Modifying and using assistive/supportive technology in today’s classrooms is vital when trying to ensure educators are meeting the needs of each child. Students in general education often learn to cope with writing tasks, and students with learning disabilities (LD) have difficulties in fulfilling those demands resulting in reduced academic achievement throughout their years in school, but assistive modifications have helped these students in many ways (Hetzroni & Shrieber, 2004). One major goal for educators working with students with LD is to provide appropriate them with support to improve their opportunities to achieve academic and social skills, and assistive technology (AT) is designed to make the learning environment more accessible and for enhancing student’s productivity (Hetzroni & Shrieber, 2004).
Word Prediction Software
Students with LD grapple with reading, spelling, and/or difficulties with writing and typing use fantastic technologies such as iPhones and Androids word prediction programs and text to voice to help complete assignments to their satisfaction (Nielsen, L. (2011). Text-to-voice also allows assisting students with LD that are struggling with supportive capabilities to checking their spelling and grammar in addition to improving reading and writing comprehension skills (Nielsen, 2011). Grade school comes with its own set of issues, and for students with LD, this period can become especially difficult when trying to grasp the written form which can turn into a demanding task. Word prediction software used with students who have difficulty with spelling, punctuation, and syntax; and the program aims to reduce the mechanical demands of writing and increase motivation for those children with specific LD’s (Silio & Barbetta, 2010).
Text-to-speech, also known as text-to-voice a software application designed to use a computerized voice to convert normal language text into audible speech and has been considered more effective than either the use of a human reader (Silio & Barbetta, 2010). When text-to-voice is combined with the use of word prediction, they have shown to be more effective in supporting the writing of students with specific LD than only using either in isolation (Silio & Barbetta, 2010). Assistive technologies have allowed students with LD to compensate for skills such as reading, organization, memory, or math problems and to enhance their functionality within their environment (Hetzroni & Shrieber, 2004).
Computer software can offer students with LD immediate spelling assistance and text-to-voice with appropriate revisions (Williams, 2002). One software model, Write: OutLoud is designed to provide the student with speech-feedback that enables the computer to read selected sections of text to students as the software highlights each word as it is being read aloud (Williams, 2002). With a focus on accountability, this model focus on accessibility and accommodations through technology supports implemented through a Universal Design for Learning (UDL) which is crucial to ensure students can show what they know (Johnson, n.d.). Write: OutLoud also ensure students have appropriate universal tools, designated supports, and/or accommodations to best support each student’s needs throughout the school year (Johnson, n.d.). In addition to the student being able to hear what is being typed, the program can also be used for proofreading finished work, can be set to speak each letter typed, speak words, sentences, or paragraphs with the additional benefit of a customization option to ensure culturally responsiveness (Heinisch, 2001).
The Co: Writer also develop by Don Johnson, is a program designed to provide spelling and writing assistance to both emerging and experienced writers with its primary feature being word prediction (Mirenda, Turoldo, & McAvoy, 2006). Additional supports for grade school children include features such as flexible spelling, phonetic spelling, linguistic word prediction, automatic grammar and punctuation assistance during text composition, the option to creating topic dictionaries of specialized words, or using one of several topic dictionaries that come with the program (Mirenda, Turoldo, & McAvoy, 2006).
Adapted keyboards and specialized software products that provide writing support are commonly used in schools and provide additional support for students with physical and learning disabilities (Mirenda, Turoldo, & McAvoy, 2006). In addition to LD, physical disabilities, handwriting may not be an option due to limitations in motor control, difficulty forming letters, illegible writing, or slow speed and assistive technology is essential in providing effective materials and assessments for those students (Tumlin & Heller, 2004). Models such as the ones stated are not intended to teach different skills, but is an enhancement that fits nicely into existing programs and curriculums and allow students with physical and learning disabilities additional tools to support inclusive learning (Williams, 2002).
Issues that have been noted as one article suggests most students with specific learning disabilities have reading and writing delays, however, in the elementary years, students may not need additional support such as assistive technologies, word prediction, spell check, graphic organizers, or books on tape (Zascavage & Winterman, 2009). I struggled to find studies on Write:OutLoud and the resources were limited, and one source notes there are only small bodies of research available that has examined the impact of various features of word processing and word prediction programs such as Co: Writer on the writing of students with LD ((Mirenda, Turoldo, & McAvoy, 2006).
Heinisch, B. (2001). Case studies using Write:Outloud. Australian Journal Of Learning Disabilities, 6(3), 28. doi:10.1080/19404150109546677
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(2), 143-154.
Johnson, D. (n.d.). Write:OutLoud testing accommodations. Retrieved from http://donjohnston.com/testing-accommodations/.
Mirenda, P., Turoldo, K., & McAvoy, C. (2006). The impact of word prediction software on the written output of students with physical disabilities. Journal Of Special Education Technology, 21(3), 5-12.
Nielsen, L. (2011). 25 incredible assistive technologies. Retrieved from http://theinnovativeeducator.blogspot.com/2011/09/25-incredible-assistive-technologies.html.
Silio, 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(4), 17-32.
Tumlin, J., & Heller, K. W. (2004). Using word prediction software to increase typing fluency with students with physical disabilities. Journal Of Special Education Technology, 19(3), 5-14.
Williams, S. C. (2002). How speech-feedback and word-prediction software can help students write. Teaching Exceptional Children, 34(3), 72.
Zascavage, V., & Winterman, K. G. (2009). What middle school educators should know about assistive technology and universal design for learning. Middle School Journal, 40(4), 46-52.