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Explanations of Savantism in Autistic Individuals (Part 3)

January 13th, 2011 Comments off

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Brunswick (2001) attests to this idea that autistic individuals are completely shut off from the world, and it is this isolation that motivates a select few to become absorbed into a particular field as a means of connecting with the world. Babies with autism appear to be developing normally until the age of two when social learning begins to contribute increasingly to the cognitive development of the children in question. Most of this learning takes place through processes of teaching by a caregiver and spontaneous imitation on the part of the toddler. However, because as autistic children gain greater knowledge of the physical world, their appreciation and discernment of human interaction fails to keep pace, and as a result, they are inclined to ignore other humans in favor of inanimate objects, to which they becoming increasingly attached. Data has verified this assertion when it was discovered that autistic individuals out perform the typically developing controls in the Wechsler Block Design Test, demonstrating the advantage that autistic participants have evolved through their “enhanced ability to mentally segment designs into their constituent parts. ” (Heavey et al. 1999, p. 146). It has been discovered that savants are more likely to engage in repetitious behaviors and among those with autism, the savants were more likely to possess one single interest, showing more obsessional attitudes towards their ability. Additionally, savant skills can be found in individuals where autism is not diagnosed. Therefore, it is more logical to conclude that an internal concentration on the skills rather than a biological predisposition determined by this disorder is at play

To counteract the claims pertaining to IQ and the ability of savant individuals to overcome such low general intelligence by biological function to achieve such great abilities, one must explore the biological explanation of IQ that Anderson (1998) cites. In his explanation, IQ is determined by the speed of neural conductivity within the brain, operating on the principle that knowledge is not the equivalent of intelligence to explain savantism. Further evidence goes on to argue that inspection time (IT) tasks provide the best calculable scale of speed processing, necessitating that participants make simple discriminations between two or more pieces of data (Scheuffgen, Happe, Anderson Firth, 2000). It has been found that the autistic group had the same inspection time as did normally developing individuals, regardless of the large gaps in IQ scores between each group, providing evidence that the modern IQ tests are not accurate in determining an individual’s true intelligence and ability.

The strong hereditary evidence suggesting that a much higher percentage of autistic individuals possess certain skills than the rest of the general population is a potent claim. However, knowing that not every savant is diagnosed with autism believes me to think that there is another factor involved, such as motivation, in addition to any biological evidence of predisposition. Also, with the discovery and understanding of a new, more practical IQ test that assesses inspection time, it appears that autistic individuals are more like normally developing people than was previously considered, providing strong evidence that in fact, these abilities are present because the autistic savant works towards them rather than has a mystical biological inclination towards them. Due to the feelings of isolation overall and the already predisposition for children and adults with autism to act in repetitive and often compulsive obsessional ways, that despite any evidence of increased blood flow and regional activity in the brain, savants possess their skills as a result of persistent focus and motivation, mostly excluding biological factors.

References

Anderson, Mike. (1998). Mental retardation general intelligence and modularity.

Learning and Individual Differences, 10, 1-9.

Brown, Walter A. Cammuso, K. Sachs, H. Winklosky, B. Mullane, J. Bernier, R.

Svenson, S. Arin, D. Rosen-Sheidley, B. Folstein, S. (2003). Autism-related

language, personality, and cognition in people with absolute pitch: Results of a preliminary study. Journal of Autism and Developmental Disorders, 33, 163-167.

Brunswick, Natheniel L. (2001). Social learning and etiology of autism. New

Ideas in Psychology, 19, 49-75.

Heavey, L. Pring, L. Hermelin, B. (1999). A date to remember: The nature of

memory in savant calendrical calculators. Psychological Medicine, 29, 145-160.

Miller, Leon K. (1999). The savant syndrome: Intellectual impairment and exceptional

skill. Psychological Bulletin, 125, 31-46.

Scheuffgen, K. Happe, F. Anderson, M. Firth, U. (2000). High “intelligence,” low

“IQ”? Speed processing and measured IQ in children with autism.

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Explanations of Savantism in Autistic Individuals (Part 4)

January 13th, 2011 Comments off

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Development and Psychopathology, 12, 83-90.

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Explanations of Savantism in Autistic Individuals

January 13th, 2011 Comments off

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Autism, a severe and incapacitating developmental disorder of brain function affects social and communication skills of a growing child and thus theoretically hinders the learning process, although a surprising number of autistic individuals excel in specific areas, an occurrence that psychologists struggle to explain. Individuals with autism often exhibit similar characteristics including: lack of eye contact; usual attachment to objects rather than people; preference to repetitive activity; delayed or unusual acquisition of language; social naiveté; and the exceptional ability in one or more specific area. Incidence in these exceptional abilities, savant skills, is defined according to the 1973 American Association of Mental Retardation as “a person with low general intelligence who posses an unusually high skill in some special tasks like mental arithmetic, remembering dates or numbers, or in performing other rote tasks at a remarkably high level. ” (Miller, 1999, p. 31). The most common types of savant abilities are in the areas of visual arts, particularly drawing, musical performance, calendar calculating and prime number derivation. Throughout the past two hundred years, occasionally the emergence of an outstanding skill in a person possessing a mental disability has been documented, thus warranting much speculation to the basis of these rare and seemingly out of place abilities.

It is possible that the extreme focus and social seclusion of these individuals compel them to seek out an area of interest to occupy their mental capacities, and thus through practice and concentrated attention on this one subject area, adapt a supreme and specific ability in this chosen field. This is a main theory posted by mainstream textbooks, but there exists another explanation that I wish to explore in evaluating the sources of savant skills in autism spectrum disorders.

