally launched
by the Cure Autism Now Foundation and continued by the Autism Speaks Foundation, the

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largest parent advocacy non-profit foundation in the United States to support autism research
(see Goodwin, 2008).
There are two related domains of technological innovation designed to address the
complex and varied needs of children with Autism Spectrum Disorders (ASD) and their
families. The first domain is related to the use of technology to facilitate timely and
appropriate identification, assessment and diagnosis of ASD, especially when the families’
access to experienced professionals is limited because of scheduling, geographical or socio-
economic constraints; or because family members may find it difficult to describe clinically
relevant autistic symptomatology when speaking with professionals during clinical visits
(Goodwin, 2008).
The second area in which the use of technology has shown promise is the support of
communication, participation and learning for children with ASD. For typically developing
children and children with special needs alike, the use of technology has altered how children
communicate, learn, play and engage in everyday activities. A 9 year old ‘texting’ her friends,
a 10 year old in the middle a busy airport speaking on the cell phone, or a 13 year old with a
Face Book or MySpace account have become familiar signs of contemporary childhood and
adolescence. While these uses of technology may now seem unremarkable and taken for
granted, they offer unique new resources for participation and engagement of children
diagnosed with ASD who have an interest in technology and a documented proclivity for the
use technological devices (e.g. Gillette, 2003).
ASD: DIAGNOSTIC CHALLENGES IN THE MIDST OF A PUBLIC
HEALTH CRISIS
Autism Spectrum Disorders (ASD) have become an urgent public health concern: an
estimated 1.5 million individuals in the U.S. and tens of millions worldwide are affected by
autism. U.S. government statistics suggest the prevalence of autism is increasing 10-17
percent annually. ASD are currently estimated to affect approximately 1%, or one in 110
children in the United States. The prevalence of ASD is 4 times higher in boys than in girls
and approximately 40% of those affected have an intellectual disability. It is estimated that
about 730,000 individuals between the ages of 0 to 21 have an ASD (Centers for Disease
Control and Prevention, 2009).
The increase in prevalence has been attributed to many factors including changes in
diagnostic criteria and migration from other clinical diagnoses (Byrd, 2003; Fombonne,
2001), however, there is disagreement in the research community about whether the size of
increase in prevalence can be fully accounted for by this migration (e.g. Croen et al., 2002;
Grinker, 2008). Most evidence points to changes in diagnostic practices and improved
recognition and awareness (Fombonne, 2005; Mandell, Stahmer and Brodkin, 2008)
ASD consist of three DSM-IV diagnoses: Autistic Disorder, Asperger’s Disorder, and
Pervasive Developmental Disorder-Not Otherwise Specified (PDD-NOS). At the time of this
writing, while the preparation of the next Diagnostic Statistical Manual, 5th Edition of the
American Psychiatric Association is in progress with several important changes expected,
these three Autism Spectrum Disorders belong to a group of Pervasive Developmental
Disorders that additionally include Childhood Disintegrative Disorder and Rett’s Disorder.

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ASD are expected to manifest in childhood in the first years of life through such
symptoms as impaired social reciprocity, delayed or absent spoken language, and proclivity
for restricted behaviors, interests and activities (APA, 2000). The diagnosis of Autistic
Disorder is made based upon the following criteria:
A. A total of six (or more) items from (1), (2), and (3), with at least two from (1), and
one each from (2) and (3):
(1) qualitative impairment in social interaction, as manifested by at least two of the
following:
(a) marked impairment in the use of multiple nonverbal behaviors such as eye-to-
eye gaze, facial expression, body posture, and gestures to regulate social
interaction
(b) failure to develop peer relationships appropriate to developmental level
(c) a lack of spontaneous seeking to share enjoyment, interests, or achievements
with other people, (e.g., by a lack of showing, bringing, or pointing out objects
of interest to other people)
(d) lack of social or emotional reciprocity
(2) qualitative impairments in communication as manifested by at least one of the
following:
(a) delay in, or total lack of, the development of spoken language (not accompanied
by an attempt to compensate through alternative modes of communication such
as gesture or mime)
(b) in individuals with adequate speech, marked impairment in the ability to initiate
or sustain a conversation with others
(c) stereotyped and repetitive use of language or idiosyncratic language
(d) lack of varied, spontaneous make-believe play or social imitative play
appropriate to developmental level
(3) restricted repetitive and stereotyped patterns of behavior, interests and activities,
as manifested by at least two of the following:
(a) encompassing preoccupation with one or more stereotyped and restricted patterns
of interest that is abnormal either in intensity or focus
(b) apparently inflexible adherence to specific, nonfunctional routines or rituals
(c) stereotyped and repetitive motor mannerisms (e.g hand or finger flapping or
twisting, or complex whole-body movements)
(d) persistent preoccupation with parts of objects
B. Delays or abnormal functioning in at least one of the following areas, with onset
prior to age 3 years: (1) social interaction, (2) language as used in social
communication, or (3) symbolic or imaginative play.
C. The disturbance is not better accounted for by Rett's Disorder or Childhood
Disintegrative Disorder
Table 1. DSM-IV Diagnostic Criteria for Autistic Disorder 299.00 (APA, 2000)

