Assistive Technology: Enhancing the Life Skills of Students With Learning Disabilities

The goal of this study was to explore and report how behavior therapists and applied behavior analysts used data derived from the Child Behavioral Checklist (CBCL) and the Parent-Infant Relationship Global Assessment Scale (PIR-GAS) to prescribe assistive technology to increase the overall psychological well-being of early childhood students, ranging in age from 3 to 5 years. The CBCL is a tool that parents, teachers, clinicians, and therapists who know the child rate a child’s problem behaviors and competencies (Achenbach, 1991). The PIR-GAS is a scale of infant-parent relationship adaptation, raging from “well-adapted” to “dangerously impaired” (Aoki, Zeanah, Heller, & Bakshi, 2002, p. 493). Applied behavior analysis (ABA) is an active ingredient that assists preschool aged students to develop creativity and learn basic skills, such as speaking, listening, controlling emotions, et cetera. In this study, applied behavior analysis was conducted using assistive technology (AT) to enhance the learning and life skills of clients with learning disabilities. AT can help autistic children achieve their highest potential regardless of their inborn abilities (Hasselbring & Glaser, 2000; Smaldino, Lowther, & Russell, 2008; Tinker, 2001).

In the field of instructional technology (IT), special education, and in ABA, the varying definitions of AT are as follows: (a) “Any item, piece of equipment, or product system, whether acquired commercially, modified, or customized, that is used to increase, maintain, or improve functional capabilities of individuals with disabilities” (Assistive Technology Act, 2004, p. 1); (b) devices and software designed specifically for those with learning or physical disabilities (Smaldino, Lowther, & Russell, 2008); and (c) AT has powerful tools that support physically challenged students with equal opportunities to more fully participate in the teaching-learning process (Hager & Smith, 2003).

In this study, the researcher takes each definition into account and focuses on studying the impact of the computer, mediating hardware, and software used by disabled students in learning environment. The research suggests that students that use AT display positive effects for psychological health when compared to other children in the program who do not use AT (Cavanaugh, 2002; Hasselbring & Wil-liam-Glaser, 2000; Khek, Lim, & Zhong, 2006; Smaldino et al., 2008, 2012). Moreover, this body of research refers to the IT devices as a system of positive reinforcement used to help students learn. In this study the use of AT plays an important role in behavior management and enhancement of life skills for the overall education of students with learning disabilities.

In the areas of applied behavior analysis and special education, there are sets of technologies and computerized equipment that are used to assist children in the learning process. The list of technological devices and/or assistive technology used by behavior therapists as a treatment for children with special needs includes simple magnifiers, pointers, alternative input/output devices, touch screens, voice recognition systems, graphic organizing software, and special cognitive software (Khek et al., 2006).

In this study, the treatment group used AT to improve language and motor delays in children 3 to 5 years of age. Evaluating researchers have documented that, when AT is used for children with special needs, properly designed instruction contributes enormously to its effectiveness, especially in the case of autism (Cavanaugh, 2002; Smaldino et al., 2008). When used correctly for students with special needs, AT tends to create a learning environment that promotes enhanced operant procedures, positive self-growth, increased motor skills, and effective oral communication (Cavanaugh, 2002; Khek et al., 2006; Smaldino et al., 2008, 2012). In conjunction with the application of AT, educational therapists have found various technological devices to be effective in specific types of learning disability. Table 1 provides a list of practical uses of assistive technology devices for specific learning disabilities.

Children with disabilities need special instructional interventions that will eventually result in their improved understanding, learning function, and self-confidence with which they merit inclusion in the regular classroom. Multiple reports indicate that the number of students with disabilities enrolled in K-12 schools has steadily increased since the passage of P.L. 94-142:

The uses of IT and AT in education are not new phenomena. IT not only brings exciting treatment based on real-world problems into the classroom but also provides scaffolding to enhance learning (Hitchcock, 2001; Tinker, 2001). IT has increased the psychological health of global communities that include teachers using IT as a treatment for behaviors on a student’s individual education plan (Salomon, 1993). This technology gives students and teachers collaborative feedback, reflection, and revision. AT also expands learning opportunities for both teachers and students (Bransford, Brown, & Cocking, 1999).