According to some mainstream textbooks, savant skills have an origin in a special form of cognitive function that only autistic individuals possess. Although the reference contains only a few sentences pertaining to this theory of cognition, in an attempt to unearth an accurate basis for savant skills, it is a worthy conjecture to explore. With supporting evidence from a wide scope of other articles pertaining to psychological studies, an article by Leon K. Miller, “The Savant Syndrome: Intellectual Impairment and Exceptional Skill” serves as a main source for information on this speculation. A strong link between autism and remarkable natural abilities implies a biological factor. Reports of the high prevalence of absolute pitch in savantism (15%) as compared to that of the general population 05-. 01%) also indicates a possible biological principle that allows such ability. In a brain scan of autistic savants with absolute pitch, there is a marked increase of blood flow to the cerebellum while listening to music in comparison to non-savantists (Brown, Cammuso, Sachs, Winklosky, Mullane, Bernier, Svenson, Arin, Rosen-Sheidley, Folstein, 2003). In keeping with this theory, the examination of five thousand, four hundred autistic children, produced data that exceptional skills were cited by parents in approximately ten percent of the sample (Miller, 1999).

In Miller’s (1999) understanding of savantism, the exceptional memory that such subjects possess is most likely the reflection of a domain-specific organization in the brain, rather than enhanced skills gained through repetitive, focused learning. Some features of savants are consistent with an attribution model that suggests a differentiation in function of brain hemispheres, thus providing a specific hypothesis to this biological theory. People with autism have obvious trouble with language and verbal skills associated with the left hemisphere creating a “consequence of right hemisphere flourish. ” (Miller, 1999, p. 35). Mathematical calculations, spatial representations, and musical and artistic abilities are associated with this right hemisphere of the brain. Strong evidence for this right hemisphere reliance also includes the fact that a far larger percentage of savants are left handed than the general population (Miller, 1999). An alternate conjecture to the hemispherical approach is that autistic savants possess numerous localities in the brain for greater pathological development of temporal and parietal (both relating to spatial orientation, bodily acclimation, such as temperature and touch, and visual and auditory input) polysensory (Miller, 1999).

Duckett (1976, as cited in Miller, 1999) has demonstrated in numerous studies that savants have stronger capabilities in several memory and creative test measurements than controls matched on age, gender, and general level of intellectual functioning, indicating that savants may be able to learn more easily than their non-gifted autistic counterparts.

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Explanations of Savantism in Autistic Individuals (Part 2)

January 13th, 2011 Comments off

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Surprisingly, savant skills have been discovered in subjects who were virtually untestable by standard methods. Nadia, a woman described in Miller’s (1999) article, exhibited an extremely talented ability in drawing, yet her expressive language was restricted to just a few phrases and typical evaluation instruments placed her performance at near floor level. Such findings distinguish a difference between actual generalized intelligence and the abilities as supported biologically of savants.

Psychologists agreeing with Miller’s proposal believe that autistic individuals have limited skill expression, revealing constraints on their cognitions. The inability of savants to express and describe their own processes of drawing, musical performance, or calendar calculation also provides evidence that savants do not have a remarkable understanding of their abilities, but instead inherently possess them through biological characteristics of the brain. Adults and children with autism do not have the social function to know how to describe such events, but this trait is also displayed by protégés without a mental disability. Highly practiced skills, for example, may become so automatic and routine in typically developing individuals that they are also unable to describe these processes. The actual concept of language itself and the structure it requires to make sense in vocalization may interfere with the preservation of detailed information about a particular event or situation, as language disorders have been found to be very common in savantism (Miller, 1999).

Many studies have been conducted to determine exactly how much understanding savants have of their own abilities and the methods in which they utilize in their talents. The ability to formulate a specific day of the week on a mental calendar may be an exceptional skill, however, it is atypical and, therefore, a difficult skill to compare against sample groups without a disability (Miller, 1999). It is suggested that people with autism who display an uncharacteristic ability in calendar computations have a very rudimentary knowledge of mathematics (Miller, 1999). While Heavey, Pring, and Hermelin (1999) insist that formulas and algorithms exist in published format for the calculation of dates, they perceive it to be highly unlikely that the learning-disabled savants would be able to access, read, and synthesize these mathematical components. A strong short-term memory is also essential in manipulating the computation of calendar dates, which concurs with the findings in a 1973 study by Spitz and LaFontaine that savants have superior short-term memory in comparison to controls with developmental delays (Heavey, Pring, Hermelin). Additionally, when asked to reproduce a piece of art, autistic individuals with such savant abilities created sketches that were not literal copies of the original, but instead more often adapted another perspective on the original artwork, bringing in outside sources of knowledge. This example functions to provide evidence that these people are capable of thinking through a process of replication instead of merely producing an exact copy (Miller 1999). Similar to the findings in artist abilities, Miller (1999) also discovered through his research that immediate recall of musical fragments by savants is “not a literal reproduction of the material heard, (but rather) participants’ renditions preserved essential musical structural regularities present in the original. ” (p. 42). Through examples and theories stated by Miller and others, there exists a strong possibility that savants have a biological tendency to excel at specific tasks, contrasting with my assumptions that much of their abilities are learned through focused study.

Many of the arguments posed by Miller and others seem to be convincing, but much of the supporting evidence of their theories seems vague and hypothetical without practical knowledge of the day-to-day behaviors of autistic individuals Autistic savants may be predisposed to certain categories of abilities that are controlled by the right hemisphere of the brain, but these cannot develop without sufficient attention. Anderson (1998) has found significant data in a series of MRIs conducted in autistic individuals, concluding that there is no structural difference in the activities of each hemisphere at any given time in autistic savants. Bilateral processing is utilized most often by nearly every function of the body, and therefore, although one side may represent a stronger presence over the other, the latter side must also be relatively high functioning (Anderson, 1998).

People with autism spectrum disorders can become obsessed and narrowly focused on one particular subject of interest, as they are motivated to concentrate on a specified goal in response to the social and environmental deprivation, leading to attentional development and extensive practice of this new skill (Anderson, 1998).

