Service Delivery for Postsecondary Students with Disabilities: A Survey of Assistive Technology Use across Disabilities
Ofiesh, Nicole S., Rice, Craig J., Long, Ellen M., Merchant, Deborah C., Gajar, Anna H., College Student Journal
As disability service providers become familiar with assistive technology (AT), some devices that were originally designed to meet the needs of a specific disability, are being used with a broader range of individuals (e.g., voice recognition systems for students with learning disabilities). To determine (a) the most frequently used AT devices in postsecondary disability services, and (b) which devices are used across categories of disability; survey data was collected nationwide from postsecondary disability service providers (n=163). Respondents reported frequent use of voice recognition systems, reading machines, frequency modulation systems (FM) and text enlargement systems. Individuals with visual and hearing impairments used AT most frequently. Individuals with psychiatric disabilities and other health impairments used AT the least. Recommendations regarding AT and service delivery are included.
Students with disabilities attending postsecondary institutions are on the rise (Henderson, 1995) and with this trend the use of assistive technology (AT) for students with disabilities has steadily increased (Higgins & Zvi, 1995, Lance, 1996; Raskind, 1993). Legislation that spans the lives of persons with disabilities from birth through adulthood, has underscored the importance of technology for all individuals with disabilities to ensure their access to education. The 1997 reauthorization of the Individuals with Disabilities Education Act (IDEA '97), now mandates the consideration of AT for all children, including those with mild to moderate disabilities, in their education programs. At the postsecondary level the Americans with Disabilities Act (ADA, 1990) and Section 504 of the Rehabilitation Act (Section 504) continue to provide access to the general curriculum, for qualified persons with disabilities, through reasonable accommodations and service delivery that include AT (e.g., books on tape, voice recognition systems). The Technology Related Assistance Act of 1988 (Tech Act) applies to both public and private human service agencies to ensure technological access in work, school, and community settings for persons with disabilities.
Together, this legislation, along with the movement to use technology to promote learning for all students, (Gomes, 2000; Orkwis & McLane, 1998; Rose, Stahl, & Sethuraman, 2000; Silver, Bourke, & Strehorn, 1998), has begun to influence service delivery of AT to a broader range of individuals with disabilities (Bryant, Rivera, & Warde, 1994; Day, 1995; Higgins & Raskind, 1995; Raskind & Higgins, 1998). The application of AT across the continuum of individuals with mild to severe disabilities marks a paradigm shift in how educators view AT, which previously had been viewed almost exclusively within a rehabilitative or remediative context (Warger, 1998), and for only persons with physical and sensory impairments (Bryant & Seay, 1998). This shift is beginning to appear in postsecondary settings. Lance (1996) found not only did postsecondary disability service providers (DSP) perceive their students with disabilities would benefit academically from the use of AT, but the students themselves expressed a need for AT training and greater accessibility to AT devices.
Legislative Impact on Postsecondary Disability Service Providers
The amendments to IDEA '97 now mandate that AT devices and services be considered in the family service plan or education program for all children from infant through twelfth grade, identified as having an exceptional educational need (i.e., who are receiving special education services) (IDEA Regulations, 1999). The Individual Education Program (IEP) team, those responsible for developing reasonable accommodations for elementary and secondary students with disabilities, must consider AT based on the individual's strengths and limitations in relation to educational access (Behrmann, 1994; Bragman, 1987). Without this amendment, public schools have been able to circumvent the consideration, cost and availability of AT for students with mild to moderate disabilities, but with an unclear consequence to a student's academic achievement. Assistive devices were most often considered for students with sensory and mobility impairments who absolutely required the use of such devices to ensure their ability to communicate and/or gain access to education.
Under Section 504 and the ADA, college and university DSP are obligated to provide reasonable accommodations to students with a documented disability to provide equal access to the institution's programs, courses, and activities (Kincaid & Simon, 1994; Thomas, 2000).
