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Copyright Journal of Special Education Technology 2007:
The purpose of this article is to offer a review of research on the use of assistive technology for students with disabilities and some reflections on the nature of knowledge that is being produced by researchers who are examining these issues. We analyzed studies published in peer-reviewed journals between 2000 and 2006 that investigated the use of assistive technology with students served under IDEA guidelines. We located 122 studies that met our criteria. We summarize the types and age of students with whom these studies were conducted, the outcomes, the types of designs used, and the journals in which the studies were published. We conclude with a discussion of implications for research and practice.
Educational research has been subjected to intense scrutiny over the past five years, culminating in our current focus on scientific research in education (Feuer, Towne, & Shavelson, 2002; Shavelson &Towne, 2002). Special education research has been subjected to these increased expectations, and scholars have crafted standards by which we can judge the quality of research that includes students with disabilities (Brantlinger, Jiminez, Klingner, Pugach, Richardson, 2005; Gersten et al., 2005; Horner, Carr, Haley, & McGee, 2005; Odom et al., 2005; Thompson, Diamond, McWilliam, Snyder, & Snyder, 2005). In this issue, Gersten and Edyburn offer comprehensive standards to guide our evaluation of the quality of research about the use of technology in special education.
Judgments about the quality of research should go hand in hand with a basic understanding of the nature and scope of the research. Research reviews can serve this purpose. By summarizing information across studies, they enable us to draw conclusions about the issues, technologies, and populations about whom we have the most information. In addition, they can illuminate gaps in the extant knowledge base. Technology-based applications develop at a rapid pace, and their implications for the education of students with disabilities are constantly evolving. While keeping abreast of research-based knowledge, therefore, is a challenge (Edyburn, 2000), it is an important endeavor for informing best practices.
Over the past decade, special educators have published a few comprehensive reviews of assistive technology that span a broad range of students with disabilities. However, several of these reviews were conducted more than 10 years ago (e.g., Fitzgerald, 1996; Okolo, Bahr, & Rieth, 1993; Woodward & Rieth, 1993). More recently, Alper and Raharinirina (2006) reviewed 68 studies conducted between 1988 and 2003. About half of them focused on students diagnosed with learning disabilities (LD). Eighty percent were designed to improve the skills of participants. The authors concluded that students with visual impairments were neglected in this body of research, and that future research should include more attention to the relationship between types of assistive technology (AT) and their application to different types of disabilities.
Edyburn (2000, 2003, 2004) has conducted annual "comprehensive one-year reviews" of special education technology research. His reviews have examined both research-based and practitioner-oriented publications and offer insight into issues that are of most interest to the field. Viewed over time, they show both continuities and changes in the attention given to different populations of students and AT. Gersten and Edyburn (this volume) discuss some of the implications of these reviews. Another source that has compiled information about AT research is the Handbook of Special Education Technobgy Research and Practice (Edyburn, Higgins, & Boone, 2005). Many of its chapters include comprehensive reviews of AT use and outcomes for students with different disabilities, as well as across different content areas (e.g., mathematics, social studies, literacy).
However, few recent reviews have undertaken a review of AT research that synthesizes studies across disability categories and types of technology-based applications. This article addresses the need for such a review by examining the complete body of AT research from 2000 to 2006 as undertaken with students served under IDEA guidelines. In doing so, we hope to contribute an additional perspective to our understanding of the research base for AT use in our schools.
In this review, we analyze only those studies that collected empirical data. Although much of the information in the professional literature focuses on issues of practice (see Gersten & Edyburn, this volume), our focus is on the research base, as disseminated in peer-reviewed publications. We acknowledge that this focus represents only one way to represent the state of knowledge in our field, and that much important and informative work is available in publications that discuss product development; explain technology applications; and delineate curricula, models of AT use, and professional development practices. However, our efforts are focused on summarizing the nature of empirical work in the field in an effort to (a) capture the types of research being conducted, (b) highlight strengths and gaps in our knowledge base, and (c) pose questions that can guide future research.
Two aspects of this article warrant a brief explanation. First, we will use the term assistive technology (AT) throughout the paper. However, as explained below, we chose to review only studies that investigated interactive technologies; thus, we excluded work focused on applications that also would fit under the federal definition of AT, including low-technology solutions and devices designed to compensate for functional limitations. second, we did not attempt to evaluate the quality of the research we reviewed. Rather, our emphasis in this paper is on the nature of that research, the topics it addresses, and the students with whom it was conducted.