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Understanding Self-Injurious Behavior in Adolescents and Young Adults and its Remedies

July 6th, 2010 No comments

Self-injury is defined as "A deliberate, intentional injury to one’s own body that causes tissue damage or leaves marks for more than a few minutes which is done to cope with an overwhelming or distressing situation” (Cutter, Jaffe & Segal, 2008). Methods of self-injury vary from person to person, but the most common form of self-injury is by cutting. By using a sharp object such as a razor blade, self-inflicted cuts are made on the skin. Other types of self-injury include, but are not limited to, the act of self burning , excessive picking at healing wounds, pulling out hair, and digging nails into the skin. “Although cutting is one of the most common and well documented forms, over sixteen forms have been documented”(Whitlock, Eckenrode, & Silverman, 2006 ). When most people cut themselves, there is often a ritualistic aspect involved. This can be in where they hurt themselves on their body (ie. on the underside of their arms, or their stomach) the environment in which they choose to hurt themselves (ie. a bathroom, or bedroom) or the time of day in which they most often will self-injure. The individual may choose to play certain music during the time they are hurting themselves. Many even clean their tools a certain way before and after hurting themselves. After they hurt themselves, the individual will often bandage it a specific way, write about it in a journal or possibly, just go to sleep. The act of cutting oneself can become just as ritualistic and necessary to the individual as brushing their teeth or cleaning their room. At some points, those who self-harm may need to self-harm, but is not in a safe environment to do so, or does not have their tools on hand. When this occurs, they will often find an alternative place to cut themselves, such as a bathroom stall. They will use a different object to hurt themselves, such as a safety pin or push-pin, and they will skip their ritualistic procedure all together (Alderman, 1997).

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TRAINing to Read: A Cognitive Tutor for Children with Mental Retardation

June 24th, 2010 Comments off

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According to Kame’enui and Wallin (2006), defining features of children identified as having special needs include significant deficits in their reading development and performance. Approximately 78% of children with moderate mental retardation (IQs between 50-69) are able to learn to read, according to one study, and all children can learn to read when their IQs are 70 or above following the appropriate intervention (Mervis, 2009).

Unfortunately, due to state and nationwide budget cuts, special education classrooms for children with a wide range of abilities are overflowing, leaving overextended teachers unable to provide the one-on-one attention necessary in literacy development. For this reason, a specialized cognitive tutor, the TRAINing to Read (TTR) program should be developed to supplement traditional reading instruction. This new system follows three important caveats (1) ease of use; (2) scalability; and (3) cost effectiveness, providing applicability for both home and school use. Moreover, it will provide customization based on individual student ability and reduce the required student to teacher ratio in special education classrooms.

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Why Develop a Computerized Literacy Program?

Although the adoption of computer technology for individuals with mental retardation has lagged behind its usage in business, government, and typically developing educational applications, computers are increasingly empowering individuals with mental retardation to enjoy more independently lives. The ability to read a list of tasks and self-regulate time management can be essential for individuals with mental retardation to hold meaningful employment. Davies et al. (2002) used a portable schedule prompting system loaded onto a Palm Pilot to determine the efficacy of scheduling software to increase independence. In this study, as well as the next by Davies et al. (2003), computer applications were significantly more effective in obtaining and maintaining independent living skills.

Software in Davies et al. (2003)’s study provided adults with mental retardation a means of tracking their personal checking accounts by storing and retrieving common payees, automatically balancing accounts, and posting checks to the register. Results from Davies et al. (2003)’s within-subjects experimental design indicated that using accounting software significantly reduced the errors by users with mental retardation when compared to traditional checking by hand (p < 001), (Davies et al. 2003). Perhaps the use of literacy software will also reduce error production by children with mental retardation without direct adult supervision.

Not only have computer programs been implicated in adult independent living skills, but they are also being adapted to special educational applications for children with mental retardation. In Ortega-Tudela et al. (2006)’s, two groups of children with Down syndrome were trained to perform mathematical skills; One group used multimedia software and the other performed traditional pencil and paper practice examples. While the authors suggest that simply working with a computer does not produce learning, individuals with Down syndrome in the computer program use group performed significantly better than their pencil and paper peers in the tested mathematical ability. Ortega-Tudela et al. (2006) propose that computer software provides the tools necessary to learn abstract concepts that were once thought impossible for individuals with Down syndrome to develop. Although evidence suggests that computer programs have been applied to teaching basic academic and independent living skills to individuals with mental retardation, the complex task of reading instruction has not been attempted in the available literature.

Computer applications provide unique methods to teach children who learn at individualized rates. Davies and Hastings (2003) argue that virtual environments are appropriate learning tools for individuals with mental retardation because of two of their inherent properties: (1) they provide opportunities for learners with mental retardation to make mistakes without fear of humiliation, and (2) programmers can manipulate virtual learning technologies in ways that they are unable to in the real world. Stories can literally come alive when teaching children to read when imagination is limited by the burdensome act of first sounding out individual words and conceptualizing them into a meaningful sentence.

Computers in the classroom offer a versatile instrument from which to introduce educational skills that are both compelling and entertaining to elementary school aged children of all cognitive abilities by operating colorful displays, interactive features, and immediate feedback. Programs like CompSkills provide self-pace, self-directed computer-generated prompting to guide a series of computer training tasks such as mouse operation and typing on a keyboard (Davies et. al, 2004). According to these findings, computer-based education for children with mental retardation provides a new frontier for intelligent tutors in the context of literacy learning. As such, CompSkills style training tasks will be an important facet to preparing children to learn early reading strategies on the computer. To perform well on the TTR module, children must be proficient in basic computer skills, many of which they have acquired through similar CompSkills programs or leisurely gaming.

Intelligent Tutors: Teaching Literacy Skills to Children with Mental Retardation

Now that we have evaluated the effectiveness of computer applications for teaching individuals with mental retardation, the preliminary overall structure of the proposed computer program should be established. The design must incorporate both model tracing, described by Koedinger et al. (1997) as a process in which student’s actions are continually compared against those that the model might generate, and knowledge tracing, which monitors student learning across all problems (Koedinger et al. 1997). An intelligent tutoring system would meet these criteria, as well as provide an external representation for students with mental retardation to demonstrate their reasoning steps in problem solving (Crowley et al. 2007) so that identification of mistake patterns could be recognized and corrected immediately. A computer program may offer corrections to mistake patterns on screen or alert a classroom teacher to the difficulty experienced by the student so that the teacher may intervene.