While AT use in K-12 settings does not guarantee that these devices will be provided in postsecondary institutions, the mandated consideration of technology suggests these students will enter colleges and universities with IEP documentation to support their need for AT. It is this type of documentation, that disability service providers use, in part, to decide the reasonableness of a request to use AT (Ofiesh & McAfee, 2000). Decisions to provide AT as a reasonable accommodation are ultimately based on precepts from Section 504 and the ADA which balance functional limitations and current impact of the disability and the requirements of the institution.
As an overarching piece of legislation, the Tech Act protects access to technology for individuals who are not in public schools, but who may be working with human service agencies (e.g., persons with disabilities supported through vocational rehabilitation). Due to the Tech Act, these individuals may also enter postsecondary institutions with previous experiences in using AT. Together, these recent pieces of legislation support the implementation of AT for a broader range of persons with doCumented educational needs, who may enter colleges and universities.
Research on AT Across Categories of Disability
Presently there is a strong need for research to validate the use of AT devices for postsecondary populations other than those individuals with sensory and mobility impairments; specifically, learning disabilities, attention deficit hyperactivity disorder (ADHD), psychiatric disabilities, and other health impaired (e.g., chronic fatigue syndrome). A review of the literature identified several studies regarding the effectiveness of AT for postsecondary students with learning disabilities only (Day, 1995, Higgins & Raskind, 1995, 1997; Hartmann, 1996). Part of the problem in carrying out empirical studies with other populations may be (a) the paucity of data on the academic characteristics of students with ADHD, psychiatric disabilities, and those individuals who are other health impaired (OHI), (b) the heterogeneity within categories of disability, (c) the nonstandard criteria used to diagnosis emerging disabilities such as environmental illness and ADHD, and (d) the differing institutional policies regarding acceptable documentation of a disability.
The current study was designed to provide a foundation for further investigation into the practice of using AT across categories of disability in postsecondary settings. To accomplish this goal, an open ended survey question was developed. Specifically, the purpose of this survey question was to determine (a) the most frequently used AT devices in postsecondary disability services, and (b) which devices are used across categories of disability.
Participants were 366 members of Association on Higher Education and Disability (AHEAD) in the United States who were listed as directors or coordinators of services for students with disabilities. Personnel at 2-year community colleges, vocational-technical colleges, and 4-year colleges and universities were surveyed.
A survey designed to gather information on demographics, accommodations, assessment, and transition in postsecondary disability services was developed. The survey was originally sent to 15 DSP at 15 institutions for validation. On the basis of feedback from the DSP, redundant, vague, and leading items were rewritten or eliminated; a revised final survey resulted. The survey included open-ended and multiple choice items. The section on accommodations included an open-ended question and surveyed the use of AT for students with disabilities (see Table 1). Answers to this open-ended question were categorized upon analysis of the surveys, by evaluating the responses of AT devices (e.g., voice recognition systems) by category of disability (e.g., learning disability). Categorization reliability was established between two individuals who classified the responses independently on 55 surveys (33%). Agreement was calculated by dividing the number of interrater agreements by the number of agreements plus disagreements, and multiplying by 100. Interrater agreement on the technology question was 94.5%. Respondents were asked to provide the title of person responding, total enrollment of institution, and number of students with disabilities by category of disability.
A total of 366 surveys were mailed to directors of offices for disability services listed in the AHEAD membership directory (AHEAD, 1997). If more than one person was listed at an institution, only the first individual listed was surveyed. Enclosed with each survey was a cover letter explaining the nature of the study and a return-addressed, stamped envelope. A follow-up mailing was conducted 10 weeks later by a reminder postcard. Responses were collated, coded, and tallied by the fourth author. All data were computed in frequencies and percentages.
A total of 163 surveys (45%) were returned. Ninety-nine professionals responded to the first mailing and 64 responded to the second mailing. Respondents represented 64 two-year schools (including 3 vocational-technical schools) and 99 four-year schools.