Method:
Selection of Studies:
We began by searching the electronic databases WilsonSelectPlus and ProQuest, using all possible combinations of these descriptors: technology, special education, disability, and impairment. We examined the results of these searches for papers that met the following criteria.
The study was designated by the electronic database as published in a peer-reviewed journal between 2000 and 2006. Studies published prior to 2000 were excluded, and studies published in 2007 were not available to us at the time this paper was written.
The authors studied the use of AT by individuals with disabilities, with the intent of better understanding or improving academic, social, communication, or behavioral outcomes. In addition, we examined studies that investigated ways to help teacher educators and service providers either learn more about AT or use AT more effectively with students. We did not include studies in which technology was used only as a medium to deliver content to teachers, such as studies in which teachers took part in professional development about literacy instruction in a Web-based course or studies in which preservice teachers learned about a particular disability through a multimedia case study. Although these types of studies used technologies to affect an outcome for students with disabilities, their goals were not those of helping teachers or other service providers use AT in educational settings.
The technology used in the study involved some degree of interactivity. Thus, we did not include studies that used technology in static ways, as was the case in studies of prompting systems, video used only to present instructional content, video feedback, and video modeling. Nor did we include articles that focused primarily on devices used to improve specific physical, sensory, or medical conditions (e.g., cochlear implants). A few studies we examined focused on issues of interface design (e.g., children's preferences for displays and switches). However, the majority of human-factors research located was conducted with adults, and therefore not included.
The study included students served under IDEA 2004 guidelines. We restricted our analyses to studies that included students, aged birth to 21, who were diagnosed with a disability. We did include studies that involved students who were considered at risk for learning or behavioral disabilities. We excluded studies that examined only the use of AT with postsecondary students or adults. However, we included studies that included postsecondary learners and/or adults if any students from birth to 21 also were included in the sample.
The author(s) asked a research question and collected data, in some form, to answer that question. As discussed above, we did not include articles that offered only reports of product development, advice to educators or others about how to use AT, models of AT use or implementation, and presentations of professional development practices. Although reviews of research did not meet this criterion, we examined their reference lists to determine if we had missed any potential articles in our electronic searches. Furthermore, we examined reference lists from relevant chapters in the Handbook of Special Education Technology Research and Practice (Edyburn, Higgins, and Boone, 2005) to locate any studies that might have been overlooked in our search.
Adhering to these criteria, we located 122 studies for analysis, ranging from 12 studies in 2004 to 22 studies in 2002. Despite our
efforts to conduct a thorough search, we recognize that, inadvertently, we may have overlooked some studies that met our criteria. However, we are confident that our search procedures were sufficient to capture the majority of the research articles published between 2000 to 2006.
Analysis of the Studies:
We read the abstract of each study identified in our searches to determine if it met the above criteria. For those studies that did, we examined the article further to obtain the following information.
Target group. This category represents the group of individuals with disabilities for whom the technology applications investigated in the study were intended. For each study, we coded one primary disability group (e.g., learning disabilities, mild disabilities). In some cases, the target group was different from the study participants. For example, students without disabilities were the participants in some studies that sought to examine their attitudes toward or opinions of students who used augmentative and alternative communication (AAC). Hence, we coded the target group for these studies speech/language disability. Furthermore, although teacher education students and service providers were often the sole or primary participants in a study, we coded the intended beneficiaries of the intervention or technology applications provided to the adult participants.
Some authors studied specific diagnostic categories, others used cross-categorical designations (e.g., mild disabilities, severe disabilities). Using the authors' descriptors of their participants, we recorded, for each study, one or more of 13 different target groups: (a) disabilities in general, (b) LD or reading disabilities, (c) cognitive disabilities, (d) speech/language disabilities, (e) physical disabilities, (f) behavior disabilities, (g) severe disabilities/ multiple/developmental disabilities, (h) mild disabilities, (i) visual impairment, (j) ADHD, (k) autism, (1) hearing impairment, and (m) English language learners with disabilities.