Moreover, Antshel et al. (2009), find that for children with hyperlexia, described as characteristically capable of decoding text but unable to comprehend its meaning, executive functioning skills are crucial to eventual success in reading. Cognitive based tutors provide children access to their own thought processes because they are able to trace the reasoning of their previous actions, fulfilling an important need among many children with mental retardation, not just those with a hyperlexia diagnoses. Awareness of metacognition will be beneficial across all fields for children with mental retardation, not just those particularly relevant to education.

A final deciding factor in the use of the computerized intelligent tutor design concerns the ease of use and intrinsically rewarding nature of the steps which serve to motivate previously uninterested learners. As a whole, cognitive tutors reduce frustration and provide children pride in a completed goal (Koedinger et al. 1997). Soares et al. (2009) determined that for children with autism, self-monitoring of their own activity completion reduced rates of maladaptive behaviors including self-injury and tantrums. Self-monitoring through means of a cognitive tutor can train children with mental retardation to recognize and track their own behavior.

Implicit learning through observation of one’s own behaviors is essential to successful learning by cognitive tutors, especially for a complex task such as reading. Much of what children with mental retardation or even children in general know about the world is learned implicitly by inducing ideas from experience rather than being explicitly taught. Learning by means of a cognitive tutor happens in much the same way, as rules for the construct being taught (in this case, reading skills) are often not overtly stated. Instead they are determined by the child through trial and error.

Research suggests that for many children with mental retardation, implicit learning skills are a strength. Don et al. (2003) discovered that when controlling for working memory and nonverbal intelligence, individuals with Williams syndrome performed equally as well on an artificial-grammar learning paradigm requiring implicit learning as their typically developing controls. Results from a study by Atwell et al. (2003) indicate that individuals with mental retardation perform poorly when compared to typically developing individuals on explicit learning activities but did just as well on implicit learning tasks. Atwell et al. (2003) suggest that acquiring knowledge about complex material is equivalent for individuals of varying cognitive abilities when accomplished through implicit learning. While this assumption may be a stretch, it is an important skill to tap in teaching new skills to individuals with mental retardation.

Considering the role of implicit learning in cognitive based tutors, as well as the motivation and metacognition skills taught through them, designing a computerized cognitive based tutor seems to be the best option to teach individuals with mental retardation how to read.

Why is Learning to Read so Important?

For children with mental retardation, reading opens the door to an independent life and the ability to further learn more complex academic skills. When children are able to read, they can to communicate with others through written language, create their own to-do lists, and shop for their own supplies. Writing offers a creative outlet for individuals with mental retardation, while reading provides a quiet recreation activity that can be enjoyed in solitude. For these and many other reasons, learning to read must be a priority in the education of all children, even those with mental retardation.

Phonics versus Whole-Word Literacy Training

After carefully considering the ease of implementation and value of a computer-based intelligent tutor to teach children with mental retardation, researchers must next identify the best mechanism for reading instruction: phonics or the more traditional sight word recognition method.

In the typically developing population, the process of reading is comprised of two distinct yet interrelated abilities: (1) word recognition and (2) reading comprehension (Macaruso et al. 2006). To identify a new sight word in reading, children must apply known rules to segment sounds into phonemes and then recombine these phonemes fluently. As a child becomes a more proficient and experienced reader, this decoding process becomes increasingly automatic, as he or she is able to consciously manipulate the components of the language in a construct known as metalinguistics (Mervis, 2009). In reading comprehension monitoring, a core component of metalinguistics, each child must think about what he or she has just read and determine if the mental translation from text is understandable. When the reading is not understood, a child must be prepared to employ cognitive tools to clarify the text such as looking for contextual cues (Mervis, 2009).

Children with mild to moderate mental retardation have historically been taught to memorize sight words rather than to “sound them out”, learning to segment words into distinct phonemes in the letter-sound pairing process of phonics (Laurice & Seery, 2004). Many reading experts are now endorsing phonetic instruction for children with developmental delays, but educators are hesitant to embrace this teaching technique. In a metanalysis conducted by Laurice and Seery (2004), comparisons between sight word learning, where children repeated words presented on flashcards, and phonics instruction, including a tactile kinesthetic task of children tracing letters over sandpaper while also saying the word, indicated improved learning through the phonics approach. Unfortunately, in the seven studies included in this metanaylsis, only one (Barbetta et al. 1993) specifically addressed teaching phonics through error correction (Laurice & Seery, 2004). Error correction procedures such as a teacher breaking down words into syllables following a mistake in phonetic “sounding out” should be a fundamental component of any intelligent tutor system as its importance has been empirically supported (Laurice & Seery, 2004).

An essential factor, the characteristic weaknesses in language abilities for specific diagnoses that also result in mental retardation, should not be overlooked in the design of this computer-based tutor for reading instruction. According to Klusek et al. (2009), nearly two thirds of all children with Down syndrome experience some degree of hearing loss, which could potentially compromise their ability to learn phonetically if unable to hear sounds accurately. The visual processing strengths of children with Down syndrome make learning to recognize whole words more natural; however, phonological memory was also able to predict variation in reading ability (Klusek et al. 2009). Moreover, Cupples and Iacono (2002) determined that children with Down syndrome who received phonological training generalized these methods to unknown words, whereas children who had learned solely to use whole words were not able to (Klusek et al. 2009). These findings indicate that phonological awareness must be integrated with whole word learning for any cognitive tutor built specifically for children with mental retardation.

Previous research suggests that performance on phonemic awareness tasks is actually a better predictor of reading achievement than IQ across various syndromes and special needs (Laurice and Seery, 2004). Macaruso et al. (2006) utilized a computer program for at-risk children to conclude that first graders eligible for Title 1 services can outperform their socioeconomically matched peers when they are taught to read using phonics rather than whole word strategies. Murphy (2009) indicated that learning through phonics was an appropriate method for teaching children with Turner’s syndrome, whereas Finestack et al. (2009) suggested that children with Fragile X have more difficulty with higher level phonological processing, but are able to both whole-word and phonetically decode less difficult words. Mervis (2009) determined that children with Williams syndrome benefit from phonetic instruction because of the strong relations between their phonological awareness and reading skills. Finally, Hatcher et al. (2004) as described by Macaruso et al. (2006) found that explicit phoneme training in reading instruction did not improve literacy skills in typically developing children, but was extremely beneficial for children with reading delays (Regtvoort and van der Leij, 2007). Obviously, there has not been sufficient and conclusive research regarding the use of phonics to teach children with mental retardation, but these strategies provided in a computer-based intelligent tutor could serve as platform to launch future research and a new tool in the educational market.