Table 2 details the demographics of the sample, including the respondents' titles, total student enrollment of the institution, and total enrollment of students with disabilities by type of disability. The enrollments of the institutions ranged from less than 5000 to greater than 20,000 The largest category of disability was LD and the smallest was both visual and hearing impaired.
Frequency of AT Devices in Disability Services
Table 3 lists the categories of AT and frequency use for all students with disabilities and by disability type. Respondents reported the most frequently used AT devices in postsecondary disability services were voice recognition systems (n=185), reading machines (n=104), FM systems (n=79) and text enlargement systems (n=64).
Frequency of AT Use Across Categories of Disability
As table 3 indicates, most frequently utilized AT device, voice recognition was used across all categories of disability except for individuals with hearing impairments. Individuals utilized reading machines across all categories of disability except by individuals with mobility and hearing impairments. FM systems were rarely used for individuals other than the hearing impaired. Text enlargement was primarily used by individuals with visual impairments and rarely with other disabilities. Of all individuals with disabilities, respondents reported students with psychiatric disabilities and other health impairments used AT the least.
The survey question used in this study produced information about two aspects of AT use in postsecondary settings. These aspects are discussed below in relation to previous research and the contribution of new information. Previous survey research has provided valuable information on the training and knowledge of AT by DSP, and the availability of AT in postsecondary settings (Lance, 1996). However, no previous research was located that provided information on those AT devices commonly used by students with disabilities, or AT use across categories of disabilities. The responses gathered through the present survey add to the literature on AT in postsecondary settings by documenting the (a) frequency of use for a variety of AT devices by postsecondary students with disabilities, and (b) use of AT devices across categories of disability.
Frequency of AT Use
Previous research by Lance (1996) on the accessibility and availability of AT, surveyed DSP by giving them a list of 21 AT devices and asking them to indicate those that were available. The AT devices most frequently identified as available on college campuses were (a) text enlargement software, (b) voice recognition, (c) scanners and optical character recognition software (e.g., reading machines), and (d) magnifying screens (Lance, 1996). The present study differed from Lance's in that DSP were given an open ended question about student use of AT on their campuses rather than a close ended list that surveyed availability of AT on their campuses. Furthermore, differences in the method of data collection and in the manner in which the categories were organized did not allow for a direct comparison of results. Except for the case of FM systems, the AT devices that Lance reported as most often available, are the same as those DSP report as being used most frequently in the present study. The AT devices most frequently identified by DSP as being used by the students they serve are (a) voice recognition, (b) reading machines, (c) FM systems, and (d) text enlargement. This result likely differs from Lance, because FM systems were not included in her list of devices. The findings of this study confirm that students with disabilities use the AT devices that are most often available in postsecondary settings. The frequency with which FM systems are used is a previously undocumented finding.
Assistive Technology Use by Categories of Disability
The second purpose of the survey question was to determine if the most frequently used devices, and others, are used across categories of disability. No previous research from postsecondary settings exists on the actual use of AT across the differing conditions of disability. Furthermore, there is a limited to non-existent research base on the effectiveness of AT with a variety of disabilities.
With an understanding of how service providers currently use technology across conditions of disability, practitioners can maximize the use of their AT holdings and promote accessibility to education for a larger group of students. Without an understanding of these technological options, there is a tendency to limit AT use by previous experience (Ofiesh & Murphy, 1990) even when research supports its effectiveness (Raskind & Higgins, 1998). Additionally, the results of this survey question provide a foundation for future research on the effectiveness of AT with a variety of disabilities by identifying which devices are used across categories of disability.
In the meanwhile, there is a growing movement in the fields of education and special education to consider technology use with a larger range of students with disabilities, other than those who the devices were originally intended to serve (Bragman, 1987; Gomes, 2000; Higgins & Raskind, 1997; Orkwis & McLane, 1998; Raskind & Scott, 1993; Silver et al., 1998). Examples of this movement have also emerged on Listserves, at national conferences (Friend, Schaefer & Thompson, 1997; Gomes, 2000; Rose et al., 2000), as well as in the literature.