In this study, the uses of computer-assisted instruction and computer-managed instruction are briefly outlined. The two treatments are used together with ABA to decrease the effects of language and speech delays in children with learning disabilities. In other words, the EDU-AT-TECH program uses AT in the form of computer-assisted instruction and computer-managed instruction as treatment for children with autism. Computer-assisted instruction refers to the use of technology to aid teaching and learning in the classroom (Cobb, 2009). Computer-managed instruction refers to the use of computer systems to manage information about learner performance and learning resources and to then prescribe and control individual lessons (Smaldino et al., 2012). Students who participate in tutorial drill, practice, and games tend to outperform students who do not use such interventions (Cobb, 2009; Morrison, 2001; Slavin, 2008). In addition, ABA teachers that use a combination of computer-assisted instruction and computer-managed instruction tend to use computer systems to manage information about learner performance and learning resources and to then prescribe and control individual lessons (Smaldino et al., 2008). By contrast, there has been a new shift toward a software design model which is characterized by a consistent presentation of voice prompts to promote interaction with audio in the form of voice and sound (Lewis & Doorlag, 1999).

Computer multimedia is a computer hardware/software system for the composition and display of presentations that incorporate text audio, still, and motion images (Smaldino et al., 2008). In this study, the researcher determined whether computer mediated hardware and software used by disabled students in a learning environment assist in improving their overall psychological well-being. Instructional Technology was used as a tool to improve instruction for students with learning disabilities.

Technology-productive tools consist of computer software that enables people to work more effectively and efficiently (Blackhurst & Koorland, 1995). IT and quality teaching increase the psychological well-being of students in the EDU-AT-TECH program. For example, voice recognition software with transcription capabilities can assist students with special needs who are physically unable to type using a keyboard (Hasselbring & Glaser, 2000).

Augmentative technology uses voice prompts to teach students that demonstrate developmental language delays in how to communicate at home and in the school environment, as well as in learning life skills. The technological cognitive code base in the device reduces a student’s dependence on others to perform such simple tasks as reading, writing, and listening. In addition, there are various types of software available that can provide immediate feedback to the student, and also offer an individualized learning environment. Furthermore, the data analysis driven method employed by ABA identifies behavior that is displayed and improved by the student as a vital component of overall success by tracking reinforcement and improved behavior in terms of performance objectives (Margolis & Michaels, 1994).

AT’s high standards provide benefits for students with learning disabilities. It improves student self-confidence and academic performance. This study includes documentation of observable behavior displayed by clients that the behavior therapist is able to describe and categorize in order to form a report. Such reports show that AT can increase students’ enthusiasm to learn. Students with mild learning disabilities often demonstrate higher-level performance and attention to detail when working on multimedia projects than they normally exhibit (Hasselbring & Glaser, 2000). As a result, their interest in academic endeavors is enhanced. In 2005, a nationwide population of approximately 70,000,000 pre-K-12 students who had been identified as having special needs was the driving initiative for the Individuals with Disabilities Education Act, which focused on students with disabilities that needed to be taught and brought to the same high standards as students without disabilities (U.S. Department of Education, 2006).

Innovative advantages in technology have assisted teachers to better meet the special needs of students with learning or physical disabilities, as well as students who have language delays. The values of using technology for diverse type of learners have been established and individualized education programs are now being created for students with special needs by integrating assistive technology into classroom instructional practices. Today’s applied behavior analysis can be used as a resource for specialized software and digital tools to create, maintain, and report student individualized education programs as well as to provide overall management, behavioral analysis, behavior therapy, and support of students with special needs. This program was created to meet the needs of the children with learning disabilities that are entitled to receive behavior therapy to meet their learning needs.

