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Assistive Technology for Students with Learning Disabilities: An Evidence-‐based Summary Prepared by Gabrielle Young, Ph.D., Assistant Professor, Memorial University of Newfoundland and Jeffrey MacCormack, M.Ed., Doctoral Student, Queen’s University
Assistive technology refers to the devices and services that are used to increase, maintain, or improve the capabilities of a student with a disability (Dell, Newton, & Petroff, 2012). While the phrase assistive technology may make us think of computers and computerized devices, assistive technology can also be very low-‐tech. For example, pencil-‐grips (the molded plastic grips that slip over a pencil) are considered assistive technology. Assistive technology that helps students with learning disabilities includes computer programs and tablet applications that provide text-‐to-‐speech (e.g., Kurzweil 3000), speech-‐to-‐ text (e.g., Dragon Naturally Speaking), word prediction capabilities (e.g., WordQ), and graphic organizers (e.g., Inspiration). In comparison to other interventions, assistive technology may have a significant effect in helping students with disabilities progress towards the goals outlined on their Individual Education Plans (Watson, Ito, Smith, & Andersen, 2010). Assistive technology helps in two ways: it can help the student learn how to complete the task and it can help to bypass an area of difficulty. For example, when a student decides to listen to a digital version of a book, they are bypassing an area of difficulty. However, if the student focuses on the computer screen as highlighted words are read aloud, they can learn unfamiliar words. Assistive technology ranges from low-‐ to high-‐tech. Assistive Technology Assistive technology can be used in two ways: to support learning and to bypass a challenging task such as handwriting. Summary In order to be effective, assistive technology needs to be embedded within quality Points instruction.
Benefits of Assistive Technology Laptop Computers and Computerized Devices Laptop computers and tablet devices are beneficial for students with learning disabilities because they are portable and lightweight. For students with handwriting difficulties, being able to take notes on a laptop or computerized device (such as an iPad) can improve the quantity and quality of the notes (Vaughn & Bos, 2009). Using a word processor can help students to complete work that is more organized and includes less spelling errors than handwritten work (Hetzroni & Shrieber, 2004). In addition, students may identify and correct more errors when using spell check than when editing by hand (MacArthur, Graham, Haynes, & De La Paz, 1996; McNaughton, Hughes, & Ofiesh, 1997). However, obtaining personal access to laptops and computerized devices does not ensure engagement and increased academic success (Donovan, Green, & Hartley, 2010). For many students, laptop computers and computerized devices can be too distracting. Teachers and students need to be trained in how to meaningfully integrate technology into academic contexts so that the devices don’t detract from learning (Dell, Newton, & Petroff, 2012).
Computer-‐assisted Instruction Computer-‐assisted instruction refers to software and applications that have been designed to provide instruction and practice opportunities on a wide range of devices (e.g., computer, laptop, iPad, mobile technology). Computer-‐assisted instruction provides immediate and dynamic feedback and students with learning disabilities can benefit from this nonjudgmental computerized drill and practice (Stetter & Hughes, 2010). Computer-‐assisted instruction has been shown to be helpful for students with learning disabilities in spelling and expressive writing skills (Wanzek et al., 2006) as this software can reduce distractibility (Hecker, Burns, Elkind, Elkind, & Katz, 2002), and can help students learn to read (Lee & Vail, 2005) and achieve other academic outcomes (Chiang & Jacobs, 2009). Computer-‐assisted instruction is also an effective way for students with learning disabilities to practice math drills (Bouck & Flanagan, 2009), as students who used computer-‐assisted instruction to practice math skills were able to memorize math facts more easily, and developed a more positive attitude towards math than students who did not use computer-‐assisted instruction (Adcock et al., 2010). Computer-‐assisted instruction provides students with dynamic feedback. Computer-‐ Computer-‐assisted instruction can help students practice spelling and multiplication assisted drills. Instruction In order to prevent the technology from being a distraction, students need to be Summary taught how to use technology to support their learning.
Points
Software Functions Assistive technology can improve the writing skills of students with learning disabilities (Batorowicz, Missiuna, & Pollock, 2012). Assistive technology can help students to bypass the mechanical aspects of writing. Using spell check and grammar features can help students focus on communicating their ideas and students can write with confidence knowing that they can easily make changes. In addition, being able to submit a final assignment that is neater and better organized supports positive self-‐esteem. Text-‐ to-‐speech (e.g., Kurzweil 3000), speech-‐to-‐text (e.g., Dragon Naturally Speaking), word prediction (e.g., WordQ) and graphic organizers (e.g., Inspiration) are four useful software functions for students who struggle with language-‐based learning disabilities. Figure 1: Helping students through assistive technology
We may not consider the default functions of word processors to be ground breaking, but for students with learning disabilities, functions such as spell check and text-‐to-‐speech can be a tremendous help when composing and decoding words.