Recently, for example, a question was posted on the Disabled Students Services in Higher Education-Listserve (DSSHEL), about whether a student with ADHD was entitled to use a Dragon Dictate (1) system. The conversation centered on typical DSP questions of whether the functional limitations of ADHD could manifest themselves in writing and if so, what were the characteristics. In this discourse, some DSP had not previously considered the use of a voice recognition system for students with ADHD, even though research supports the substantial writing struggles of some students with ADHD and LD (DuPaul & Eckert, 1998; MacArthur, 1998).
Speech recognition software was originally conceived as a communication tool for individuals with limited mobility use and visual impairment (Schepis, Reid, Behrman, 1996). However, recent research has indicated that speech recognition systems have had some success for students with learning disabilities (LD) at the postsecondary level (Higgins & Raskind, 1995; Day, 1995) and children with ADHD (MacArthur, 1998). No empirical research on its effectiveness with emerging disabilities such as psychiatric disabilities and other health impairments, such as environmental illness and chronic fatigue syndrome, has been found.
Nevertheless, the findings of the present study suggest that voice recognition is one of the AT devices used in postsecondary institutions across categories of disability, but most frequently with the populations they were originally intended. For example, students with visual and mobility impairments often use voice recognition and students with visual impairments and LD, reading machines. Almost exclusively students with hearing impairments use FM systems.
When the four most frequently available AT devices are used to assist individuals with other types of disabilities, it is most often with students who have a LD. The prevalence of the use of AT with the LD population, could be due to (a) the large number of students with LD attending postsecondary institutions (Henderson, 1995), (b) the greater knowledge of the functional limitations and manifestations of disability for students who have LD (Hughes & Smith, 1990), and/or (c) the fact that there is research to support the use of AT for students with LD (Day, 1995; Higgins & Raskin, 1995; Higgins & Zvi, 1995). Additionally there is some indication that voice recognition is used with the emerging populations of students with OHI and psychiatric disabilities.
There is a great deal of diversity in the OHI category. It includes individuals with pure physical conditions, which do not effect cognitive functioning (e.g., asthma) and some that do. Some OHI such as environmental illnesses, allergies, and chronic fatigue syndrome can impact reading and writing due to deficits in attention, organization, distractibility, and concentration (Books, 1998; Glines & Rapp, 1988; Simon, Katon, & Sparks, 1990). Students with psychiatric disabilities can have academic deficits due to the same types of cognitive processing problems (Thomas & Grimes, 1987), which can be exacerbated or improved with medication. Thus, voice recognition can be an appropriate accommodation for these students if the functional limitations of their disability impact reading or writing.
Frequency modulation, used predominantly by those with hearing impairments, is an example of a type of technology that could be used with a larger range of students. Two responses indicated that an FM system is used for a student with LD and a student with an OHI.
Likewise devices such as a Trac Ball, or other mouse emulators, appear to be used with only persons with mobility impairments. Students whose functional limitations are specific to fine or gross motor problems might use this type of device to operate a computer more effectively. Conversely, the purpose of some AT devices are so specific, the application of the device to a range of persons with disabilities is limited (e.g., TDD).
Clearly, certain AT devices are being used across categories of disability. Some service providers appear to encourage the use of AT devices for individuals with disabilities based on the functional limitations and characteristics presented by the individual and not necessarily by the general characteristics of a specific type of disability. This is especially important for individuals with ADHD, LD, psychiatric and OHI (e.g., environmental illness) whose functional limitations can vary greatly among individuals. Moreover, with an emerging population of older learners with disabilities related to aging (e.g., hearing loss), as well as a greater number of students on medications with side effects (e.g., anti-depressants, anti-seizure), it is likely that technology will be reinterpreted to meet the needs of a variety of learners with greater frequency.