The TRAINing to Read Cognitive Tutor Design

To formulate an effective cognitive tutor that can be easily replicated to teach millions of children with mental retardation, an adaptable, visually stimulating, and interactive program must be designed where children can learn at varying speeds. Self-paced knowledge tracing will be an important facet of our design to prevent children from becoming bored or overly frustrated, in addition to the many characteristics described in the following paragraphs.

Input from an animated character, similar to Lexie the Lion employed by Macaruso and Walker (2008), will provide instructions for each module and scaffold hints to support student progress on the cognitive tutoring system. A Bayesian estimation procedure will be used to identify individual strength and weaknesses based on responses to questions posed in the model and used to select follow up questions that are in the appropriate range of difficulty for each student (Koedinger et al. 1997). Throughout a child’s operation of the computerized intelligent tutor, the program will trace all responses and return to areas frequently missed to provide hints and specific practice as necessary (Macaruso and Walker, 2008), while alerting classroom teachers and parents of these difficulties. In this way, our cognitive based tutor will provide the individualized support that has become increasingly important as children with a wide range of intellectual abilities are placed together in the same public school classrooms with one common instructor.

Koedinger et al. (1997) emphasize the importance of timely feedback in our cognitive tutor to provide adequate motivational benefits. Macaruso et al. (2006) substantiated that corrective feedback was crucial to the process of learning through cognitive tutors, citing programs like Daisy Quest and the Daisy’s Castle, precursors to our phonetic instruction model. Children must be informed of their mistakes so that they can modify their approach before the incorrect strategy becomes habitual or strongly encoded.

It will be important to constrain the problem space of our students’ responses similar to those described by Lesgold et al. (1992) in their SHERLOCK system, by allowing only actions that would be plausible for users with mental retardation to make. For example, mistakes resulting from inattention will be built into the problem space so that when errors predictive of distraction are made, the child’s attention is redirected back to the task quickly. Specific hints should also be given to the student based on his or her past performance on the task to ensure the appropriate level of feedback is given. The complexity of feedback should be personalized to each child’s individual cognitive ability so that lower functioning children are not given more information about their performance than they can adequately process and retain.

In a new computerized cognitive tutor design, TRAINing to Read (TTR), children with mental retardation will learn to segment, pronounce and blend phonics in an introduction to basic literacy skills. Downloadable from the internet, TTR can be mass distributed to children’s homes, schools, and libraries, where daily reports of activities and errors will be generated and emailed to educators and parents. Each child will be assigned a unique login name and password so that multiple students can share a single computer. Children can also access their TTR module from various computers, allowing for them to practice at home under parental supervision as well as at school, in the library, or in after-school care settings.

Upon loading the software, children will be administered a CompSkills style training (Meyers, 1988) to become comfortable with pointing and clicking their desired response with a computer mouse. I had originally considered developing a membrane keyboard overlay to label objects on the screen as was described by Meyers (1988) but decided that learning to move a mouse would be an easier skill for children to acquire. On the other hand, for children with visual-spatial processing difficulties, a keyboard substitution will also be made available.

Following computer skill training, children will be introduced to a realistic yet animated character, Bob the Train Conductor, who will lead them through the exercises and provide hints when they are requested. Trains will be a structural theme throughout the TTR program, as many children with mental retardation show interest in modes of transportation, particularly trains. Other theme structures could be built for additional levels in the program or for specific interests for various children with mental retardation and downloadable from the same internet website.

Bob, our train conductor, will walk across the screen, pause to introduce himself, and explain his mission while requesting help from the learner to achieve his assigned task. Bob has been asked to transport cars full of toys from the toy store to homes throughout the community where hundreds of little children are waiting to play with their gifts. Cars contain toys and their corresponding activities and are propelled along the track with the completion of each activity. After the learner has completed the activity in each car, another train car “pulls” into the screen view and its corresponding activity is launched.

The first car in Bob’s train asks participants to repeat a particular sound (written on the side of the train) and click on an item that begins with this same sound. For example a colorful “P” would be placed on the side of the train car and highlighted when the sound was produced by the conductor. The learner will next be expected to click on the puppy and drag its icon over to the top of the train car, where the mouse button would then be released and the puppy toy would fall inside the train car to await delivery. Once the toy was successfully dropped into the train car, the “P” on its exterior would be highlighted and the child would be asked to repeat the sound into a microphone headset where observed auditory waves are compared against the expected response to determine accuracy of pronunciation. If an error occurs, the child is prompted to try again. If not, the train’s whistle blows and the next car pulls forward to reveal the next letter-toy pair.

Another activity built into the design of the train program will be a fading task to enhance recall skills for children with mental retardation in literacy learning. Using Bob’s voice, a phoneme drawn on the side of a train car will be pronounced slowly, and the child will be encouraged to repeat this sound. The word will be broken down into phonemes and paired with a simple line drawing of a child’s toy. For example, the word “cat” will be written on the outside of the train car and individual sounds will light up as the conductor pronounces them. In the same fading strategy discussed by Hetzroni and Shalem (2005), a toy cat will be shown clearly on the top of the train car, pairing the toy with the letters and spoken sounds. As the train conductor repeats the word, the lines of the cat drawing will gradually fade, leaving only the words to represent the cat toy. The child will repeat the word “cat” into the microphone headset and the train car will roll off of screen and the next activity car will be presented. Each of the child’s verbalizations will be recorded in the computer and forwarded to the supervising teacher or parent who can also gauge the child’s progress throughout the exercise auditorily.