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Characterized by heterogeneity in the range of symptoms and degree of their severity
across affected population, manifestations of ASD also change over the course of an
individual’s lifespan development (Wing, 1996). A popular saying in the autism community
and among some researchers, “If you have met one person with autism, you have met one
person with autism”, attributed to an adult with ASD, author Stephen Shore, highlights the
uniqueness of each affected person’s manifestations and experience of ASD. The
heterogeneity of ASD creates challenges in planning clinical interventions because
understanding a child’s unique individual profile is as important as understanding ASD as a
clinical syndrome (Greenspan and Weeder,1999). Tomchek et al. (2010) provide an overview
(see Table 2) of potentially challenging areas of occupation for individuals with ASD. In the
field of occupational science and occupational therapy, occupations are defined as meaningful
activities that support a person’s health, well-being, and development (AOTA, 2008).
Table 2. Potentially Challenging Areas of Occupation (Tomchek et al., 2010: S126)
Currently, no pathognomonic signs or biomarkers have been specifically associated with
ASD and diagnosis is made based upon the clinical interpretation of a broad spectrum of
observed behavior manifestations using standardized methods of evaluation (Lord and
Spence, 2006). Asperger’s Disorder and PDD-NOS are milder forms of Autistic Disorder. In
Asperger’s Disorder, language development proceeds without delay although the degree to
which language develops in a normative fashion has been questioned (e.g. Landa, 2000). The
diagnosis of PDD-NOS is given when there are insufficient criteria for a diagnosis of Autistic
Disorder or Asperger’s Disorder but many of the symptoms are present.
Evaluation by an experienced clinician remains the best ‘instrument’ for diagnosis of
autism in infants and toddlers (Cox et al., 1999; Lord, 1995). Research suggests that such
expert diagnosis is highly stable and accurate in children as young as 2 years of age (Charman

The Uses of Technology for and with Children with Autism Spectrum Disorders
5
and Baird, 2002; Lord et al., 2006). Access to expert diagnosis, however, presents a
significant challenge to families.
Filipek et al. (2000) identified significant challenges to early diagnosis for children with
ASD. In a survey of 1,300 families, although most parents had serious concerns about their
children’s development by 18 months and sought medical evaluation by age 2, the average
age at diagnosis of autism was about 6 years. Fewer than 10% of the children in the survey
were diagnosed at initial visit; another 10% were either assured that their child “would grow
out of it” or advised to return if their worries persisted. Over 80% of the surveyed families
were referred to another clinician when their children’s mean age was 40 months. At this
second visit, 25% were told “not to worry,” 40% were given a formal diagnosis, and yet
another 25% were referred to a third or fourth professional. Approximately 20% of the
surveyed families reported that they paid privately for an evaluation or had to exert
considerable pressure to obtain a referral. Over 30% of the surveyed parents who were
referred for subsequent third and fourth evaluations reported that the practitioners who
diagnosed their children did not offer any help or information regarding education, therapy, or
referrals to parent support groups. Only about 10% of the parents reported that a clinician
explained their child’s impairments linked to ASD. Almost 50% of the surveyed families
reported that other parents and the school system, rather than the health care professionals,
were the major source of information and assistance over time (Filipek et al., 2000).
Although an ASD diagnosis may be made by an experienced professional based upon
DSM-IV criteria, a reliable diagnosis ideally involves two instruments representing the best
practice for ASD diagnosis: the Autism Diagnostic Observation Schedule (ADOS), a four-
module interactive assessment based upon the level of language development that the child
has achieved (Lord et al., 1989) and the Autism Diagnostic Interview, Revised (ADI-R) a
detailed interview with the caregiver that focuses on details of the child’s development
between the ages of 3 and 4 years (Lord, Rutter and Le Couteur, 1994; Rutter, Le Couteur and
Lord, 2003). While a number of diagnostic instruments, characterized by varied requirements
for training and time of administration, have been developed to identify ASD, it is usually the
case that the instruments requiring more training and certification, and taking longer to
administer such as ADOS and ADI-R, have better reliability and validity than briefer
instruments requiring less training. The Childhood Autism Rating Scale (CARS, Schopler,
1980) for example, is a brief checklist that can be filled out by a clinician using different
kinds of data, from direct observations and parent interviews to medical records. While
CARS does not take a long time to administer nor does it require extensive training and
experience, it also over-identifies children with intellectual disabilities and under-identifies
children with PDD-NOS. Another checklist instrument, the Gilliam Autism Rating Scale
(GARS; Gilliam 1995), is completed by a caregiver, is brief and easy to score and also
requires minimal training of the clinician. Empirical studies on GARS, however, found poor
reliability and validity and under-identification of children with ASD (Lecavalier, 2005;
South et al., 2002; Williams, Atkins and Soles, 2009). Comparative analysis of three widely
used screening instruments for ASD diagnosis in toddlers at high risk indicated that no
instrument or individual item showed satisfying power in discriminating ASD from non-ASD
(Oosterling et al., 2009).
Recent efforts are under way to overcome this challenge by designing rapid and reliable
assessment paradigms that would obviate clinic-based, time-intensive and high-cost
behavioral assessments. Lee et al. (2010) report on the reliability and validity of an Internet-