Disability service providers who are interested in the application of the AT devices in their holdings to a broader range of learners with disabilities may consider the following recommendations:
1. Once the diagnosis and current impact is determined, look beyond the diagnosis of disability to the diagnostician's interpretation of the test findings. Determine if the diagnostician has interpreted the test findings in terms of functional limitations resulting from the disability. The disability may manifest itself through limitations such as fine or gross motor control which impacts writing, visual processing that impacts reading speed, or memory problems that may impact a student's ability to organize thoughts for writing, or comprehend text. Discussions of this nature may be in the examiner's narrative of test behavior, interpretation of test scores, or summary of test findings.
2. Determine how the types of AT devices might give greater access to education based on the individual's functional limitations, as well as the individual's strengths. For example, an individual may have a physical disability with severe, chronic pain that impacts attention span. However, if oral expression is good, a voice recognition system may facilitate both written expression and sustained attention. For individuals who are on medication and have functional limitations of high distractibility and short term memory that impact the ability to stay focused during reading, recorded texts may be a reasonable accommodation, even though there is no LD present. Students with chronic fatigue syndrome may find print enlargement software or a large monitor with increased font size, eases reading and writing tasks, even though there is no visual impairment present.
3. Consider the setting demands of the course and classroom. Setting demands can include printed text, pencil and paper exercises, speeches and oral presentations, graphic design and illustration, research, graphic and visual representations, and linear (conspicuous) problem solving or non-linear (inconspicuous) problem-solving. The bottom line is to evaluate how the characteristics of the AT device can meet the needs of the functional limitations, using the individual's strengths, and addressing the setting demands. Orkwis and McLane (1998) write:
Text: Printed text is "fixed" (not flexible) and creates barriers for many students (e.g., those learning disabilities, low vision, or blindness). Digital text (on a computer) is flexible: it can easily be transformed in size, shape, or color, and can be automatically transformed into spoken speech. Audio: When key information is presented solely in audio form, it creates barriers for students who are deaf [and hearing impaired], who are non-native speakers of the language, who have auditory processing problems, and even those who are merely in a noisy environment. Audio with captions provides flexible alternatives for all of these. (p. 6)
Orkwis and McLane also discuss the perceptual barriers created by graphics or pictorial information for students who are blind or visually impaired. However, their solution--digital images with verbal descriptions--lies a great deal in the hands of the instructor. Interested readers are strongly encouraged to review their publication for more information on curriculum access and a list of AT alternatives to writing, speaking, and drawing. Furthermore, sometimes the setting demands of the course (e.g., poetry and music) cannot be represented in digital format in a way that the writer intended the material to be experienced (Rose et al., 2000).
4. Provide training and ongoing support for new users. For AT to be successful, both DSP and students must be trained on the device and have many opportunities for practice. In the case of voice recognition systems, disability support service providers have noted that successful use is influenced by two key factors: the attitude of the user, and the use of training and practice activities (McNaughton, 1998).
5. Implement periodic review checks. A key factor to the successful use of AT is both user satisfaction and support. Disability service providers need to know if and why an individual continues or stops use of an AT device. This information is needed in order to continue to meet the educational needs of the student and will also provide the DSP with needed information regarding both the usefulness and effectiveness of the device for certain types of functional limitations.
6. Some service providers may be concerned that with a reinterpretation of how some AT devices are used, there will be more student demand than supply. However, DSP must remember that accommodations and service provisions are provided by law to individuals whose functional limitation impacts a major life activity. If the disability service program has a policy to provide accommodations even beyond this, then it is important to understand that although this practice is not legally required, it supports the idea of universal instructional design for all students--for some researchers and practitioners this is a very worthwhile goal.