Text-‐to-‐speech -‐ Text-‐to-‐speech software, such as Kurzweil 3000, can read aloud digital or printed text. This is beneficial as students are more likely to understand text when unfamiliar words are read to them (MacArthur, Ferreti, Okolo, & Cavalier, 2001). Text-‐to-‐speech can have a positive effect on decoding and word recognition (Raskind & Higgins, 1999), as well as reading fluency and reading comprehension (Izzo, Yurick, & McArrell, 2009; Montali & Lewandowski, 1996; Stodden, Roberts, Takahishi, Park, & Stodden, 2012). Text-‐to-‐speech software can be especially helpful for students who retain more information through listening than reading. This software can assist students with monitoring and revising their
typed work, as hearing the text read aloud may assist students in catching grammatical errors that may have otherwise gone unnoticed (Raskind & Higgins, 1995; Rao, Dowrick, Yuen, & Boisvert, 2009; Zhang, 2000). After reviewing the literature, Strangman and Dalton (2005) reported that the use of text-‐to-‐speech software can improve students’ sight reading and decoding abilities. In addition, text-‐to-‐speech software can improve the reading comprehension of individuals with specific deficits in phonological processing (difficulty hearing letter-‐sounds) as students can learn to decode new words when they are highlighted as they are read aloud (Fasting & Halaas Lyster, 2005; Holmes & Silvestri, 2009). Kurzweil 3000 provides reading, writing, studying, and organizational support for students who have difficulty reading or writing (e.g., Elkind, 1998). The use of Kurweil 3000 software also improves students’ perception of their work and their ability to write expressively (Chiang & Jacobs, 2009). Programs such as Kurzweil 3000 may decrease the negative emotions students associate with reading and provide students with a more complete comprehension of the text (Young, 2012), and as a result, text-‐to-‐speech programs are recommended for use along with research-‐supported reading intervention practices.
Speech-‐to-‐text – Writing involves low-‐level transcription skills (e.g., handwriting, spelling, punctuation, and grammar), as well as high-‐level composition skills (e.g., planning, generating content, and revising). Speech-‐to-‐text software transcribes spoken word into computer text, allowing the student to bypass the demands of typing or handwriting; freed from these effortful tasks, students may compose stories that are longer, more complex, and contain fewer errors (Graham, 1999). Speech recognition accuracy improves with use; however, new users can become frustrated with the training process, and they may lack the ability to efficiently edit the program’s text output. Titles such as XpressLab are licensed by the Ministry of Education and can be used to improve expressive oral language for students in grade 7-‐12. Voice recognition software can improve word recognition, spelling, and reading comprehension skills for students with learning disabilities (Higgins & Raskind, 2000). MacArthur and Cavalier (2004) found that for students with learning disabilities, essays dictated using Dragon Naturally Speaking were better than handwritten essays, but essays dictated to a scribe were even better. These authors found a differential impact on students with and without disabilities, providing evidence that this technology removes a barrier based on disability. Word Prediction -‐ Word prediction software was originally designed for students with physical disabilities who experienced difficulty typing. However, word prediction with text-‐to-‐speech is also effective for students with learning disabilities because it reduces the need for handwriting, and improves students’ spelling accuracy and writing skills (Cullen, Richards, & Frank, 2008; Evmenova, Graff, Jerome & Behrman, 2010; Handley-‐More, Dietz, Billingsley & Coggins, 2003; Lewis, Graves, Ashton, & Kieley, 1998; Silió & Barbetta, 2010). In addition, students may find it enjoyable to have the words recommended through word prediction and be able to form sentences without having to worry about spelling and word-‐choice (Evmenova et al., 2010). An analysis of 25 years of research found that word prediction increases transcription accuracy and may also increase word fluency and compositional quality of writing for students with learning and academic difficulties (Peterson-‐Karlan, 2011). In one particular study, children and their families generally found WordQ to be helpful, and reported improved vocabulary use and increased independence, productivity, and motivation to write (Tam, Archer, Mays, & Skidmore, 2005). While there are potential benefits to the use of WordQ, a basic foundation of phonological awareness is required as students who are unable to identify the beginning sound of words will not benefit from using word prediction software because
the user has to provide the first letters of the word (MacArthur, 1999). In addition, word prediction demands a fairly high level of attention to make use of the suggested words (MacArthur, 1998); and as a result, each child must be considered on an individual basis in order to select the appropriate technology for his or her learning needs. Text-‐to-‐speech software helps students to bypass the task of decoding words. Software Seeing individual words highlighted as the text is read aloud may help to improve Summary students’ sight word vocabulary. Points Speech-‐to-‐text software bypasses the tasks of handwriting and spelling, allowing the student to concentrate on developing their ideas and planning their work. Word prediction software can make writing more enjoyable and can increase the quality of expressive writing for students with learning disabilities. You can access a list of Ministry of Education approved software titles at: http://www.osapac.org/db/software_search.php?lang=en. Mid-‐tech Devices Mid-‐tech devices such as audio recorders, portable note takers, mp3 players, calculators, and pentop computers (such as LiveScribe smartpen) can be useful without the cost associated with high-‐tech devices. For example, the AlphaSmart is a note-‐taking device that can provide basic word-‐processing, without the cost related to the purchase and maintenance of a laptop. AlphaSmart devices were discontinued in 2013, but NEO Direct still provides support for users. Figure 2: Exploring technology for students with learning disabilities
While assistive technology can be low or high-‐tech, most of the assistive technology for students with learning disabilities is high-‐tech (Lewis, 1998). Teachers should become familiar with assistive technology and understand how it can be incorporated within their teaching to support an inclusive learning environment.