New technologies also serve to increase the current and future compatibility of classrooms in adapting to accommodate special needs learners. Learning centers can be equipped with assistive technology or digital devices and software designed specifically for children and adolescents with learning or special disabilities. The technology enables students to control the rate of speech delivery. A computer screen is used so they can better read the results of a database. The treatment allows students to perform a search by using a voice synthesizer, to have the printed page remade to meet their needs or to enable them to take notes in class through an electronic storage device that can later print out the document in Braille (Smaldino et al., 2008). The behavior therapists in the study made accommodations for the learners by offering user-centered selection of text and graphics for design options for the AT.

Behavior therapists at EDU-AT-TECH use technique alternatives with special needs learners by providing handouts using notes for hearing impaired learners and using audio recording for visually impaired learners. Thus, the treatment can improve the learning of all students. Students diagnosed with visual impairments require different kinds of learning materials such as appropriate audio devices; adjusted instruction for exceptional learners; and prescription of technology, media, and materials. Applied behavior analysis uses assistive strategies for students with disabilities. AT is beneficial to the clients because assistive technology enhances learning.

In Table 2 and Table 3, the outcomes of EDU-AT-TECH clients are presented by age, and by age and gender. EDU-AT-TECH was initiated in July 2007. Ninety-six EDU-AT-TECH clients consented to participate in Invest in Children’s external evaluation of the overall initiative. A total of 63.5% of the clients were male and 36.5% of the clients were female.

The mean age of the 61 male EDU-AT-TECH clients that participated in the program was 28 months, and the median age of the 35 female EDU-AT-TECH clients was also 28 months.

Table 4 represents data collected about the total number of parents that wished to be involved in Invest in Children’s external evaluation process. There were 96 EDU-AT-TECH clients enrolled in the program. Parents had the option of giving consent to be contacted during the evaluation process: 21.9% of the parents and/or caregivers indicated that they did not want to be contacted in regards to the evaluation of their child. By contrast, 77.1% of the parents and/or caregivers wanted to have contact with the provider regarding the evaluation of their child.

Table 5 is the data representation of the total number of clients that had a closed case in the EDU-AT-TECH program. Details of the data representation are discussed following the table.

Of the total number of EDU-AT-TECH clients in the EDU-AT-TECH program, 79.2% cases were closed, and the analysis of the data suggests that 27.1% of the cases were closed with treatment program completed satisfactorily; 38.5% of the cases were closed for noncompletion because a family member withdrew the client from the EDU-AT-TECH service; 2.1% of the clients’ cases were closed for noncompletion because the child transitioned to another program outside of the agency; 5.2% of client cases were closed because of noncompletion because the child aged out of the program at 48 months; and finally, 6.3% of the cases were closed for noncompletion because the family moved residence.

Table 6 is an analysis of how clients were referred to the EDU-AT-TECH program. The types of referral were self/parent, medical provider, social service organization/other agency, home service coordinator, and HMG service coordinator.

The data in Table 6 show that there are nine identified reference referral resources for the EDU-AT-TECH clients for Learning Disability Services: 10.4% of referrals are derived from parents, 2.1% of all referrals are from medical providers, 3.1% of the referrals are from a social service organization that are outside of the EDU-AT-TECH agency, 11.5% of the clients are referred by the Home Service Coordinator (Targeted ABA Program or Own Agency), and 71.9% of all referrals are from Home Service Coordinator (other agency).

Table 7 provides a presentation of the paired sample statistics and/or t test. The statistics are used to compare the assessment scores and group performance on a pretest and posttest of EDU-AT-TECH clients.

Table 7 contains the paired t-test used to compare the EDU-AT-TECH client assessment scores and group performance on a pretest and posttest. For instance, the assessment that is administered to the client is known as the CBCL. The CBCL is a standardized psychometric measure which records the behavioral problems and competencies of the children aged 1 1/2 to 5 years, as reported by their parents or others such as a guardian.