7. Lastly, but perhaps most importantly, there is a critical need for service providers to collect and disseminate data on the effectiveness of the decisions they make as well as their decision making process. Important data to collect is (a) the perception of effectiveness by the user, (b) how a functional limitation was documented for a specific type of disability (e.g., test names, scores, observations), (c) frequency of follow-up between student and practitioner, (d) amount of training time and support required, and (e) task specific information related to effectiveness of the AT device and the targeted problem (e.g., decrease in reading time, increase in comprehension of material, development of study aides).
Overall, the present study has four limitations. The first is that the respondents were all members of AHEAD. AHEAD is an organization that disseminates literature to members on important topics including AT, and provides ongoing education to disability service providers about access to education. This may limit the generalizability of the results to institutions not affiliated with a professional higher education and disability organization. Second, although this study provides data on the use of AT for individuals with certain disabilities, it does not detail how practitioners supported their decision to do so. This information would be valuable to disability service providers interested in practicing the use of AT in non-traditional ways, as well as a basis for future research. Third, when the survey was developed ADHD was subsumed under the category of LD and thus, does not adequately represent the use of AT with students with ADHD. It is recommended that future surveys of this nature have a separate category for ADHD. Lastly, the survey does not provide information regarding where AT devices are housed on campuses and who is responsible for their purchase. The use of AT across categories of disabilities may be influenced by this administrative, logistical and financial component. For example, some institutions may have open access computer labs equipped with AT and some may have AT housed in areas only for individuals with disabilities. In cases where computer labs have an open access policy, AT need not even be an accommodation.
Without question, more research needs to be conducted regarding the use of technology to meet the needs of a wide variety of learners. Future research should address the areas noted as limitations to this study, as well as the effectiveness of AT with emerging populations, and the decision making process to accommodate with AT. Additional analysis on the use of AT in open access labs by students with and without disabilities could provide information on how useful technological devices are in providing access to education or at least how useful they are perceived to be, by postsecondary students.
Table 1 Survey Question on Technology 31. Please list by category of disability what technology (e.g., voice text, kurzweil reader, brailler, etc.) you provide. Disability category Technology visual impairment -- hearing impairment -- learning disability -- mobility impairment -- psychiatric disability -- other health impairment(s) -- Table 2 Demographic Information Title of person responding n Director of disability services 108 (66%) Other (e.g., dean of student services) 55 (34%) Total enrollment of institution < 5,000 62 (38%) 5,000 - 10,000 47 (29%) 10,000 - 20,000 32 (20%) > 20,000 22 (13%) Average number of students with disabilities by category of disability M Learning Disabilities 111 Other health impairment(s) 43 Mobility impairment 37 Psychiatric disability 22 Hearing impairment 12 Visual Impairment 12 Note N = 163 Table 3 Frequency of Technology Use Across Categories of Disability Assistive Total Visual Hearing Learning Technology f Impairment Impairment Disability f Voice Recognition 185 93 41 Reading Machine 104 68 33 FM System 79 77 1 (a) Text Enlargement 64 61 1 2 Brailler 51 51 TDD 35 35 CCTV 30 28 1 1 Spell Checker 19 19 Software (e.g., word prediction, Inspiration 10 10 (b) other 11 Adaptive keyboard device 10 Trac Ball 7 Real-time technology 6 6 Talking calculator and spell checker 6 6 4 speed tape recorder 6 6 StickyKey software 3 AccessDOS (one handed keyboard use) 2 Adaptive/ motorized work station 2 Human Ware Master Touch 2 2 Assistive Mobilit Psychiatric OHI Technology Impairment Disability Voice Recognition 30 14 7 Reading Machine 2 1 FM System 1 (a) Text Enlargement Brailler TDD CCTV Spell Checker Software (e.g., word prediction, Inspiration (b) other Adaptive keyboard 9 1 device Trac Ball 7 Real-time technology Talking calculator and spell checker 4 speed tape recorder StickyKey software 3 AccessDOS (one handed keyboard use) 2 Adaptive/ motorized work station 2 Human Ware Master Touch 1 The URL for Dragon Dictate is http://www.dragonsys.com/frameset/productframe.html (a) Text enlargement category includes computer screen magnifiers and print enlargement software (b) Other responses with a frequency of 1 included: TalkMan IV, customized grammar checker, specialized software, infrared systems, visual blood pressure device, projection system for microscope, Head Master plus, Handiwork/Handishaft, head-pointer, Comtek, and Cordikeys.