Graphic Organizers – Graphic organizers benefit individuals who experience difficulty expressing their thoughts on paper as well as visual learners who need to see their ideas mapped out. While graphic organizers completed without technology can help students with learning disabilities to improve the quality of writing (Institute for the Advancement of Research in Education, 2003), electronic versions, such as Inspiration, allow students to arrange their thoughts on the computer screen without worrying about order, level of importance or categories because the text can be easily manipulated. Graphic organizers provide an organizational framework to help writers generate topics and content for writing projects and can assist with the planning and organizational stages of writing, and using concept mapping software can increase the quality and quantity of writing (Sturm & Rankin-‐Erickson, 2002). Using a web-‐based graphic organizer with procedural prompts enabled students to produce better organized and higher quality papers, than they could produce with handwritten organizers (Englert, Wu & Zhao, 2005; Englert, Zhao, Dunsmore, Collings, & Woblers, 2007). Being taught a strategy to plan and organize writing can improve the compositions of students with learning disabilities (MacArthur, 2009). For more information about graphic organizers, please click here.
Pentop computers -‐ Pentop computers, such as LiveScribe smart pens, are cheaper than high-‐tech devices like iPads but can provide text-‐to-‐speech, strategy feedback, and other organizational functions. As cost-‐effective and self-‐regulated reading aides, pentop computers may be a useful tool for students with reading disabilities (Schmitt, McCallum, Hennessey, Lovelace, & Hawkins, 2012). Pentop computers are also useful because they utilize instruction strategies such as providing auditory feedback during composition or math work. Handheld computerized devices that provide feedback have shown to be helpful for students with learning disabilities for essay composition (Bouck, Bassette, Taber-‐Doughty, Flanagan, & Szwed, 2009), and receptive note-‐taking and multiplication skills (Bouck, Flanagan, Miller, & Bassette, 2009). For example, pentop computers are able to provide reminders such as “don’t forget to carry” during multiplication questions (Doughty, Bouck, Bassette, Szwed, & Flanagan, 2013). Calculators and math software-‐ Students with learning disabilities may have a history of academic failure, which contributed to their development of learned helplessness in math. For some students, a fear of failure and low academic self-‐concept can lead to math related anxiety. While the use of calculators can level the playing field for students with learning disabilities, some research has shown that calculators may provide unfair advantage (Bouck & Flanagan, 2009). Graphing calculators may be particularly effective because they provide visual conformation of the graph-‐shape. The added advantage of visual data can be highly motivating for students with learning disabilities (Bethell & Miller, 1998). Math drill programs can be an effective way for students to learn to mentally solve math questions (Adcock et al., 2010), they are also effective in increasing motivation and the addition and subtraction skills of students with dyscalculia (Amiripour, Bijan-‐zadeh, Pezeshki, & Najafi, 2011). Math Trek 1,2,3 is an example of software licensed by the Ministry of Education for use in classroom. You can find the full list of approved software titles here: http://www.osapac.org/db/software_search.php?lang=en. Concept organizers, whether completed electronically or by hand, may contribute Mid-‐tech to better writing in students with learning disabilities. Devices Pentop computers can be used for reading (text-‐to-‐speech), writing (digitizing Summary written words), and math (strategy feedback). Points Calculators can help students with learning disabilities demonstrate their understanding of mathematical computations. Graphing calculators can provide additional support as they verify graph shapes and help solve algebraic equations.