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based Interactive Autism Network (IAN)-implemented parent survey involving assessments
of verbal children ages 4-17 with an existing diagnosis of ASD. Although there were several
caveats that weaken the generalizability of this study’s results, statistical analysis of accuracy
of an Internet – based parental report within families participating in an ASD-specific autism
registry suggested that it has a high concordance rate with clinic-based best practice
assessments (ADI-R and ADOS). The picture is complex because whether and how
diagnostic instruments are used vary across clinical settings with different eligibility
requirements, as well as across individual clinicians. Although best practice guidelines in
ASD diagnosis have been developed (Filipek et al., 2000; Johnson and Myers, 2007; Lord
and Bishop, 2010), and American Academy of Pediatrics recently recommended that all 18-
and 24-month-olds be screened for autism spectrum disorders (Zwaigenbaum et al., 2009),
most psychologists assessing children for the Department of Developmental Services (DDS)
eligibility who were surveyed in the Hering (2005) study, reported not using best practice
guidelines. The result of this lack of consistency is that different diagnostic practices produce
often-conflicting evaluations, with the rate of agreement by different evaluators for individual
children in one study reported to be only 45% (Williams, Atkins and Stoles, 2009).
Thus, the situation ‘on the ground’ is often a far cry from the recommended best practice
guidelines and parents may receive conflicting diagnoses from different professionals, a
traumatic and confusing experience that adds stress and uncertainty to the lives of children
and families. When the racial and ethnic backgrounds and socio-economic status of the
families enter the picture, it gains an additional level of complexity. For example, population-
level studies strongly indicate an unprecedented scale of health and service disparities in ASD
diagnosis for African American children. Demographic and epidemiological data about the
children’s age at diagnosis and the duration of the diagnostic process indicate that African
American children are 2.6 times less likely than Caucasian children to receive an ASD
diagnosis on their first specialty care visit and to have a much higher probability of being
misdiagnosed with adjustment disorder, conduct disorder or ADHD. A national study of age
of diagnosis correlates in Medicaid-enrolled children with ASD found that socio-demographic
characteristics as well as local healthcare resources and state policies contribute to disparities
in the age of diagnosis (Mandell et al., 2009). Caucasian children entered the mental health
system at an earlier age (6.0 versus 7.1 years, p = .005); however, after adjusting for age, sex,
and time eligible for Medicaid, African American children required more time in treatment
before receiving the diagnosis: African American children receiving Medicaid were
diagnosed on average at 7.9 years of age, 18 months later than Caucasian children on
Medicaid who were diagnosed at 6.3 years (Mandell et al., 2002, 2003, 2006, 2007; Mandell,
Stahmer and Brodkin, 2008; Stahmer and Mandell, 2007). The picture that emerges from
these studies is of systematic delays in diagnosis and challenges to secure appropriate services
once the diagnosis is received. In summary, there is a shortage of professionals trained in
ASD who have the experience and the resources to follow best practice guidelines in
diagnosis and interventions. Because of this shortage, families often have to wait weeks and
even months for an appointment. Even when families are able to secure an appointment with
an experienced clinician, they may have to travel if they live far from major cities
(Oberleitner, 2006). This is an area of urgent need where tele-health and medical information
technologies, combined with sophisticated digital video-capturing, storage and streaming,
offer unique opportunities to families who otherwise may not have access to a high quality
diagnostic evaluation and assessment.