(1) The URL for Dragon Dictate is: http://www.dragonsys.com/frameset/product-frame.html
AHEAD 1997 Membership Directory. (Available to members from the Association on Higher Education and Disability, 100 Morrissey Blvd., Boston, MA, 02125).
Americans with Disabilities Act of 1990, 22 U.S.C.A. [section] 12101 et seq. (West 1993)
Behrmann, M. (1994). Assistive technology for students with mild disabilities. Intervention in School and Clinic, 30,(2). 70-83.
Books, S. (1998, April). Environmentally induced damage to children: A call for broadening the critical agenda. Paper presented at the annual meeting of the American Educational Research Association, San Diego, CA. (ERIC Document Reproduction Service No. ED 420 399)
Bragman, R. (1987). Integrating technology into a student's IEP. Rural Special Education Quarterly, 8, 34-38.
Bryant, B. R., Rivera, D., & Warde, B. (1994). Technology as a means to an end: Facilitating success at the college level. In D. Edyburn & D. Majsterek (Eds.), Technology applications for individuals with learning disabilities. LD Forum Monograph, 19(1), 13 - 18.
Bryant, B. R., & Seay, P. C. (1998). The technology-related assistance to individuals with disabilities act: Relevance to individuals with learning disabilities and their advocates. Journal of Learning Disabilities, 31, 4-15.
Day, S. L. (1995). Computerized voice recognition system effect on writing skills of community college students with learning, disabilities. Unpublished doctoral dissertation, The Florida State University.
DuPaul G. J., & Eckert, T. L., (1998). Academic interventions for students with attention-deficit/hyperactivity disorder: A review of the literature. Reading and Writing Quarterly: Overcoming Learning Difficulties, 14, 59-82.
Friend, J., Schaefer, B., & Thompson, T. (1997, July). Long Range Assistive Technology Planning. Paper presented at the annual conference of the Association on Higher Education and Disability (AHEAD), Boston, MA.
Glines, D., & Rapp, D. (1988). Allergies and problem students. Health Educator, 19, 34 - 38.
Gomes, R. (2000, June). Integrated approach to universal design curriculum at San Francisco State University. Paper presented at Designing for the 21st Century: An International Conference on Universal Design, Providence, RI.
Hartmann, K. (1996, June). Software and Input Devices for More Effective Writing. Paper presented at the Postsecondary Learning Disabilities Training Institute, Newport, RI.
Henderson, C. (1995). College freshman with disabilities. Washington, D. C.: HEATH.
Higgins, E. L., & Raskind, M. H. (1995). Compensatory effectiveness of speech recognition on the written composition performance of postsecondary students with learning disabilities. Learning Disability Quarterly, 18, 159-174.
Higgins, E. L., & Raskind, M. H. (1997). The compensatory effectiveness of optical character recognition/speech synthesis on reading comprehension of postsecondary students with learning disabilities. Learning Disabilities: A Multidisciplinary Journal, 8, 75 - 87
Higgins, E. L., & Zvi, J. C. (1995). Assistive technology for postsecondary students with learning disabilities: From research to practice. Annals of Dyslexia, 45, 124 - 142.
Hughes, C. A., & Smith, J. A. (1990). Cognitive and academic performance of college students with learning disabilities: A synthesis of the literature. Learning Disability Quarterly, 13, 66-79.
Individuals with Disabilities Education Act (IDEA) Amendments of 1997. Public Law 105-17.
Individuals with Disabilities Education Act (IDEA) Amendments of 1997, 20 U.S.C. [section] 300.346, Fed. Reg., 64, 48, 1999.