Considerations Much needs to be done to improve the quality of special education technology research (Edyburn, 2009). Little research has been conducted on the use of assistive technology in inclusive schools (Watson, Ito, Smith, & Andersen, 2010), and only a few researchers are conducting systematic, well-‐ designed research that can lead to confident conclusions on how the use of assistive technology affects learning (Edyburn & Gersten, 2007; MacArthur, Ferretti, Okolo, & Cavalier, 2001; Wanzek et al., 2006). In addition, research cannot be produced quickly enough to match the rate of technological innovations, and as a result, educators tend to rely on the claims of the producers of the technologies rather than evidence-‐based research (Blackhurst, 2005). Despite the enthusiasm that may surround the application of assistive technology in the classroom, assistive technology is not a panacea. Lack of common vision, limited training, access to support services, insufficient funding, and lack of teacher time are commonly cited problems in regards to the implementation of assistive technology (Ault, Bausch, & McLaren, 2013; Flanagan, Bouck, & Richardson,
2013; Morrison, 2007; Okolo & Diedrich, 2014). Researchers have noted that there is still an enormous gap between the potential of assistive technology and how much it actually helps (Burne, Knafelc, Melonis, & Heyn, 2011). Assistive technology can reduce students’ dependence on others to read, write, and organize their work (MacArthur, Ferretti, Okolo, & Cavalier, 2001; Mull & Sitlington, 2003). When provided with effective strategy instruction, outlining programs and concept mapping software can help with planning, and word processing, spell check, word prediction, and speech recognition can offer support for transcription and revision (MacArthur, 2009). While assistive technology can support struggling learners, MacArthur (2009) cautions that technology by itself has little impact on learning. In order for students to benefit from the technology, educators must have an understanding of assistive technology and how to embedded it within quality instruction (Batorowicz, Missiuana, & Pollock, 2012; Lee & Vega, 2005; Marino, Marino, & Shaw, 2006; Michaels & McDermott, 2003). Staff Training In a large scale survey study nearly three-‐quarters of respondents indicated that improved staff training and knowledge were the most important actions that could be taken to promote technology use (Okolo & Diedrich, 2014). Assistive technology devices and services have to be coupled with context-‐ appropriate instruction from trained teachers (Specht, Howell, & Young, 2007), as students’ successful implementation of assistive technology is directly related to the knowledge, skills, and dispositions of special education teachers (Michaels & McDermott, 2003). While educators acknowledge the potential of assistive technology, they may feel overwhelmed by the responsibility of understanding and using this technology with their students (Lee & Vega, 2005; Ludlow, 2001). Many teachers feel that they lack the knowledge and support to more fully integrate assistive technology into the curriculum (Okolo & Diedrich, 2014). This is not surprizing given that only a third of special education programs surveyed by Judge and Simms (2009) addressed assistive technology, and few workshops or professional development opportunities exist to continually support teachers’ use of assistive technology during instruction (Lee & Vega, 2005; Ludlow, 2001; Michaels & McDermott, 2003). Teachers’ use and understanding of assistive technology may increase when provided with effective instruction during pre-‐ service education or professional development opportunities (Flanagan, Bouck, & Richardson, 2013; Lee & Vega, 2005). General educators and special educators need to become familiar with assistive and instructional technology so that they can embed this technology within their instruction to meet the needs of all their students (Chmiliar, 2007; Chmiliar & Cheung, 2007; Flanagan, Bouck, & Richardson, 2013). When recommending the use of assistive technology, one must consider how training can be provided for students, parents, and teachers to become competent with the technology, as well as environmental factors that will continue to support the child in using technology (Specht, Howell, & Young, 2007). Funding should be allotted for the training of teachers to effectively facilitate assistive technology use (Burne, Knafelc, Melonis, & Heyn, 2011), and all educators who support an individual student should be knowledgeable about that child’s assistive technology and be able to embed the use of the technology within instruction (Nelson, 2006; Okolo & Diedrich, 2014). Computers shouldn’t be restricted to a specific subject area, and the use of technology should not solely occur within a computer lab; rather, assistive and instructional technology should be an integral part of all subjects and the use of these tools should be built into the curriculum. Schools should encourage teaching staff to assume the role of technology co-‐ordinators as they understand the demands of the curriculum and may be best equipped to find free or low cost educational solutions to help students meet curricular expectations.
Considerations Summary Points
Due to the limited evidence-‐based research, teachers tend to make decision about assistive technology based on claims from the software companies. In order to be effective, assistive technology has to be coupled with quality instruction. Teachers require training to support their implementation of assistive technology.
Examples of Assistive Technology by Domain Receptive
Low-‐ to Mid-‐tech
Mid-‐ to High-‐tech
Notepad – Notepads are an excellent way to record information. Students with learning disabilities (LDs) may appreciate having the information colour-‐coded based on the purpose, topic, or function of the information.
Audio recorders – Audio recorders that store hundreds of hours of audio can be purchased as cheaply as $30-‐$40.
Talking dictionary – Students with LDs can use talking dictionaries to verify definitions and spelling. Talking dictionaries are small enough to be carried in a pencil case and are not as expensive as computers or tablets.
Apps for Mobile Devices Audiobooks – Provides a simple way to listen to many of the best classic books and modern titles. Let me try it.
Speaking
Cue cards – Cue cards provide helpful hints for the oral presentation of information, and the process of composing cue cards can help organize the information before-‐hand.
Reading
Highlighter strips – Translucent rectangles of colour can help eliminate extra visual clutter by blocking out the rest of the text. Sticky notes – Students with LDs may find it useful to summarize the main ideas of the text with sticky notes which can be stuck directly on the page.
Visuwords – This free online dictionary allows students to look up words to find their meanings and associations with other words and concepts. Tell me about it. Let me try it. Prezi – A free 3D graphic organizer which can be used to create presentations. Prezis can be collaborative as students can comment and build upon other Prezis. Tell me about it. Kurzweil 3000 – Text-‐to-‐speech software, such as Kurzweil 3000, can read aloud digital or printed text. Tell me about it. Let me try it.