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USE OF TELE-HEALTH IN ASD ASSESSMENT AND INTERVENTION
Tele-health is a technique that uses telecommunication and information technologies to
transfer basic patient information in order to deliver health care services at a distance,
including diagnosis and treatment (Loane and Wootton, 2003). Tele-health technologies, also
called ‘telemedicine’, have been used since the 1990s to increase access to health care in
medically-underserved areas and populations (Office for the Advancement of Telehealth,
2003).
For example, distance writing, an Internet-based computer-mediated psychological
intervention has been used in mental health disciplines for over a decade as a complimentary,
cost-effective way to augment face-to-face ‘talk therapy’, as well as to reach those previously
unreachable through more traditional therapeutic approaches (see L’Abate, 2001). Tele-health
technology has been used to ameliorate geographic and scheduling limitations and bring
health care professionals together with children and families when there are concerns about a
child’s development. Two kinds of tele-health technologies are currently available: 1) Real-
time, synchronous tele-health includes video-conferencing in real-time between a provider
and a patient, or a real-time consultation between providers; 2) Asynchronous, or ‘store-and -
forward’ tele-health is capturing medical information electronically and then forwarding it to
a provider (Stamm, 1998). “Store-and-forward’ has been a tele-health technology of choice
for ASD because it is often difficult to accurately sample symptom-relevant behaviors such as
self-injury, seizures, tantrums or aggression in real time during a tele-health session with a
provider.
Accurate presentation of these behaviors through ‘store-and-forward’ video-imaging
modalities improves providers’ understanding of the child’s challenges in the natural
environments and creates an extensive video-based medical record for diagnosis or follow-up
evaluations, for example, when a medication is prescribed. Grady (2002) found that this type
of patient-provider communication reduced overall stress in the family, and saved time and
financial resources (see also Oberleitner, 2006; Reischl and Oberleitner, 2009).
Figure 1 demonstrates a flow diagram of a strategy developed by Talk Autism, a
communication service shared by organizations to access a common database of resources
and distance learning library (Oberleitner et al., 2006, p. 231). In this diagram, a caregiver
video-records an episode of concern or interest; the video is either mailed conventionally or
electronically transferred to an appropriate health care provider; the provider reviews the
video; the provider responds to the caregiver with recommendations via telephone, letter or e-
mail; the video-recorded episode is archived for future reference.
The use of tele-health for ASD holds promise in a number of clinical disciplines, such as
counseling, neurology, psychiatry, social work, speech and language, occupational therapy,
and physical therapy. The integration of technology and health care, however, has been slow
to develop in mainstream clinical practice, hindered in part by legal, financial, and regulatory
barriers, including ambiguities in third-party reimbursement coverage of tele-health
applications, and concerns about the confidentiality, privacy and security of health
information.

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Figure 1. Flow Diagram of the Use of Tele-health for ASD (Oberleitner et al. 2006, p.
231)
To overcome the challenges in provider acceptance, third-party payer reimbursement and
liability, the tele-health community must demonstrate this technology’s efficacy and produce
cost effectiveness data through high-quality, peer-reviewed clinical studies. A report by the
Office of Technology Policy (2004) recommends that to overcome these challenges, “tele-
health suppliers (manufacturers and services firms), providers (clinics and clinicians), payers
(third party insurers), and other stakeholders must be prepared to work together to address a
wide array of needs, issues and opportunities” (p.10). Additionally, rigorous cost-benefit and
business case analyses are necessary to justify public funding for developing mainstream
applications for tele-health.
USE OF UBIQUITOUS COMPUTING FOR BEHAVIOR IMAGING IN ASD
Behavior Imaging® technology has emerged to meet the needs of families and
practitioners for an accurate and systematic integration of behavior information with health
records in the ASD diagnosis and intervention. The goal of this field is to make an impact on
ASD-related health care industry similar to other ‘imaging’ techniques such as X-Rays, MRIs
and CT scans (Oberleitner et al., 2010). Parents and other caregivers often report the need to
record, store, and analyze video data about their children with ASD to make it available to
health care professionals (Hayes et al., 2004).

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The usefulness of behavior imaging technologies depends not only on the clinical skills
and expertise of the practitioners but also upon the availability of high quality, extensive
video data that captures clinically relevant behavior. Moreover, personal health records that
document clinical history and that are synchronized with the behavioral video data must be
made available to clinicians to assist in long-distance functional assessment. Finally, these
synchronized data streams should be available for marking and sharing among individual
clinicians and their interdisciplinary teams. Such marking and sharing may include ‘tagging’,
or classifying / categorizing certain segments or points in the video, assembling them in
clinically meaningful sub-corpora or collections, and having long-distance, internet-based,
secure access in order to work collaboratively on the interpretation of these data.
But how are such streams of data created? The technological complexity of this process
ranges from a digital video-recording of a child’s behavior carried out by a family member to
a sophisticated, automated capture system that is part of a built-in home environment. Hayes
et al. (2004) report on the development of a technologically sophisticated automated capture
system used for collecting data on activities that are part of interventions for children with
ASD and for keeping records about these activities. An important part of this process was
defining what kinds of intervention data will be captured because different individuals in
different locations, both professionals and family members, may be administering and
monitoring interventions. The automated capture system allowed to document which team
member was providing which intervention, how these professionals or family members
communicated with one another, and what kinds of records or assessments they were
administering. Essentially, the capture system made it possible for family members and
professionals to visually show what they did with the child with ASD, and how the child
responded, rather than trying to describe it. Hayes et al. (ibid) identified three discreet types
of information: 1) duration, or how long the child was engaged in an activity, and whether the
activity was appropriate; 2) performance, or how often the child responded to a question or a
direction in an appropriate way; and 3) written narrative description of the child’s behavior.
An example of the automated capture and access system (Hayes, 2004) is Abaris designed at
the Georgia Institute of Technology by Gregory Abowd, the Distinguished Professor at the
School of Interactive Computing and Executive Director of the Health Systems Institute. The
purpose of Abaris is to document Discreet Trial Training (DTT) intervention where a team of
therapists takes turns working with a child for approximately 2 to 3 hours a day every day,
which involves completing hundreds of trials per session. Before the automated capture
system was available, in the end of the session each therapist was expected to manually add
up the data, calculate the percentages of successfully completed trials, create graphs that
reflect progress and write narrative notes, a task that was both difficult and time-consuming.
Abaris automated this process by capturing and integrating the individual therapist’s data with
the video of the session. Rather than using a pen and pencil, therapists use a tablet PC and
specially designed electronic forms (called CareLogs) to enter the data. Summary statistics
are automatically calculated and then are available for graphing.
Reflecting its dual function, capture and access, Abaris consists of two parts located on
the same computer: one part for capture, or recording of data, and another for its access and
analysis. Other components include a web cam for capturing video and audio, a wireless
microphone for voice recognition, and a digital pen for writing on specially printed paper.
The structure of Abaris is reflected in Figure 2:

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Figure 2. Components of the Abaris system (Klientz et al., 2005)
To make automated capture more extensive and continuous, whole home environments
have been adapted to integrate data capture systems. Georgia Tech’s Aware Home project
(Klentz et al., 2008), part of the university’s Aware Home research initiative, is a three story,
5040 square feet home that functions as a laboratory for the interdisciplinary design of
technology, its development and evaluation. Automated capture and access technologies like
Abaris can be useful in the early detection of autism, enhancing collaborations among
families, health care professionals and teachers, and making systematically collected, high
quality data available for research on ASD (Klentz et al., 2007). One of Aware Home
project’s most recent innovations is “Social Mirrors”, an environment-embedded social
networking system to support adults with ASD wanting to live independently (Gregory
Abowd, personal communication, March 29, 2011).
USE OF TECHNOLOGY TO SUPPORT COMMUNICATION,
PARTICIPATION AND LEARNING OF CHILDREN WITH ASD
There is growing interest in technology-based interventions for children with ASD.
Practitioners working with children with ASD and their families will be more clinically
effective when they have a deep understanding of the technologies used by their clients and
the meaning these technologies have for them. In the second part of this chapter the
discussion will turn to how technology is used to enhance communication, learning and
participation of children with ASD. This is an area much discussed in the popular media;
however, the analytic intersection of ‘technology’, ‘childhood’ and ‘autism’ present both
challenges and opportunities. The challenges lie, on one hand, in romanticizing technology as
a magically omnipotent, uniformly accessible tool that identifies and alleviates impairments
imposed by autism and by doing so fundamentally transforms the lives of children and their
families.
On the other hand, there is a danger in not appreciating this powerfully transformative
tool enough, especially in post-industrial “knowledge societies” of the Internet Age where
being computer- and digitally-literate is on par with traditionally defined literacy
(Organization for Economic Co-operation and Development, 2001). The solution to this
quandary lies perhaps in paying careful attention to how technology, childhood and autism

The Uses of Technology for and with Children with Autism Spectrum Disorders
11
intersect in a realm of what anthropologist George Marcus (1995) calls “the imaginary”, an
orientation to imagining futures that arises out of technology and scientific practice being
both imaginative and visionary (p. 4).
Especially in clinical settings, where practitioners and family members collaborate in
carrying out interventions that ‘emplot’ desirable, hoped-for futures (Mattingly, 1998), there
is tension between technology’s potential and the reality of people’s everyday lives. The
tension lies between technology, especially its Internet-based varieties, as a tool for preparing
young people for participation in the ‘knowledge economy’ (Hargreaves, 2003) and
technology as a mediator of universal literacy in the context of globalization. As Moss (2008)
writes, “Even in our discussions about computer technologies and digital literacies, the ideal
norm and what is real can be far apart. In the ideal, the Internet, specifically the World Wide
Web, has provided a means for cultures to participate in crosscultural communications.
Digital technologies bring the global world to the most remote villages, making the world
smaller. Presumably, this global world has an impact on community or vernacular literacies
as this contact with the wider world increases. Yet, unequal access resulting in a digital divide
is still a reality. Material resources, or lack thereof, continue to contribute to who has power
and who does not. Also, while digital technologies expand our definitions of writing, there is
still a tension about what kind of writing will prepare our young people to be able to succeed
in a technologically sophisticated, global society. What kinds of writing and other literacies
should be valued is still a question” (p. 562-563).
Considering the barriers to how information is created, exchanged and used via various
technologies in communities around the world, Hawisher and Selfe (2000) decry the myth of
a ‘global village’ perpetuated mostly in the U.S. and in other post-industrial societies by the
view of the Internet and World Wide Web as a “global literacy environment in which peoples
from all over the world can communicate with one another without significant barriers posed
by geopolitical location, language, culture, and everyday practices and attitudes” (p. 2), or as
in case of autism, by all of the above plus the communicative challenges posed by a
developmental disorder that impacts the very ability to communicate (see also Warschauer,
2004). Another challenge lies in recognizing the practices of identifying and understanding
autism itself: a highly heterogeneous, developmentally variable phenomenon that is both
clinical and socio-cultural (Solomon, 2010). In considering how technology is used for and
with children, including children diagnosed with ASD, there is a need to acknowledge that
institutional setting in which the children are participants are organized by ideologies
regarding the uses of technology as well as by local notions of competence, achievement, and
development (e.g. Mehan, 1996). These institutional ideologies are reproduced and ratified
through situated practices, whether these institutions are hospitals and clinics, schools, after-
school care programs or online communities. Another analytic hurdle is a representation of
children in post-industrial societies as passive users and consumers of technology. There is a
lament about “a new type of child” who is a “technologically astute, information-loaded and
brand-literate product of advanced consumer culture” (Lindstrome and Seybold, 2003, cf
Clarke, 2008). A less pessimistic view is that children and families incorporate technologies
into their lives and by doing so, transform them in sometimes unpredictable and paradoxical
ways. In a related discussion about mass media as exemplified by Disney cultural products,
and its interpretive, assimilating consumption (Certeau, 1984) by children and families,
Mattingly (2006) writes:
“The power of mass media to shape cultural identities has also been a topic of central