After the child has successfully completed three very difficult train car tasks in a row (or is displaying signs of fatigue), he or she will be presented words segmented into phonemes. A headshot of the train conductor will read the posted word complete with facial expression and moving lips, while sounding out each syllable and encouraging the child to repeat the word as loudly or softly as desired. This fast paced exercise should reinvigorate the student for learning new material while also making him or her feel accomplished when quickly completing an easier task. The integration of the conductor’s face in this screenshot is important to note, as it mirrors the findings by Massaro and Bosseler (2005), who discovered that children with autism learn significantly faster in the presence of a computer generated face. According to this same source, the human face provides visual information during speech production which may be helpful for individuals with mental retardation.

Throughout the TTR program, children will be reminded to click on any of the help modules to request assistance as needed. Information provided in the help bars will be based on the child’s current abilities and success in responding to previous train car activities, through a knowledge tracing process. Each child can request a spoken cue, one where the conductor enters the center of the screen and speaks directly to the learner, providing the first few sounds of a letter or other hints as appropriate according to the exercise. Other cues can be given through animated prompts or separation of syllables in a more difficult word. When a child has asked repeatedly for help through the help menu, an instant message will be immediately sent to the supervising teacher or parent via cellular phone or computer. This notification system will allow instructors to intervene before a child becomes too frustrated or to step in to correct a behavioral problem. An email log of each help request and incorrect response will be maintained and emailed to all applicable users (teachers, parents, clinicians, and others).

After all of the train tasks have been completed, the train will travel across the screen in a circular pattern on the tracks quickly as the conductor (and the student) repeat words from earlier within the lesson across the train cars.

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TRAINing to Read: A Cognitive Tutor for Children with Mental Retardation (Part 2)

June 24th, 2010 Comments off

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Bob the Conductor will be shown delivering all of the toys that each child learned about through the reading activities, and at the end of this sequence of graphics, children will be presented with a redemption code where they can ask a parent to help them enter online and chose one of the many prizes to be mailed to their home.

The physical construction of this downloadable computer program must be designed and tested on hundreds of children with mental retardation to determine the efficacy of the model with an appropriate power. Developers must first identify a school district similar to those involved in the testing of Betty’s Brain where cooperation and collaboration is beneficial to both parties and there exists a large population of high functioning individuals with mental retardation. In the initial test stages, TTR should first be deployed specifically for children with mental retardation with IQs greater than 70 because previous research suggests that these children are capable of learning to read. Once the effectiveness has been determined and revisions made to the program, children with lower IQs should be tested to ensure that children of all cognitive abilities can benefit from the TTR computer program. Modifications may be required to provide a more suitable learning environment for children with lower cognitive functioning, but this should be addressed after initial deployment and revisions have been made.

To ensure proper implementation and execution of the TTR literacy program, teachers must “buy into” the program, for lack of a better word. During the initial beta testing of the program, teachers from school districts participating in the first pilot studies will be invited to attend a free two-day seminar where they will learn about TTR’s development. Attendees will have the opportunity to test out the TTR software and make recommendations to the developers, as well as sign up for their classrooms to be one of the first to launch the program. Through these pre-release seminars, classroom teachers should feel ownership for the program and will thus be more likely to administer and supervise according to the original design. New modules in place of the train theme, additional hint instructions, and other improvements will be made based on teacher feedback before the final version is released. As TTR will be available for update on the internet, this software can be modified and downloaded throughout the life of the program to continually improve it as a literacy training resource.

Once TTR has been downloaded onto school computers and teachers have been trained to administer the program, an informational session will be held for parents at the school so that TTR may be successfully used in the home. Parents and teachers will be able to communicate with one another through the program’s messaging service to track student progress and indicate concern in specific areas of learning.

Should the initial implementation of TTR be successful, additional academic lessons for older children with mental retardation can be produced within a similar framework. In this way, children with intellectual and even physical disabilities could safely conduct their own science experiments using virtual Bunsen burners and volatile chemicals that would otherwise be unsafe in a special education classroom. Cognitive tutors can be expanded beyond reading and mathematics applications to encompass other courses that could benefit children with mental retardation. Based on the design and implementation process described, I predict great success in the use of TTR and other future cognitive tutor models to supplement traditional academic instruction.

References

Antshel, K. Marrinam, E. Kates, W. Fremont, W. & Shprintzen, R. (2009). Language and literacy development in individuals with Velo-cardio facial syndrome. Topics in Language Disorders, 29, 170-186.

Atwell, J. Conners, F. & Merrill, E. (2003). Implicit and explicit learning in young adults with mental retardation. American Journal of Mental Retardation, 108, 56-68.

Crowley, R. Legowski, E. Medvedeva, O. Tseytlin, E. Roth, E. & Jukic, D. (2007). Evaluation of an intelligent tutoring system in pathology: Effects of external representation on performance gains, metacognition, and acceptance. Journal of American Medical Informatics Association, 14, 182-190.

Davies, D. & Hastings, R. (2003). Computer technology in clinical psychology services for people with mental retardation: A review. Education and Training in Developmental Disabilities, 38, 341-352.

Davies, D. Stock, S. & Wehmeyer, M. (2002). Enhancing independent time-management skills of individuals with mental retardation using a palmtop personal computer. Mental Retardation, 40, 358-365.

Davies, D. Stock, S. & Wehmeyer, M. (2003). Utilization of computer technology to facilitate money management by individuals with mental retardation. Education and Training in Developmental Disabilities, 38, 106-112.

Davies, D. Stock, S. & Wehmeyer, M. (2004). Computer-mediated, self-directed computer training and skill assessment for individuals with mental retardation. Journal of Developmental and Physical Disabilities, 16, 95-105.

Don, A. Schellenberg, E. Reber, A. MiGirolamo, K. & Wang, P. (2003). Implicit learning in children and adults with Williams syndrome. Developmental Neuropsychology, 23, 201-225.

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TRAINing to Read: A Cognitive Tutor for Children with Mental Retardation (Part 3)

June 24th, 2010 Comments off

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Finestack, L. Richmond, E. & Abbeduto, L. (2009). Language development in individuals with Fragile X syndrome. Topics in Language Disorders, 29, 133-148.