ShowMe Interactive Whiteboard – In order to reduce anxiety, students may opt to record presentations on their iPad beforehand. Video recordings can be uploaded on YouTube or a more private domain. Tell me about it. Let me try it. Speak Selection –Located in the accessibility features of Apple devices, Speak Selection can be used to read aloud electronic text. Tell me about it.
Storyline Online – A free online streaming video program featuring books read aloud. Each book includes accompanying activities and lesson ideas. Let me try it.
Free Books – This app contains more than 23,000 free books Notes, highlight option, bookmark and dictionary tools are provided. Let me try it.
Project Gutenberg – Over 45,000 free e-‐books. Let me try it.
10 Best PDF Reader Apps GoodReader – This PDF reader allows you to add sticky notes, highlight and take notes. Let me try it.
Writing
Pencil grips – For students who struggle with handwriting, pencil grips can provide a surface that is easier to manipulate. Computerized pens – These pens can automatically transmit handwriting into digital text. Some computerized pens have audio-‐recording functions that allow the writer to listen to specific sections of the audio file by tapping on the written notes.
Wikipedia – The Simple English function on Wikipedia allows content to be “translated” into plain English which is easier to read. Let me try it. Word processing – Functions such as spell check, dictionary options, synonym support, and word-‐prediction features are helpful for students with learning disabilities.
Pages – The Pages app allows you to compose, edit work and share. It also includes word prediction, speech-‐to-‐text, and spell check functions. Let me try it.
iWordQ – iWordQ provides reading assistance, word choice and proof reading functions. Tell me about it. Let me try it.
Dragon Dictation – This easy-‐to-‐use voice recognition application allows you to speak and instantly see your text or e-‐mail messages. You must be connected to the Internet for this application to work. Let me try it.
Reasoning
Graphic organizers – Organizing ideas visually allows students with LDs to see the connections between ideas. Audio recorders – Many students with LD experience difficulty translating oral language into written text. Recording ideas early in the thinking process can provide a record for later recall and clarification.
Math
4-‐function calculator – Depending on the type of work being done, a 4-‐function calculator can be a great help without providing disproportionate advantage to students with LDs.
Inspiration – This software helps students organize ideas visually without the challenge of handwriting or spelling requirements. The content can be instantly translated into outlines for essays or compositions. Tell me about it. Let me try it. Spark-‐Space – This software supports the writing of students who are visual learners through the use of functions such as idea mapping essay writer tool. Tell me about it. Audacity – Audacity is a free software program which allows you to record and edit sounds. Tell me about it. Let me try it. Graphing calculator -‐ Graphing computers can solve complex equations, and the dynamic display screen allows the student to verify the results before solving on paper. Math Dictionary for Kids – An animated, interactive online math dictionary that explains over 600 common mathematical terms in simple language. Tell me about it. Let me try it. Braining Camp – Animated lessons and interactive activities to assess student understanding. Tell me about it. Let me try it. IXL Math -‐ IXL's math practice skills are aligned with pre-‐K through Grade 8 provincial curricula, and students' performance is assessed on each objective. Let me try it. Sumdog – Sumdog's learning engine adapts its math questions to each student's ability. Covering number operations through to simple algebra, it is designed for students age 6 to 14. Tell me about it. Let me try it.
SimpleMind+ – This app allows you to brainstorm and organize your ideas. Completed concept maps can be automatically converted to an outline. Let me try it.
ShowMe and ScreenChomp – These apps provide an interactive whiteboard interface to solve problems. The actions on the screen and audio can be recorded and shared as a video file. Tell me about it. Let me try it.