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concern within contemporary culture theory. Stuart Hall, for example, has argued that mass
media is a primary vehicle for ideological production, a means through which groups
construct images of their lives (Hall 1997). Mass media might be colonizing but ethnographic
studies of the actual practices of cultural production and reception help to complicate the
picture of media as ideology machine. Such studies reveal the way that the global is made
“local” in specific contexts and show that the meaning of a media text is not given by the text
itself but by the processes through which it is taken up and consumed by particular
interpretive communities (Abu-Lughod 1991; Metcalf 2001; Rapp and Ginsburg 2001).
Reception theories in media studies have been at pains to argue that meaning is a complex
and local practice of negotiation between the world of the text and the world of the audience.
It is a historically particular and local invention (see Spitulnik 1993 for a review of this
literature). In other words, the audience does not merely consume, it “poaches,” as Michel de
Certeau (1984) puts it, helping to construct meaning through its practices of consumption” (p.
498).
Thus, there is a need for an ethnographically informed, person-centered examination of
the situated practices and ideologies of the uses of technology for and with children with
ASD, as well as its geo-political, economic and user-centered accessibility. In this sense, the
‘social life’ of technology, to paraphrase Appadurai (1986), has to be part of the analytic
picture. Similarly to Georg Simmel’s conceptualization of ‘economic objects’ (1907/1978, cf
Appadurai 1986), the ‘social life’ of technology for children with ASD involves
understanding its value not as its inherent property but rather a property assigned to it by
subjects - be they the children themselves, their family members, teachers, or clinicians - who
are guided by their own subjectivities in a space between desire and enjoyment, “which is a
distance that can be overcome” (Appadurai 1986: 3). The tension that exists in this space is
worth considering because it tells us about the practical logics that guide how technology is
used for and with children with ASD in the first place, what the underlying practical
reasoning is behind its use, and what possible and imagined futures are “emplotted”
(Mattinlgy, 1998) in the process. In the very least, this space can tell us about the newly
visible potentialities and competencies that the uses of technology afford to children, families,
clinicians who are part of the children’s lifeworlds.
The uses of technology for and with children with ASD also foreground the materiality of
human bodies in social life. Philosopher Judith Butler (1993) interrogates the processes of
‘construction’ of a gendered body, asking questions that may be relevant to understanding the
place of technology in the lives of children with ASD and their families: ”What are we to
make of constructions without which we would not be able to think, to live, to make sense of
it all, those that have acquired for us a kind of necessity? Are certain constructions of the
body constitutive in this sense: that we could not operate without them, that without them
there would be no “I”, no “we”? Thinking of the body as constructed demands a re-thinking
of the meaning of construction itself”. (p. xi) These questions suggest a view of the uses of
technology as constructing a certain kind of a human being where materiality of the body and
the materiality of technology exist in a constitutive relationship, making an ‘unintelligible’
and ‘unlivable’ body ‘intelligible’ to others and ‘livable’ for self. There are several example
of such ontological flexibility afforded by technology. In the field of Socially Assistive
Robotics, socially intelligent robots engage in contingent social interaction with children with
ASD and their family members, thus supporting communication among human participants
(Dautenhahn, 2003; Feil-Seifer and Mataric, 2005, 2008). In the field of Virtual Reality,