Age range. Here, we noted the age of participants in each study. Unlike our coding for the target group (above), we considered the age range of the study participants themselves. Because many studies spanned more than one age range (e.g., preschool and elementary school participants, or middle school through high school participants), we coded multiple age ranges for each study. We used the following ranges in our analysis: (a) early childhood (ages 0-4), (b) elementary school (ages 5-10), (c) middle school (ages 11-14), (d) high school (ages 1521), (e) post-high school, (f) teacher education students, and (g) service providers. The category teacher education students was used to designate participants in a preservice preparation program, and service providers was used to designate study participants who were inservice educators, administrators, related service providers, and family members.
Type of outcome. In this category, we examined the outcomes of primary interest in the study, using broad category labels to capture a variety of related outcomes under the same designation. Several studies focused on several broad outcomes, and we assigned these to multiple categories. Outcomes categories are: (a) communication, (b) employment, (c) functional/self-help skills, (d) implementation, (0 literacy skills, (g) other academics (not literacy), (i) social/emotional, (j) technology knowledge, and (k) other.
Several of these categories warrant additional comment. Technology knowbdge refers to the acquisition of more positive attitudes or improved knowledge or skills about assistive technology use among teacher educators or service providers. Implementation refers to studies that examined the ways in which technology was being used in educational or home settings. Several studies that examined the effectiveness of or students' preferences for specific technology features (e.g., scanning, switches) were coded as other.
Methods. As might be expected, the methods used in the studies were quite diverse. Rather than attempting to assign studies to tightly defined categories, we used a broad categorization scheme that required fewer inferences. Thus, we coded the primary method used in a study as either: (a) descriptive, (b) intra-individual, or (c) comparison. Descriptive studies aimed to describe individual, group, or organizational (e.g., classroom, school, district, program) use of AT and, often, the factors that influenced that use. These studies typically used survey or case study methods. Intra-individual studies collected data that enabled the researcher(s) to compare an individual's performance over time and/or across different conditions. These studies used single-subject designs. Group comparison studies focused on examining differences among groups of students over time or among conditions. Methods included correlational, quasi-experimental, and experimental designs. This category scheme does not imply that certain types of studies were more valuable than others; we believe that all three types of methods provide important information to the field (e.g., Odom et al., 2005). Nor did we attempt to evaluate the quality of the research conducted in these studies.
Results:
Target Group
As shown in Table 1, 17% (n = 21) of the studies we reviewed did not focus on any particular disability group, but rather, explored issues of relevance to students with disabilities in general. Studies that investigated issues related to teacher preparation or the use of technology in a particular school or program are examples of research targeting disabilities in general. Studies that examined a range of students with mild disabilities accounted for 7% (n=9) of this group of studies. Studies designating their target group as students with mild disabilities were typically those investigating the implementation of a technology-based intervention in an inclusive classroom.
Among the studies that focused on a specific disability group, speech and language disability was the most frequent, investigated in 29% (n=35) of the studies in this analysis. The next most frequent target group was learning or reading disabilities, accounting for about 18% (n= 22) of the studies. Between 5% and 10% of the studies focused on severe/multiple/developmental disabilities (n=10) and cognitive disabilities (n=6). No other specific disability group accounted for more than 5% of the studies we reviewed, although the reader should note that any target group might have been included in the general disabilities category.
Age Range:
As shown in Table 2, about two thirds of participants in the studies were in elementary, middle, or high school, with an approximately equal distribution across these age ranges. Over 1 in 10 studies (11%) included children with disabilities in early childhood (ages 0 to 5). Teacher education students and service providers were represented in more than one third (36%) of the studies.
Outcomes:
As shown in Table 3, 39% of the studies addressed the use of technology to improve students' academic skills (i.e., literacy, 32%, other academics, 7%). Studies focusing on the implementation of technology were also prevDUMMY MAINTEXT aLent in this sample, accounting for 23% of the studies reviewed. Student outcomes other than academic skills included social/emotional outcomes (10%), communication skills (9%), and functional/self-help skills (7%), such as purchasing and organizational skills. Also present were studies that focused on preparing professionals to use technology wiTH students who have disabilities (i.e., technology knowledge, 8%). Not surprisingly, given our focus on students served by IDEA, only 2% of the studies focused on outcomes related to employment.