References Adcock, W., Luna, E., Parkhurst, J., Poncy, B., Skinner, C., & Yaw, J. (2010). Effective class-‐wide remediation: Using technology to identify idiosyncratic math facts for additional automaticity drills. The International Journal of Behavioral Consultation and Therapy, 6, 111-‐123. Amiripour, P., Bijan-‐zadeh, M. H., Pezeshki, P., & Najafi, M. (2011). Effects of assistive technology instruction on increasing motivation and capacity of mathematical problem solving in dyscalcula student. Educational Research, 2(10), 1611-‐1618. Ault, M. J., Bausch, M. E., & McLaren, E. M. (2013). Assistive technology service delivery in rural school districts. Rural Special Education Quarterly, 32(2), 15-‐22. Retrieved from http://search.proquest.com/docview/1420524203?accountid=6180 Batorowicz, B., Missiuna, C. A., & Pollock, N. A. (2012). Technology supporting written productivity in children with learning disabilities: A critical review. Canadian Journal of Occupational Therapy, 79(4), 211-‐224. doi:10.2182/cjot.2012.79.4.3 Bethell, S. & Miller, N. (1998). From an E to an A in first year algebra with the help of a graphing calculator. Mathematics Teacher, 91, 118-‐119. Blackhurst, A. (2005). Perspectives on applications of technology in the field of learning disabilities. Learning Disabilities Quarterly, 28, 175-‐178. doi:10.2307/1593622 Bouck, E. C., Bassette, L., Taber-‐Doughty, T., Flanagan, S. M., & Szwed, K. (2009). Pentop computers as tools for teaching multiplication to students with mild intellectual disabilities. Education and Training in Developmental Disabilities, 44, 367–380. Bouck, E. & Flanagan, S. (2009). Assistive technology and mathematics: What is there and where can we go in special education. Journal of Special Education Technology, 24, 24-‐30. Bouck, E., Flanagan, S., Miller, B., & Bassette, L. (2012). Technology In Action. Journal of Special Education Technology, 27, 47-‐57. Burne, B., Knafelc, V., Melonis, M. & Heyn, P. (2011). The use and application of assistive technology to promote literacy in early childhood: a systematic review. Disability and Rehabilitation: Assistive Technology, 6, 207-‐213. doi:10.3109/17483107.2010.522684 Chiang, H., & Jacobs, K. (2009). Effect of computer-‐based instruction on students’ self-‐perception and functional task performance. Disability and Rehabilitation: Assistive Technology, 4(2), 106-‐118. doi:10.1080/17483100802613693 Chmiliar, L. (2007). Perspectives on assistive technology: What teachers, health professionals and speech language pathologists have to say. Developmental Disabilities Bulletin, 35(1), 1-‐17. Chmiliar, L., & Cheung, B. (2007). Assistive technology training for teachers – Innovation and accessibility online. Developmental Disabilities Bulletin, 35(1), 18-‐28. Cullen, J., Richards, S. B., & Frank, C. L. (2008). Using software to enhance the writing skills of students with special needs. Journal of Special Education Technology, 23, 33-‐44. Dell, A., Newton, D., & Petroff, J. (2012). Assistive technology in the classroom: Enhancing the school experiences of students with disabilities (2nd ed.). Boston, MA: Pearson. Donovan, L., Green, T., & Hartley, K. (2010). An examination of one-‐to-‐one computing in the middle school: Does increased access bring about increased student engagement? Journal of Educational Computing Research, 42, 423-‐441. doi:10.2190/EC.42.4.d Doughty, T., Bouck, E., Bassette, L., Szwed, K. & Flanagan, S. (2013). Spelling on the fly: Investigating a pentop computer to improve the spelling skills of three elementary students with disabilities. Assistive Technology, 25, 166-‐175. doi:10.1080/10400435.2012.743491 Edyburn, D. (2009). Using research to inform practice. Special Education Technology Practice, 11(5), 21-‐ 28. doi:10.1080/09362830902805699
Edyburn, D., Gersten, R. (2007). Defining quality indicators in special education technology research. Journal of Special Education Technology, 22(3), 3-‐18. doi:10.1598/RRQ.42.1.7 Elkind, J. (1998). Computer reading machines for poor readers. Perspectives International Dyslexia Association, 24, 9-‐13. Englert, C. S., Wu, X., & Zhao, Y. (2005). Cognitive tools for writing: Scaffolding the performance of students through technology. Learning Disabilities Research and Practice, 20, 184-‐198. doi:10.1111/j.1540-‐5826.2005.00132.x Englert, C. S., Zhao, Y., Dunsmore, K., Collings, N. Y., & Woblers, K. (2007). Scaffolding the writing of students with disabilities through procedural facilitation: Using an Internet-‐based technology to improve performance. Learning Disability Quarterly, 30, 9-‐29. doi:10.2307/30035513 Evmenova, A., Graff, H., Jerome, M., & Behrmann, M. (2010). Word prediction programs with phonetic spelling support: Performance comparisons and impact on journal writing for students with writing difficulties. Learning Disabilities Research & Practice, 25(4), 170–182. doi:10.1111/j.1540-‐ 5826.2010.00315.x Fasting, R. B., & Halaas Lyster, S. (2005). The effects of computer technology in assisting the development of literacy in young struggling readers and spellers. European Journal of Special Needs Education, 20(1), 21-‐40. doi:10.1080/0885625042000319061 Flanagan, S., Bouck, E. G., & Richardson, J. (2013). Middle school special education teachers’ perceptions and use of assistive technology in literacy instruction. Assistive Technology, 25(1), 24-‐30. doi:10.1080/10400435.2012.682697 Forgrave, K. (2002). Assistive technology empowering students with learning disabilities. Assistive Technology, 75, 122-‐126. doi:10.1080/00098650209599250 Graham, S. (1999). The role of text production skills in writing development: A special issue. Learning Disabilities Quarterly, 22, 75-‐77. doi:10.2307/1511267 Handley-‐More, D., Dietz, J., Billingsley, F., & Coggins, T. (2003). Facilitating written work using computer word processing and word prediction. The American Journal of Occupational Therapy, 57, 139-‐ 151. doi:10.5014/ajot.57.2.139 Hecker, L., Burns, L., Elkind, J., Elkind, K., & Katz, L. (2002). Benefits of assistive reading software for students with attention disorders. Annals of Dyslexia, 52, 243–272. doi:10.1007/s11881-‐002-‐ 0015-‐8 Hetzroni, O. E., & Shrieber, B. (2004). Word processing as an assistive technology tool for enhancing academic outcomes of students with writing disabilities in the general classroom. Journal of Learning Disabilities, 37, 143-‐154. doi:10.1177/0022221940403 Higgins, E. L., & Raskind, M. H. (2000). Speaking to read: A comparison of continuous vs. discrete speech recognition in the remediation of learning disabilities. Journal of Special Education Technology, 15, 19-‐30. Holmes, A., & Silvestri, R. (2009). Text-‐to-‐voice technology in adult aboriginal sample with reading difficulties: Examination of the efficacy. Toronto, ON: Aboriginal Office of the Ministry of Education and Ministry of Training, Colleges, and Universities. Institute for the Advancement of Research in Education. (2003). Graphic organizers: A review of scientifically based research. Prepared for Inspiration Software at AEL. Izzo, M., Yurick, A., & McArrell, B. (2009). Supported eText: Effects of text-‐to-‐speech on access and achievement for high school students with disabilities. Journal of Special Education Technology, 24, 9-‐20. Judge, S., & Simms, K. A. (2009). Assistive technology at the pre-‐service level. Teacher Education and Special Education, 32, 33-‐44. Langova, Anna. (n.d.) Word help. [Photograph] Retrieved from http://all-‐free-‐download.com/free-‐ photos/word_help_185278_download.html
Lee, Y., & Vail, C. O. (2005). Computer-‐based reading instruction for young children with disabilities. Journal of Special Education Technology, 20, 5–18. Lee, Y., & Vega, L. A. (2005). Perceived knowledge, attitudes and challenges of AT use in special education. Journal of Special Education Technology, 20, 60-‐63. Lewis, R. (1998). Assistive technology and learning disabilities: Today’s realities and tomorrow’s promises. Journal of Learning Disabilities, 31, 16-‐26. Lewis, R., Graves, A., Ashton, T., & Kieley, C. (1998). Word processing tools for students with learning disabilities: A comparison of strategies to increase text entry speed. Learning Disabilities Research and Practice, 13, 95-‐108. Ludlow, B. L. (2001). Technology and teacher education in special education. Disaster or deliverance? Teacher Education and Special Education, 24, 143-‐163. doi:10.1177/088840640102400209 MacArthur, C.A. (1998). Word processing with speech synthesis and word prediction: Effects on the dialogue journal writing of students with learning disabilities. Learning Disability Quarterly, 21, 1-‐ 16. doi:10.2307/1511342 MacArthur, C. A. (1999). Word prediction for students with severe spelling problems. Learning Disability Quarterly, 22, 158–172. doi:10.2307/1511283 MacArthur, C. (2009). Reflections on research on writing and technology for struggling writers. Learning Disabilities Research & Practice, 24(2), 93–103. doi:10.1111/j.1540-‐5826.2009.00283.x MacArthur, C., & Cavalier, A. (2004). Dictation and speech recognition technology as test accommodations. Exceptional Children, 71(1), 43-‐58. doi:10.1177/001440290407100103 MacArthur, C. A., Ferretti, R. P., Okolo, C. M., & Cavalier, A. R. (2001). Technology applications for students with literacy problems: A critical review. The Elementary School Journal, 101(3), 273-‐301. doi:10.1086/499669 MacArthur, C. A., Graham, S., Haynes, J. B., & De La Paz, S. (1996). Spelling checkers and students with learning disabilities: Performance comparisons and impact on spelling. Journal of Special Education, 21, 22-‐42. doi:10.1177/002246699603000103 Marino, M. T., Marino, E. C., & Shaw, S. F. (2006). Making informed assistive technology decisions for students with high incidence disabilities. Teaching Exceptional Children, 38(6), 18-‐25. McNaughton, D., Hughes, C., & Ofiesh, N. (1997). Proofreading for students with learning disabilities: Integrating computer and strategy use. Learning Disabilities Research and Practice, 12, 16-‐28. Michaels, C. A., & McDermott, J. (2003). Assistive technology integration in special education teacher preparation: Program coordinators’ perceptions of current attainment and importance. Journal of Special Education Technology, 18, 29-‐41. Montali, J., & Lewandowski, L. J. (1996). Bimodal reading: Benefits of a talking computer for average and less skilled readers. Journal of Learning Disabilities, 29, 271-‐279. doi:10.1177/002221949602900305 Morrison, K. (2007). Implementation of assistive computer technology: A model for school systems. International Journal of Special Education, 22(1), 83-‐95. Mull, C. A., & Sitlington, P. L. (2003). The role of technology in the transition to postsecondary education of students with learning disabilities. Journal of Special Education, 37(1), 26-‐32. doi:10.1177/00224669030370010301 Nelson, B. (2006). On your mark, get set, wait! Are your teacher candidates prepared to embed assistive technology in teaching and learning? College Student Journal, 40(3), 485 – 494. Okolo, C. M., & Diedrich, J. (2014). Twenty-‐five years later: How is technology used in the education of students with disabilities? Results of a statewide study. Journal of Special Education Technology, 29(1), 1-‐20.
