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18 Teacher Tool Kits for Computer-Assisted Instruction for Children with Autism


Thursday, July 7, 2011
Florida Hall A (Gaylord Palms Resort and Convention Center)
Computer assisted instruction can be used to supplement STEM instruction for children with autism.  However, many available programs are either developed as toys or for typically developing children.  A tool kit is included that specifies  criteria that should be considered when assessing or designing computer assisted instruction for children with autism.  
The purpose of this work is to demonstrate how Science, Technology, Engineering, and Mathematics (STEM) instruction can be utilized by a group of students (primarily those with autism) that often are unable to receive this area of instruction due to the nature of their disability and limited additional assistance within the classroom. We propose that computer-based technologies can be utilized as a tool for STEM instruction.  Further, an efficient, consistent protocol for delivery can be generated which will result in a Best Practices delivery while taking individual differences into consideration. Currently, the majority of readily available computer-based programs (e.g., shoebox tasks) are either designed as toys or designed for typically developing children.  In doing so, these computer-based programs often overlook any behavioural constraints that may impede learning objectives, and often fall short of fully supporting instructors by promoting and recording learning as well as behavioural events.  The following teacher tool kit can be used to assess current computer-based programs with ease.  This same tool kit can provide the base criteria for development of future computer-based technology that allow each program to be easily tailored by the instructor to meet the learning goals for each individual child with autism. 

STEM education has a big push right now for substantial reasons.  First, there is an overall lack of interest in science, engineering and mathematics careers; and second, if children are not interested by eight years of age, then it is difficult to increase interest (American College Testing, 2006).  Therefore, there is a big push to increase interest and instruction across the board from governmental agencies such as the Department of Education and funding agencies such as the National Science Foundation.  The question is, how do we increase STEM instruction for children with autism and related disabilities to afford a level playing field and the equal potential for growth to all students?   

STEM education 

STEM education currently utilizes a combination of text book learning, experimentation, and paper/pencil examinations.  Some new curricula even include movies and visual aids. However by third grade, it is a primarily reading-based curriculum.  For the students in special classrooms (e.g., Autism, Trainable Mental Handicap (TMH), self-contained), the hands-on components and experimentation of STEM instruction can be highly beneficial academically in that there is less to be interpreted on an emotional and/or social level to afford task completion.  However, to address behavioral needs, one-on-one assistance is often needed to complete these tasks. Teachers in these types of classrooms often do not have enough support to give each student one-on-one focused attention.  A second problem is that a majority of the science-based experiments take multiple days/weeks to see an outcome (e.g., a plant life cycle).  Due to the nature of the disability, it is often difficult for students to connect events from day to day. Therefore, STEM instruction is often underutilized.   

One solution is to utilize computer-based instruction to facilitate learning (Wegerif, 2004) at an individually-tailored understandable rate until initial subject mastery.  While there is very little research looking at computer-based technologies for STEM education for children with autism (other than research on human-robot interaction), there is a clear relationship between the level of distractibility and attention to task.  Further, it is anticipated that outside distractions coming from peer or instructor interaction significantly reduces time-on-task as well as overall learning outcomes.  Lastly, there is a significant limitation to the number of peers in a special-needs classroom; peer-based or “team” learning projects and/or experimentation across such a limited, idiosyncratic population is clearly not equivalent to the in-class experience in a standard classroom, where the population is more homogeneous, less distracted/distracting, better able to cope with annoyances, and have a classroom base large enough that poor peer-to-peer matches can be easily corrected.  The obvious solution to this issue is to utilize computers to substitute or supplement team-based endeavours, which opens up STEM curricula to children with autism equal to that of their typically developing cohorts.

The Tool Kit

 The classroom teacher needs to be an essential part of implementation of computer assisted instruction, from choosing the correct instructional assistance to transitioning it into classroom curriculum. Therefore, this tool kit is designed to assist teachers in choosing computer-based instructional  technologies for supplemental instruction of STEM curriculum. Further, it can be used to provide base design criteria for future development of STEM technology.  