Methods:
As demonstrated in Table 4, group comparison was the most frequently used method, accounting for 40% of the studies we reviewed. The number of group comparison studies nearly doubled between 2005 and 2006, perhaps because of the federal government's emphasis on research that employs experimental designs. Studies that produced descriptive data, primarily through surveys and case studies, accounted for 39% of the research reviewed. Intra-individual comparisons, primarily through singlesubject designs, were used in 21% of the studies.
Literature Scatter:
Edyburn (2000) contended that one way to better understand the evolution of research about special education technology is to examine the range of journals in which the research is published. Table 5 provides information about the journals from which the studies we analyzed were drawn. The 122 studies examined for this review were published in 27 different journals. Two journals accounted for about two thirds of the studies: 40% were published in the Journal of Special Education Technology and 21 % were published in Augmentative and Alternative Communication. The number of publications per journal dropped sharply after that, with no other journals accounting for more than five studies across the course of this six-year review span.
Most papers were published in special education journals. The range of special education journals in which the articles were located is quite extensive, however, spanning journals deigned to appeal to a broad audience (e.g., Exceptional Children), disability-specific journals (e.g., Journal of Visual Impairment and Blindness, Learning Disability Quarterly), and teacher education journals (e.g, Teacher Education and Special Education). Only a handful of studies were published in technology journals (e.g., Learning Media, and Technobgy, Journal of Research on Computing in Education) or journals aimed at more general education audiences (e.g., Reading Research and Instruction).
Discussion and Conclusions:
In this review, we identified 122 articles that met our inclusion criteria; that is, research-based publications about AT for students served under IDEA. We located almost twice the number of research-based articles than did Alper and Raharinirina (2006), who found 68 papers published between 1998 and 2003. Perhaps this discrepancy indicates that the frequency of AT research is on the rise. However, we located substantially fewer articles than Edyburn has in his annual reviews. For example, Edyburn (2000) located 114 articles published in 1999 and 224 articles published in 2003 (Edyburn, 2004). Edyburn synthesized articles that were "judged to be relevant if [they] expressly mentioned technology and individuals with disabilities in the contexts associated with schools and learning" (Edyburn, 2003, p. 7). A comparison of the number of articles we identified over a six-year span to the number of articles found by Edyburn on an annual basis supports the contention that the majority of information about AT addresses "issues of practice" (Gersten & Edyburn, this volume).
Over a decade ago, Okolo and colleagues (Okolo, Cavalier, Ferretti, & MacArthur, 1995) characterized AT research as "scattershot" and lacking much evidence of programmatic foci. With some notable exceptions, the same observation can be applied to the body of work reviewed here. Lines of programmatic research were most evident in studies of AT for students with speech and language disabilities. Nearly one third of the studies reviewed focused on these students, and most of these studies were published in the journal Augmentative and Alternative Communication. The prevalence of students with speech and language disabilities in our sample is partially explained by the degree to which this population uses AAC. However, the body of research conducted with this group of students is notable for its systematic nature. Clear and accumulative lines of research, such as attitudes toward students who use AAC and the organization and displays of AAC devices, were evident among these studies.
In addition, we noted a defined line of research in which students with cognitive disabilities were taught purchasing skills through technology-based applications. However, although many studies addressed the same broad content (e.g., literacy), we found only a few studies about any particular topic. Furthermore, the disabilities and ages of participants varied from study to study, making it difficult to draw conclusions about the efficacy of any particular application or approach.
As might be expected, students with high-incidence disabilities (that is, LD, behavior disorders, attention deficit-hyperactivity disorders, and the noncategorical designation mild disabilities) accounted for nearly onethird of the participants in these studies. It was encouraging to find that many of these studies focused on the implementation or evaluation of AT in general education classrooms. This suggests that, at least for these students, AT is being investigated in the real-life contexts in which it is most likely to be used. However, students with physical and sensory impairments, who are likely to derive extensive benefits from AT, were rarely the focus of these studies. Similarly, Alper and Raharinirina (2006) noted DUMMY MAINTEXT that students with visual impairment were underrepresented in the studies they reviewed. We would concur, but add that students with other sensory and physical impairments also represent a very narrow section of the research base.
When considering the ages of students in these studies, it seems clear that researchers have done a good job investigating issues of relevance across the K-12 range. Furthermore, students from birth to age 4 were included in over 10% of the studies, which suggests that AT is playing an important role in educational issues for very young children. The prevalence of teacher education students and service providers (that is, teachers, related service personnel, and families) also is promising. We have ample documentation that lack of teacher education, professional development, and family involvement are major barriers to more effective use of technology (e.g., Lahm, 2005). Our analysis indicates that researchers are paying attention to these issues.