The Uses of Technology for and with Children with Autism Spectrum Disorders
13
Embodied Conversational Agents also called “Virtual Peers” engage children with autism in
interpersonal relationships through collaborative storytelling (Cassell, 2001; Tartaro and
Cassell, 2006, 2008).
In less philosophical terms, technology helps realize the potentialities of children with
ASD as human beings with rich subjectivities, communicative intentions and abilities, and
inner worlds: It quite literally helps ‘construct’ a different kind of being than the child has
been until technology was introduced into his or her lifeworld. The possibility that technology
can have this effect disrupts and problematizes the notion of agency as residing within an
individual, suggesting a more complex agentive relationship between human beings and their
material and semiotic worlds (Barad, 1996, 2007). Some of these themes can be heard in
parental narratives about how their children with ASD engage with technology. Consider, for
example, a story told around Christmas time by a mother of a four-year old boy diagnosed
with ASD; at the time this story was told, the boy’s verbal communication has been limited to
only a few words1. The narrative is shared with a group of family members of children with
ASD that meets as part of an ethnographic study on health and service disparities in ASD
diagnosis for African American children. The group is mediated by two researchers.
Mother: He knows that Santa is coming and is going to bring him something. And the
funny thing, we were asking, what do you want, what do you want and he says, "Ipad, Ipad."
(laughs) Because he plays with my husband's Ipad and he can-, he's great with computers you
know. He may not be able to speak really well, but he can navigate the Ipad, he can
download, he knows how to go to websites to download the games and applications that he
wants and he can stay on it for hours, so that- I mean-, his preschool teacher sent us an article
about a child with autism who found their niche with an Ipad, and I said well I can relate to
that because my son can spend hours upon hours on the Ipad. Like this is mine, I have it. And
I bought some computer software for him, so he plays this Blue’s Clues computer game for
hours. Like last Saturday, it was just the two of us and I was kind of, you know, making some
preparations, so I had the laptop and he stayed on it for 4 hours straight and when I tried to
pull him away, like, "ok it's too long, let's take a break, let's eat," he doesn't want to eat or
anything, he likes technology, so- I think that's good. I mean in some respects, I don't want
him to have too much, but then again, 10,000 hours is the uh, expert level, so, with anything. I
read The Outliers, and that was one of the things that they talk about. Once you reach 10,000
hours doing anything, you become an expert at it. Yeah, Bill Gates, among other people, had
10,000 hours built in, professional athletes, 10,000 hours. So that seems to be benchmark for
mastery of something.
Researcher: So are you keeping track of hours?
Mother: I'm keeping track of his hours, I was like, "ok, we got 4 today, we're on our
way!" (Laughs)
Researcher: Were you surprised with the Ipad?
1This example was selected from a digital video-and audio- data corpus collected for an ethnographic,
interdisciplinary project ‘Autism in Urban Context: Linking Heterogeneity with Health and Service
Disparities’ (1 R01 MH089474-01; NIH / NIMH; Olga Solomon, PI) that examines health and service
disparities in ASD diagnosis for African American children living in urban Los Angeles.

Olga Solomon
14
Mother: Yes! I mean it was almost instant. It took him maybe 20 minutes before he
figured out, "Ok, if I slide my finger across it makes pages move. What if I push this button?"
And he, he figured it out. Meanwhile, I'm still sitting there trying to get onto the Internet and
he's like, "Mommy, let me show you."
Such narratives about families’ experience with technology offer a glimpse of the ways in
which it is used for and with children with ASD. These narratives allow to see how
impairments imposed by ASD are experienced, interpreted and mediated; what theories of
competence and disability are at play; and what socio-cultural practices are improvised and
routinely carried out to manifest certain kinds of technologically expressed selves and
mediated identities.
In this sense, the kinds of technology and the practices of its use offer a unique picture of
ASD from the perspectives of the children, their families and clinicians who work with them.
Such examination illustrates that competence may be as much an attribute of the socio-
cultural and socio-interactional context as of an individual’s mind or body, i.e. the inclusion
of technology in educational and family settings supports, mediates and affords children’s
communicative competencies that otherwise may not be visible.
TYPES OF TECHNOLOGY USED FOR AND WITH CHILDREN WITH ASD
Technological devices used for and with children with ASD may be categorized by the
following six domains of engagement in social interaction that technology mediates (see
Table 3 for examples):
1) Medium of communication. Communication via speech is enhanced by voice
output keyboards; communication via text is enhanced through the use of computer
keyboards, texting on the cell phone, iPads and other text-generating devices.
2) Social ontologies. Ontological properties of interlocutors can be manipulated and
configured favorably, for example, minimizing facial information, in Socially
Assistive Robotics; and by designing Virtual Peers in Virtual Reality environments.
Individuals with ASD also have opportunities of altering their own social identities
through the choice of avatars in Virtual Reality environments, e.g. Second Life.
3) Affect recognition and affect communication. This domain of functioning is
technologically enhanced through affective computing and wireless bio-sensing2
where individuals with autism wear biosensors that make visible their physiological
states such as stress and anxiety.
4) Enhancing participation through auditory and tactile prompting, and
scheduling. Experience of participating in activities with others is enhanced though
auditory and tactile prompting devices that keep an individual with ASD focused and
on task; scheduling devices enhance a sense of predictability of social environments,
promote confidence and decrease anxiety.
2Developed by Affectiva, a company created through the collaboration of researchers at MIT Media Lab and the
technology industry.