When choosing computer-based programs (curriculum-based or online activities), the classroom environment, the child, and the computer technology must all be considered in order to optimize the learning experience. Further, computer-based technology is not intended to be a complete replacement of teacher-initiated instruction, however should be used as an additional teaching tool that allows for enhanced learning in this area. 

Environment  The key to the classroom environment is the configuration of classroom space.  The first consideration is the number of computers within the classroom and their intended usage. No matter if the instructor has one computer or ten, the number of activities/programs available on the computer should be limited so that only the intended activity is available.  The second consideration is the configuration of the computer within the intended space.  Computers should be located in an area of the classroom that minimizes outside stimuli (e.g., study carrels) and a set distance from other carrels, students or possible distractor objects.

Student Computer-based instruction for children with autism need not only focus on academic-based STEM learning objectives, it also needs to include behavioral learning objectives.   Table 1 describes physical characteristics, computer experience, and academic, social and psychological skills that should be considered when choosing or developing computer assisted instruction with regards to the child as the user.  

Table 1:  User Profile for Child with Autism

Characteristics

Description of Characteristics

    

 

Physical Characteristics

Ability

Physical characteristics are equal to typically developing child (DSM-IV Criteria, Pervasive Developmental Disorders 299.00 Autistic Disorder)

 

Background

Normal motor and Visual Capabilities (DSM-IV Criteria, Pervasive Developmental Disorders 299.00 Autistic Disorder)

 

 

Computer Experience

System Use

Novice: Step-by-Step

Transition from Novice to Expert Capability

 

Education level

Age 8 and above (Mayes, 2003)

 

 

Academic Skills

Cognitive Capacity (spatial ability)

*Age and IQ may affect the stability of test scores over time and the pattern of abilities in children with autism

*Non-verbal IQ higher than verbal IQ

*IQ increases with age

(Mayes, 2003)

 

Basic Knowledge

Differences found between

IQ<80 and IQ>80 in following areas: IQ, Verbal IQ, Non-verbal IQ, Visual Reasoning, Graphomotor, Reading, Math, Spelling

(Mayes, 2003)

 

 

Social Skills

Assesments

Social skills assessments may be used to gauge an more accurate level of social skills competency  (Constantino, 2003; Bellini, 2006)

 

Social Orienting

*SRS  (Social Reciprocity Scale) (Dawson, 2004)

 

Joint Attention

*ADI-R (Autism Diagnostic Interview-Revised) (Dawson, 2004)

 

 

Psychological Skills

Assesments

*Autism Social Skills Profile (ASSP) (Ayres, 2005)

 

Attitudes

*System should be subjectively pleasing

*Have variability for child’s sensory needs

(Ayres, 2005)

 

Motivation

Attention grabbing – colors, lights, sounds, feedback (Ayres, 2005)

 

Some perceptual and cognitive tasks that can be monitored during computer-based instruction may include attention to task, following directions (verbal and/or visual), correct response and amount of assistance required (as described in Table 2).  While the teacher may be required for the majority of the behavior monitoring to date, some current computer-based programs and future design may be able to incorporate and adapt monitoring procedures.   

Table 2:  Measuring Behaviors During Computer Activities 

Dependent Variable

Operational Definition

    

Attend to Task

Time looking at Computer Screen

Ratio of the time spent looking at the computer screen to total time of training session.

Off task

Ratio of the time spent on avoidance behaviors to total time of the training session.

 

Follow Directions

Verbal Instructions

Ratio of the total number of verbal directions followed to the total number of directions given.

Visual Instructions

Ratio of the total number of visual directions followed to the total number of directions given.

Task Reaction Time

Time to begin task after hearing/seeing instruction

 

Correct Response

Initial Response

Ratio of the number of correct responses given by child to the total possible number of correct responses during the entire scenario.

Checking answers

Number of times the subject visually checked the answer prior to selection

Corrections

Ratio of the number of times the child made corrections independently compared to the number of corrections made with system feedback.

Whole vs. Part

Ratio of the number of correct responses classifying part to whole given by child to the total possible number of correct part to whole responses during the entire scenario.