Peterson-‐Karlan, G. R. (2011). Technology to support writing by students with learning and academic disabilities: Recent research trends and findings. Assistive Technology Outcomes and Benefits, 7(1), 39-‐62. Raskind, M. & Higgins, E. (1995). Effects of speech synthesis on the proofreading efficiency of postsecondary students with learning disabilities, Learning Disability Quarterly, 18, 141-‐158. doi:10.2307/1511201 Raskind, M. & Higgins, E. (1999). Speaking to read: The effects of speech recognition technology on the reading and spelling performance of children with learning disabilities. Annals of Dyslexia, 49, 251-‐281. doi:10.1007/s11881-‐999-‐0026-‐9 Rao, K., Dowrick, P., Yuen, J., & Boisvert, P. (2009). Writing in a multimedia environment: Pilot outcomes for high school students in special education. Journal of Special Education Technology, 24, 27-‐38. Schmitt, A., McCallum, E., Hennessey, J., Lovelace, T., & Hawkins, R. (2012). Use of reading pen assistive technology to accommodate post-‐secondary students with reading disabilities. Assistive Technology, 24, 229-‐239. doi:10.1080/10400435.2012.659956 Silió, M. C., & Barbetta, P. M. (2010). The effects of word prediction and text-‐to-‐speech technologies on the narrative writing skills of Hispanic students with specific learning disabilities. Journal of Special Education Technology, 25, 17-‐32. Specht, J., Howell, G., & Young, G. (2007). Students with special education needs and their use of assistive technology during the transition to secondary school. Childhood Education, International Focus Issue, 83, 385-‐389. doi:10.1080/00094056.2007.10522956 Stetter, M. E., & Hughes, M. T. (2010). Computer-‐assisted instruction to enhance the reading comprehension of struggling readers: A review of the literature. Journal of Special Education Technology, 25(4), 1-‐16. Stodden, R. A., Roberts, K. D., Takahishi, K., Park, H. J., & Stodden, N. J. (2012). The use of text-‐to-‐speech software to improve reading skills of high school struggling readers. Procedia Computer Science, 14, 359-‐362. doi:10.1016/j.procs.2012.10.041 Strangman, N., & Dalton, B. (2005). Using technology to support struggling readers: A review of the research. In D. Edyburn, K. Higgins, & R. Boone (Eds.), Handbook of special education technology research and practice (pp. 325-‐334). Whitefish Bay, WI: Knowledge by Design, Inc. Sturm, J. M., & Rankin-‐Erickson, J. L. (2002). Effects of hand-‐drawn and computer-‐generated concept mapping on the expository writing of students with learning disabilities. Learning Disabilities Research and Practice, 17, 124-‐129. doi:10.1111/1540-‐5826.00039 Tam, C., Archer, J., Mays, J., & Skidmore, G. (2005). Measuring the outcomes of word cueing technology. The Canadian Journal of Occupational Therapy, 72(5), 301-‐308. doi:10.1177/000841740507200507 Wanzek, J., Vaughn, S., Wexler, J., Swanson, E., Edmonds, M., & Kim, A. (2006). A synthesis of spelling and reading interventions and their effects on the spelling outcomes of students with LD. Journal of Learning Disabilities, 39, 528-‐543. doi:10.1177/00222194060390060501 Watkins, M. (1989). Computerized drill-‐and-‐practice and academic attitudes of learning disabled students. Journal of Special Education Technology, 9, 167-‐172. Watson, A. H., Ito, M., Smith, R. O., & Andersen, L. T. (2010). Effect of assistive technology in a public school setting. American Journal of Occupational Therapy, 64, 18-‐29. doi:10.5014/ajot.64.1.18 Vaughn, S. & Bos, C. (2009). Strategies for teaching students with learning and behaviour problems (7th ed.). Upper Saddle River, NJ, Pearson. Young, G. (2012). Examining assistive technology use, self-‐concept, and motivation, as students with learning disabilities transition from a demonstration school into inclusive classrooms. Unpublished Doctoral thesis, Western University, London, Ontario, Canada. Retrieved from http://ir.lib.uwo.ca/cgi/viewcontent.cgi?article=2316&context=etd
Zhang, Y. (2000). Technology and the writing skills of students with learning disabilities. Journal of Research on Computing in Education, 32, 467-‐478. Zcool.com.cn. (n.d.) Modern science and technology picture 02 hd pictures [Photograph]. Retrieved from http://all-‐free-‐download.com/free-‐ photos/modern_science_and_technology_picture_02_hd_pictures_168754_download.html