The Uses of Technology for and with Children with Autism Spectrum Disorders
15
5) Turn-taking of social interaction. This domain of functioning can be
technologically enhanced via the use of DiamondTouch™ StoryTable, a multi-user
touch and gesture, drag-and-drop device to support small group collaboration, where
children with autism have to coordinate their actions in order to participate in an
enjoyable play activity.
6) Safety-related skills. Several Virtual Reality applications have been developed to
teach safety-related skills such as what to do in the event of a fire, or how to cross a
busy street.
Domain of technological
intervention
Technology and Research
1) Medium of Communication
Voice
Voice out-put communication aids (VOCA) 3
(Gillette, 2003; Mirenda, 2001, 2003)
Writing
Computer keyboards (Heimann, et al., 1995);
e-mail (Burke, and Kraut and Williams, 2010; Benford,
2008)
Cell phones (Durkin et a., 2010; Goldsmith and LeBlank,
2004)
iPads and other tablet PCs
2) Social ontologies
“Other”
Socially Assistive Robotics (Dautenhahn, 2003Feil-Seifer
and Mataric, 2005; 2008)
Virtual Peers (Cassell, 2001; Tartaro and Cassell, 2006,
2008)
CosmoBot™4 (Brisben, Lockerd, and Lathan,2004)
“Self”
Second Life (Boulos, Hetherington and Wheeler, 2007)
3) Affect recognition and
affect communication
Affective Computing, Wireless Bio-sensing Technology
(el Kaliouby et al., 2006; Picard, 2009; Picard and
Goodwin, 2008)
Virtual Reality for training eye gaze skills (Trepagnier et
al., 1998)
4) Enhancing participation
through auditory and tactile
prompting
Tactile and auditory prompting devices5
(Coyle and Cole, 2004; Shabani et al., 2002; Taylor and
Levin, 1998; Taylor, Huges, Richard, Hoch, and Coello,
2004)
through scheduling
Microsoft PowerPoint (Rehfeldt, Kinney, Root, and
Stromer, 2004); Video enhanced activity schedules
(Dauphin, Kinney, and Stromer, 2004); Computer based
activity schedules (Stromer et al., 2006)
5) Turn-taking of social
interaction
StoryTable system based on DiamondTouch (Bauminger
et al., 2007)
6) Safety-related skills
Do2Learn Virtual reality application (Strickland, 1997;
Strickland et al, 1996; Rizzo, Strickland and Bouchard,
2004)
Table 3. Examples of technologies and supporting research across six domains
3Developed by Archimedes Access and Research and Technology, Inc.
4Developed by Anthrotronics, is a patented interactive robotic system designed to enhance development of children
with special needs including ASD.
5Developed by Follow Through Inc., 2003; JTECH Communications Inc., 2004

Olga Solomon
16
Such a domain-based approach contributes to the existing reviews on the uses of
technology for individuals with ASD. Goldsmith and LeBlank (2004), for example, review
five types of technology used as a temporary instructional aid: 1) tactile and auditory
prompting devices; 2) video-based instruction and feedback, 3) computer-aided instruction, 4)
virtual reality, and 5) robotics. Other categories that differentiate the uses of technology for
ASD include assistive technologies; alternative and augmentative communication systems,
designed either to supplement (i.e., augment) children’s existing speech or to act as a primary
(i.e., alternative) method of expressive communication; voice output communication aides
(VOCA); interactive games; educational software; affective computing; online communities;
ubiquitous computing; wireless bio-sensing; user-centered collaborative design processes; and
product assessment (see also Gillette, 2003; Gillette et al., 2007; Goldsmith and LeBlank,
2004; Goodwin, 2008 for reviews).
CHALLENGES AND PROMISES OF TECHNOLOGY IN CLINICAL
PRACTICE
While there is a sense of excitement about the possibilities of the use of technology for
and with children with ASD, there remain serious challenges to bridging development,
research and practice. Kimbal and Smith (2007) review the challenges related to computer
technology use and conclude that work needs to be done in crossing the bridge from research
to practice and in transforming promising and sound experimental findings into effective,
affordable, and readily available technological products. Until the bridge from research to
practice is crossed, the task of integrating the technology into clinical or educational practice
rests primarily on the shoulders of families and practitioners rather than developers and
researchers. Even though there is strong empirical support for the use of some technologies
with children with ASD, there are not enough ‘ready to use’ applications that provide logistic
feasibility for the use in clinical, educational settings (McConnell, 2002).
On the other hand, there may be an advantage to the absence of ready-made prescriptions
on how to use the multiplicity of technological devices presently on the market. As Goldsmith
and LeBlanc (2004) point out, PDA’s, cell phones, laptops, and MP3 players have entered
mainstream society and are becoming more and more affordable. A child with ASD using an
iPad or a cell phone for prompting or scheduling will look indistinguishable from the
neurotypical others using these devices. The task of the clinician is to find ways to adapt these
devices into a technologically enhanced clinical practice.
ACKNOWLEDGMENT
The author wishes to thank the following individuals who have been members of the
Innovative Technology for Autism Advisory Board: Gregory Abowd, Katarina Boser
Danielle Gillette, Matthew Goodwin, and Albert (Skip) Rizzo. A special thank you to Portia
Iversen who first initiated this initiative as part of the Cure Autism Now foundation’s area of
research. Others whose research has contributed to the author’s on-going commitment to the

The Uses of Technology for and with Children with Autism Spectrum Disorders
17
study of technology for and with individuals with ASD are: Justine Cassell, Sharon Cermak,
David Feil-Seifer, Gillian Hayes, Julie Kienz, Mary Lawlor, Maja Mataric, and Elinor Ochs.
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