Hetzroni, O. & Shalem, U. (2005). From Logos to orthographic symbols: a multilevel fading computer program for teaching nonverbal children with autism. Focus on Autism and Other Developmental Disabilities, 20, 201-212.

Kame’enui, E. & Wallin, J. (2006). Information technology and the literacy needs of special populations: Ode to FedEx and dairy farmers. International Handbook of Literacy and Technology, 2, 379-386.

Koedinger, K. Anderson, J. Hadley, W. & Mark, M. (1997). Intelligent tutors to school in the big city. International Journal of Artificial Intelligence in Education, 8, 30-43.

Laurice, J. & Seery, M. (2004). Where is the phonics? A review of the literature on the use of phonetic analysis with students with mental retardation. Remedial and Special Education, 25, 88-94.

Lesgold, A. Lajoie, S. Brunzo, M. & Eggan, G. (1992). SHERLOCK: A coached practice environment for an electronics troubleshooting job. Instruction and Intelligent Tutoring Systems: Shared Goals and Complementary Approaches. Hillsdale, New Jersey: NDSS.

Macaruso, P. Hook, P. McCabe, R. (2006). The efficacy of computer-based supplementary phonics programs for advancing reading skills in at-risk elementary students. Journal of Research in Reading, 29 (2), 162-172.

Macaruso, P. & Walker, A. (2008). The efficacy of computer-assisted instruction for advancing literacy skills in kindergarten children. Reading Psychology, 29, 226-287.

Martin, G. Klusek, J. Estigarribia, B. & Roberts, J. (2009). Language characteristics of individuals with Down syndrome. Topics in Language Disorders, 29, 112-132.

Massaro, D. & Bosseler, A. (2005). Read my lips: The importance of the face in a computer-animated tutor for vocabulary learning by children with autism. SAGE Publications and the National Autistic Society, 10, 495-510.

Mervis, C. (2009). Language and literacy development of children with Williams syndrome. Topics in Language Disorders, 29, 149-169.

Meyers, L. (1988) Using computers to teach children with Down syndrome spoken and written language skills. In Nadel, L. (Ed): The Psychology of Down Syndrome. New York: NDSS.

Murphy, M. (2009). Language and literacy in Turner syndrome. Topics in Language Disorders, 29, 187-194.

Ortega-Tudela, J. & Gomez-Ariza, C. (2006). Computer-assisted teaching and mathematical learning in Down syndrome children. Journal of Computer Assisted Learning, 22, 298-307.

Regtvoort ,A. & van der Leij, A. (2007). Early intervention with children of dyslexic parents: effects of computer-based reading instruction at home on literacy acquisition. Learning and Individual Differences, 17, 35-53.

Soares, D. Vannest, K. & Harrison, J. (2009). Computer aided self-monitoring to increase academic production and reduce self-injurious behavior in a child with autism. Behavioral Interventions, 24, 171-183.

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Early Detection of Autism in Infants and Toddlers (Part 3)

June 15th, 2010 Comments off

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These animal subjects subsequently displayed the persistent and severe cognitive and social impairments as well as stereotyped and self-stimulatory behaviors that are defining features of autism (Dawson et al. 1998). However, this discovery does contrast a recent case study evaluation of a young autistic girl by Dawson, Osterling, Meltzoff, and Kuhl which determined that in this specific child at one year of age, impairments did not exist in the domains of immediate memory of actions, working memory, and response inhibition linked to frontal lobe functioning as core features of autism (2000).

Head Circumference Growth as a Predictor of Autism

A recent discovery in human physiology and brain development research has led to the involvement of the Baby Sibs consortium in an effort to determine the earliest physical markers of autism, particularly abnormal head circumference growth (Kalb, 2005). It is presumed that if a significant increase in head growth during infancy is a risk factor for autism, the mechanism that triggers this onset of growth would actually precede any manifestation of the disorder. Post-mortem brain studies described by Lainhart suggest that brain abnormalities begin before birth in at least a percentage of cases of autism, and therefore, provide further evidence to this claim (2003). According to this same author, between birth and six to fourteen months of age, head circumference has been shown to increase at a significantly greater rate in children with autism than in an control or reference sample (Lainhart, 2003); fifty-nine percent of children with autism and only six percent of typically developing children show an increase of two or more standard deviations in head circumference during this developmental time. In another study of this same type with consistently similar results, it was determined that approximately ninety percent of two and three year old children had brain volumes larger than the healthy average in addition to abnormally large head circumferences (Courchesne, Carper, & Akshoomoff, 2003). In comparison to growth charts produced by the Center for Disease Control, average head size in recruited participants increased from the twenty-fifth percentile at birth to the eighty-four percentile in six to fourteen month old babies with autism spectrum disorders (Courchesne, et al. 2003), well before the typical onset of clinically significant behavioral symptoms. By late childhood, however, a follow-up study of participants between the ages of eight and forty-six yielded MRI results demonstrating that this extreme brain overgrowth is time limited and that eventually brain size between control and autistic individuals becomes approximately equal (Courchesne, et al. 2003). An additional study by Torrey, Dhavale, Lawlor, and Yolken discovered a pattern of significantly larger body weight and length in four month old infants later diagnosed with autism in comparison to control subjects, inferring that an abnormality in metabolism, growth factors, and hormone levels may indeed be the culprit (2004). Accelerated rate in head circumference growth is associated during infancy with overall increased brain volume and gray matter, as well as increased cerebral gray matter. Scientists have not come to a conclusive decision as to what exactly accounts for this increase, but theory suggests that the sudden growth could result from an over abundance of neuronal connections, which pruning fails to eliminate (Kalb, 2005).

The discovery that an overgrowth of head circumference occurs frequently during the early months of life for those later diagnosed with autism holds a very promising clinical role in the detection of this disorder. An inexpensive and noninvasive assessment technique, the tracking of brain size development may be a key to early diagnosis and consequently, even earlier intervention practices. If these results are further confirmed by subsequent studies, physicians and psychologists in the future may be able to quickly assess the risk for developing autism based on physical examination alone.