Same vs. Different

Ratio of the number of correct responses classifying same/different given by child to the total possible number of correct same/different responses during the entire scenario.

 

Contact Teacher

Independent Contacts

Ratio of the number of times the child independently contacted teacher for help compared to the system alerting teacher to help

Inappropriate Contacts

Number of times the child contacted teacher without an academic or behavioral need 

 

Computer Technology Computer technology is also an important component. Both the hardware (inputs and outputs) and software (feedback, cues, duration, and adaptability) must be taken into account when assessing computer assisted instruction (see Table 3). Ultimately the process of learning how to accomplish the task should be easily understood so that learning the instructional material can become the focus (Sklar, 2003).  

Table 3:  Computer Technology Profile 

Characteristics

Description of Characteristics

       

Hardware

 

Input Devices

*Most common input devices are keyboard and mouse

*Touchscreen or modified input (single button, 2 button or 4 button response pad) may be considered to reduce distraction

Screen Size

*Smaller screen size may be more beneficial for focusing attention

Output 

*Type of voice for output (e.g., providing instructions) 

 

Software

 

Feedback/Attentional Cues

*Feedback should be provided directly following input

*Use actions, sound effects or other engaging features to increase interest and attention (Moore & Calvert, 2000)

Duration of lesson

*Short and manageable

*Provides opportunity for success

*Provides desired level of time on task

Exiting Program

*Non-intuitive escape from program encourages task completion

Adaptability

*Enhanced adaptability accounts for greater number of individual differences 

Even though the upcoming Science and Mathematics state requirements have created alternative standards for individuals with Cognitive Disabilities, the majority of standards require peer/instructor involvement.  Therefore we suggest that computer-based technology can be used as a teaching tool that can act as a social peer to assist in meeting STEM criteria set up by State Standards.  This research has the potential of providing academic instruction and behavioral intervention that could provide needed instruction not only to be successful on standardized exams, but to encourage and support further educational/career opportunities.  Furthermore, it has the potential for transfer of training into the traditional type classroom leading to future inclusion.

Works Cited

American College Testing. (2006). http://www.act.org/research/policymakers/pdf/ACT_STEM_PolicyRpt.pdf, December 20, 2010. 

Ayres, A.J. (2005). Sensory Integration and the Child. Los Angeles: Western Psychological Services. 

Constantino, J.E. (2003). Validation of a Brief Quantitative Measure of Autistic Traits: Comparison of the Social Responsiveness Scale with the Autism Diagnostic Interview-Revised . Journal of Autism and Developmental Disorders, 33(4), 427-433.

Dawson, G.E. (2004). Early Social Attention Impairments in Autism: Social Orienting, Joint Attention, and Attention to Distress. Developmental Psychology, 40(2), 271-283. 

Mayes, S.A. (2003). Ability Profiles in Children with Autism. Autism, 6(4), 65-80. 

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

Sklar, E. (2003).  Agents for Education: When too much intelligence is a bad thing. In Second International Joint Conference on Autonomous Agents and Multi-Agent Systems.

Wegerif, R. (2004). The role of educational software as a support for teaching and learning conversations. Computers & Education, 43, 179-191.


Kristin E. Oleson, M.S.
Researcher
University of Central Florida

Kristin Oleson, M.S., is a researcher with the University of Central Florida and a certified Florida public school teacher. Kristin has over 7 years' experience working with the autistic population (ages 2 - 12th grade) and their families, from behavior intervention therapy and education to technology-based research.


Ryan Erin Yordon, M.S.
Researcher
University of Central Florida

Ryan Yordon, M.S. is a researcher at the University of Central Florida in the Applied Cognition and Technology Laboratory. Her research includes developing and implementing technology-based protocols and interventions for specialized populations.


Tatiana T. Ballion, M.A.
Researcher
University of Central Florida

Tatiana Ballion is a researcher at the University of Central Florida in the Applied Cognition and Technology Laboratory. Her previous work has been in the area of human-computer, human-robot interaction, the Uncanny Valley, and anthropomorphism. Her interests include the introduction of human heuristics and templates to non-human entities and interactions.