Kincaid, J., & Simon, J. (1994). Issues in higher education and disability law. Columbus, OH: Association on Higher Education and Disability.
Kurzweil, R. (1998/1999, December/January). Speech technology helps users read, write, and study. Closing the Gap, 17, 16.
Lance, G. D. (1996). Computer access in higher education: A national survey of service providers for students with disabilities. Journal of College Student ]Development, 37, 279-288.
MacArthur, C.A. (1998). From illegible to understandable: How word prediction and speech synthesis can help. TEACHING Exceptional Children, 30, 66-71
McNaughton, D. (1998). Tech Talk: "You talk, it types?"-Not quite: Speech recognition technology for postsecondary students with disabilities. Journal of Postsecondary Education and Disability, 13, (2), 78-81.
Ofiesh, G., & Murphy, B. L. (1990, September). As we see it: CD-ROM and education. CD-ROM End User, 26-29.
Ofiesh, N., & McAfee, J. (2000). Evaluation practices for college students with learning disabilities. Journal of Learning Disabilities, 33, 14-25.
Orkwis, R., & McLane, K. (1998). A curriculum every student can use: Design principles for student access (ERIC/OSEP Topical Brief). Reston, VA: The ERIC Clearinghouse on Disabilities and Gifted Education and The Council for Exceptional Children.
Raskind, M. (1993). Assistive technology and adults with learning disabilities: A blueprint for exploration and advancement. Learning Disabilities Quarterly, 16, 185-196.
Raskind, M. H., & Higgins, E. L. (1998). Assistive technology for postsecondary students with learning disabilities: An overview. Journal of Learning Disabilities, 31, 27 - 40.
Raskind, M. H., & Scott, N. (1993). Technology for postsecondary students with learning disabilities. In S. A. Vogel, & P. B. Adelman (Eds.), Success for college students with learning disabilities (pp. 240 - 279). New York, Springer-Verlag.
Rehabilitation Act of 1973, 29 U.S.C. [section] 794 et seq.
Rose, D., Stahl, M., & Sethuraman, S. (2000, June). Universal Design for Learning(tm)--Applying universal design to media, materials, and methods. Paper presented at Designing for the 21st Century: An International Conference on Universal Design, Providence, RI.
Schepis, M. M., Reid, D. H., & Behrman, M. M. (1996). Acquisition and functional use of voice output communication by persons with profound multiple disabilities. Behavior Modification, 20, 451 - 468.
Silver, P. Bourke, A., & Strehorn, K. C. (1998, September). Universal instructional design in higher Education: An approach for inclusion. Equity and Excellence in Higher Education, 47-51.
Simon, G. E., Kanton, W. J., & Sparks, P. J. (1990). Allergic to life: Psychological factors in environmental illness. The American Journal of Psychiatry, 147, 901-906.
Technology-Related Assistance to Individuals with Disabilities Act of 1988, Pub. L. No. 103-218.
Thomas, S. B. (2000). College students and disability law. Journal of Special Education, 33, 248 - 257.
Thomas, A., & Grimes, J. (Eds.). (1987). Children's needs: Psychological perspectives.
NICOLE S. OFIESH University of Arizona CRAIG J. RICE Providence College ELLEN M. LONG Juniata College DEBORAH, C. MERCHANT Keene State College ANNA H. GAJAR The Pennsylvania State University…
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Publication information: Article title: Service Delivery for Postsecondary Students with Disabilities: A Survey of Assistive Technology Use across Disabilities. Contributors: Ofiesh, Nicole S. - Author, Rice, Craig J. - Author, Long, Ellen M. - Author, Merchant, Deborah C. - Author, Gajar, Anna H. - Author. Journal title: College Student Journal. Volume: 36. Issue: 1 Publication date: March 2002. Page number: 94+. © 2009 Project Innovation (Alabama). COPYRIGHT 2002 Gale Group.
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