Communication Abnormalities: Nonverbal Gestures and Speech

Parents frequently express initial concern over their child’s speech and communication development, and thus this often becomes the first complaint of autism-related behavior that sends parents to seek out an evaluation. Although typically developing newborn infants possess immature brains, limited cognition, and weak bodies, it has been established that most are very motivated beyond an instinctual drive to attract parental care for immediate biological needs, and thus “to communicate intricately with the expressive forms and rhythms of interest and feeling displayed by other humans,” (Trevarthen & Aitken, 2001). This drive does not seem to be as strong in young children with autism as in most instances they communicate less frequently than matched developmentally delayed children. These children are also less likely to use contact and conventional gestures in requesting an object, but are, in fact, more likely to use unconventional gestures to make up for this deficit in such ways as manipulating the hand of the individual with whom they are interacting to the desired object (Volkmar et al. 2005). In an article by Werner et al. it was demonstrated that at two months of age, infants start to implement their vocalizations in a semi-social manner, and this distinction further aids in subsequent speech and language development (2000). From these results, one can determine that perhaps differences in these areas of vocalization between typically developing and impaired infants become evident by the age of twelve months. Also between the ages of six months to one year, meaningful differences become more pronounced in the communicative criteria, especially noted when these children develop a general lack of orientation toward verbalization and their own names. These differences, however, are often not utilized in evaluation of development and assessment for autism in individual children because most parents fail to recognize these communication difficulties until spoken language is more apparently delayed.

Within this same realm of communicative impairment, very young children with autism have also be distinguished in various studies from typically developing controls on the basis of response to name calling.

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Early Detection of Autism in Infants and Toddlers (Part 4)

June 15th, 2010 Comments off

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The process of learning to orient to one’s own name involves aspects of both social and communication domains as well as attention (Werner et al. 2000), and therefore, difficulties in responding to this specific vocalization indicates a broad range of dysfunction. Potentially a powerful estimate of impairment on the autism disorder spectrum, typically developing infants orient to their name being called approximately seventy-five percent of the time, whereas only thirty-seven percent of autistic infants oriented to their names between the ages of eight and ten months using retrospective home video footage in a study by Werner et al. (2000). Fewer differences were noted in terms of social response to name calling than in the Osterling and Dawson study (1994) of infants at one year of age, perhaps due to the fact that between nine and twelve months of age, many new behaviors are just beginning to develop. Although many complex social, emotional, and communicative behaviors emerge during the eight to nine months of life, skills within these categories do not begin to solidify until after the age of one.

Joint Attention as a Predictor for Social Impairment

The previous example of response to name calling in very young children also draws upon the difficulties that most autistic infants experience in their development of joint attention skills. During the first year of life, children with autism spectrum disorders may fail to follow a point and in many instances, will not gaze switch between interesting objects and an adult’s face or coordinate responses to emotional displays by an adult (Charman, Baron-Cohen, Swettenham, Cox, Baird, & Drew, 1997). Moreover, gaze monitoring in joint attention, which provides relevant information concerning interests and dangers in the environment, is essential for the active participation of social learning opportunities for all infants (Charwarska, Klin, & Volkmar, 2003). As such, deficits in spontaneous gaze monitoring are widely recognized at this point in current research as early signs of autism, although we are unaware of the neurological mechanisms to produce these problems. Kalb has determined through eye-tracking technology that when affected toddlers view the videos of their caregivers or other babies within the same nursery of which they are familiar, they tend to focus more on the individual’s mouth or an object located directly behind the individual than his or her eyes (2005). This finding was confirmed when Charwarska et al. demonstrated in 2003 that although face recognition improves with age in those with autism, older individuals employ feature-based rather than holistic strategies in face processing, and therefore, “recruit different neural substrates in face processing than their typical controls,” (1985).

In terms of pointing behavior, typically developing children will follow a pointed index finger when they have achieved a developmental level of twelve months old, but children with autism from the time they are born are significantly less likely, according to Young et al. to switch their gaze as a means of following a point by another individual (2003). Despite these findings, many infants with autism at two years of age show intact performance relative to typically developing controls in the area of nonsocial use of gaze to obtain information about objects and the environment surrounding them. Charman et al. suggest that these abilities remain intact in those with autism although social gaze is not initiated because they are not a feature of the central social communicative deficit in autism (1997). This discovery asserts that there may indeed be a key difference between the growth of social and nonsocial use of gaze in broad development of all infants.

Imitation and Pretend Play

Significant delays in the production of imitation in very young infants as well as pretend play schemes in their slightly older counterparts are important warning signs to monitor in developing criterion for early assessment strategies. Imitation by typically developing and developmentally delayed infants is not merely a superficial repetition of movements made by another person but is instead a complex tool for developing interpersonal relationships with parents (Trevarthen & Aitken, 2001). Trevarthen and Aitken continue in this explanation in stating, “[imitation] is, even for newborns, an emotionally charged mutual influence of motive states in which certain salient expressive actions of the other are identified and repeated to further an ongoing communication,” (2001). A study by Charman et al. produced confirming results in suggesting that although basic level of imitation is apparent in school-age children with autism, those under the age of twenty months show considerable difficulty and unresponsiveness in this area (1997). After the mastery of a significant degree of gross and fine motor skills has been obtain through imitation, most children will begin to establish play activities progressing from simple object exploration to functional object use and finally pretend play. Between the ages of nine and twelve months, however, distinguishable abnormalities become evident and progressively more deviant in those with autism spectrum disorder in comparison to typically developing peers (Volkmar et al. 2005). In this same study, it was determined that by the second birthday of many children with autism, differences in functional play abilities and routines are striking, particularly in terms of purposefulness, symbolism, and complexity (Volkmar et al. 2005). As functional play ability continues to be impeded throughout the early years of life, pretend play is further hindered, and thus, many children with autism do not begin to develop a concept of such imaginative behavior until they have been taught specific strategies and skills within an early intervention setting (Charman, Swettenham, Baron-Cohen, Cox, Baird, & Drew, 1998).

Implications of Early Diagnosis

Early detection and diagnosis of autism in young infants may be crucial to the future outcome of these individuals because early behavioral intervention has been shown to provide a substantial impact on the long-term prognosis (Osterling et al.

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