The CBCL has three main scales. The checklist is composed of 113 items that are all scored on a 3-item scale: 0 = not true, 1 = somewhat true, and 2 = very true. A parent or parents or guardian completes the CBCL. The instrument provides three scores: (a) a total score (CBCLt), (b) scores on internalizing behaviors (CBCLi; fearful, shy, anxious, and inhibited), and (c) externalizing behaviors (CBCLe; aggressive, antisocial, and undercontrolled).

A checklist is the form of the instrument. The method of delivery is a selfreport. The CBCL has relevance to injury. In other words, the instrument is used to assess behaviors that may be associated with injury in children.

PIR-GAS is an assessment scale for children under the age of 6 that focuses on the overall quality of the child-parent relationship. In the assessment, the parent-child relationships are described by a range of ability to adapt, from “well adapted” to “severely impaired”: The PIR-GAS scores range from 90, indicating a well-adapted relationship, to 10, indicating a severely impaired relationship. Stressors affect relationships described by scores in the middle range of 50 but still maintain some adaptive qualities (Billings & Moos, 1985).

Additionally, the PIR-GAS has been shown to share concurrent validity with the Achenbach CBCL for children ages 1.5 through 5 by providing answers to the following two questions: (a) Do children with autism spectrum disorders show improved functioning following treatment? (b) Does the use of AT and behavior therapy lead to differing levels of improvement in the symptoms exhibited by the children? The study also provides information that may prove useful to agencies in enhancing their current strategies for working with students with learning disabilities (Cripps & Zyromski, 2009).

In Table 8, the paired sample correlation of the performances of EDU-AT-TECH clients’ statistical correlations are identified and discussed.

Table 8 shows the EDU-AT-TECH clients’ mean and of a set of scores for each assessment, which is as follows: CBCLi 1 is 58.61, CBCLi 2 is 51.48, CBCLe1 is 68.87, CBCLe2 is 57.64, CBCLt1 is 65.62, CBCLt2 is 55.21, PIRc1.1 is 68.88, and PIRc1.2 is 75.69.

There is a strong correlation between increase in client overall psychological well-being when behavior therapists and/or teachers administer both the pretest and posttest and use the data to provide interventions for the client.

Table 9 provides a presentation of the statistical analysis of pretest and posttest CBCL scores. Significant differences are identified and discussed.

Table 9 shows that there is a significant difference in means between pretest and posttest CBCL scores, indicating improvement on all three scales: (a) CBCLi 1 and CBCLi2, (b) CBCLe1 and CBCLe2, and (c) CBCLt1 and CBCLt2. For example, with the PIR-GAS, there is a statistically significant increase in posttest scores, indicating improvement.

Table 10 represents an analysis of group statistics of pretests and posttests. The group statistics are discussed in Table 10.

Table 10 shows that there is an increase in post scores for the CBCLi, CBCLe, CBCLt, and the PIRc1.

The EDU-AT-TECH program was developed to address the needs of children from birth to 5 years of age that show signs of autism spectrum disorder issues. The Educational Assistive Technology program was developed to increase parent participation in the evaluation process, rate significant behavior problems identified by the therapist to increase children’s success rate in school. The EDU-AT-TECH program has the following significant and/or positive outcomes: (a) There is a statistically significant increase in PIR-GAS posttest scores, indicating improvement. (b) There is a significant difference in means between pretest and posttest CBCL scores, indicating improvement on all three scales. (c) There is a strong relationship between increase in client overall psychological wellbeing when behavior therapists administer both the pretest and posttest and use the data to provide interventions for the client.

By contrast, there are three main areas where EDU-AT-TECH may want to devise a plan for improvement: (a) In the future, researchers may want to see if there is a correlation between parental consent and clients who withdraw from the program. These data could be useful in maintaining enrollment in the program; (b) researchers would like to decrease the number of students that withdraw transition, age out, and move out of the program; and (c) researchers will need to track parent participation in the evaluation process. With more parent and guardian involvement in the program, the more likely children will complete the program and gain a list of skills to live healthier lives.