Literacy skills remain a primary concern of AT researchers, as about one third (32%) of the studies targeted students' literacy skills. Studies of AT implementation also were common among those we reviewed, accounting for 23% of the sample. Implementation studies were primarily descriptive, however, and in only a few cases evaluated the impact of a particular model or set of practices. It was interesting to note that social/emotional issues, which most often entailed investigations of attitudes and social interactions, were the focus of 10% of the studies. This finding suggests that researchers are not only concerned with functional outcomes such as skill development, but also with the social and psychological well-being of the students who use these technologies.
The primary research methods used in the studies were designs that compared groups of students across time or conditions (40%) and designs that offered qualitative information about the use and impact of AT (39%). Single-subject designs also were frequent, evident in 21% of the studies. Such designs have a long history in the field of special education (e.g., Thompson et al, 2005), and seemed well suited in these studies to the questions they addressed.
Although experimental designs are widely considered the best design for documenting the effectiveness of an intervention (Gersten et al., 2005), such designs were rare in this set of studies. We noticed a trend toward more well-controlled studies in 2004 through 2006, with an increasing number of quasi- and experimental designs in more recent studies. Quality standards developed by Gersten and Edyburn (this issue) and others are critical for the field as we attempt to expand the quantity and quality of our research base.
Absent from this body of research were some of the designs that instructional technology researchers have found most useful in investigating the features and impact of technology-based interventions, such as design experiments (Brown, 1992) and designed-based research (Sandoval & Bell, 2004). Similarly, AT researchers' knowledge of single-subject design, a methodology almost absent in the general educational technology literature, could make considerable contributions to more general research about technology's use and impact in educational settings.
Finally, when considering literature scatter, we observed a narrower range of publication outlets than Edyburn has documented in his yearly reviews. Although the studies we analyzed were spread across 27 journals, 60% were published in just two: Journal of Special Education Technology and Augmentative and Alternative Communication. This finding might seem reassuring-keeping abreast of AT research may not require extensive searches of the literature or subscriptions to multiple journals. However, the lack of publications in more general special education and education journals raises the concern that we are "preaching to the choir." Thus, it seems incumbent upon AT researchers to make a stronger effort to inform those educators whose professional interests may not be so closely aligned with AT that this body of research is relevant to their practices on behalf of students with disabilities.
As discussed above, the conclusions one can draw from this review are limited by its scope-interactive technologies for K-12 students with disabilities. Undoubtedly, there is a wealth of other information about AT that is available to special educators, general educators, service providers, teacher educators, and families. Literature about product development and product descriptions, models for AT use, and recommendations for effective practice serves a very important function in informing best practices and in guiding future research. However, based on this review, one might question the strength of the research base on which such information is founded.
To say "we need more research" is to repeat an overused admonition, but we believe such a conclusion is warranted. Our analysis leads us to many of the same conclusions offered by Silver-Pacuilla (2006), which are based on nine forums conducted with AT experts in 2004 and 2005. Among other issues, participants in these forums stressed the need for building capacity in AT research through better communication, multidisciplinary collaboration in the design and conduct of research, and improved teacher education and professional development.
Finally, a wealth of topics awaits the attention of AT researchers. As discussed above, information about the design and efficacy of AT for low-incidence disabilities is minimal, as is any systematic body of research about the design, fit, or impact of specific types of technologybased applications for improving literacy outcomes for students with mild disabilities. We located only a few studies of speech technology (Zhao, this issue) and no studies of emerging technologies such as gaming (Shaffer, this issue) or portable, mobile technologies (e.g., cell phones). As discussed in Bouck, Okolo, and Courtad (this issue), studies about the relationship between students' use of technology at school and at home also are nonexistent. No study we reviewed has the phrase "universal design" in its tide. Furthermore, despite their importance in helping students make optimal use of technologies, only a few studies examined how technology features, such as the interface itself, affected students. These issues seem particularly important as technology applications continue to migrate to the Web, which may affect the ways in which we will be able to learn and access information in the future. The needs and voices of students with disabilities need clearer representation in all of these developments.