This article is an excerpt from the LD@school learning module Technology for All: Supporting Students with LDs by Integrating Technology into Classroom Instruction. Click here to access this module.
Writing is one of the most complex tasks for all students, and particularly for students with LDs. In this article, we will consider four stages of the writing process, planning, composing, revising, and sharing, and technological tools that prove effective at each stage. For each stage, educators may select different technological tools depending on the learning objectives targeted.
The first step, planning, consists of:
- ensuring that students understand the instructions and expectations;
- activating prior knowledge related to content and form;
- generating ideas, organizing them, and selecting the most relevant ones; and
- developing an outline that will allow students to move on to the composition stage.
One type of technological tool that is extremely helpful at this stage is visual learning software. This technology gives more freedom to students when organizing their thoughts than a pen and paper method. Some programs, such as Mindomo, allow users the ability to turn diagrams and mind maps into written outlines. Portions of text can be colour coded to indicate related concepts, and elements can easily be moved around, added to or removed as students reflect on and further develop their ideas.
Examples of visual learning software:
- Inspiration or Kidspiration
- Microsoft Evernote
- Google Docs
Educators can encourage all students to complete the composition phase using word processing software instead of pen-and-paper. When students type their work, they can more easily add, delete, or move sections of text to improve the quality of their work. As a result, they may find it easier to respond to feedback and add elements such as transition words, descriptive adjectives, or complex sentences.
Additionally, encouraging students to type their work allows those who struggle with their handwriting to reduce the amount of effort spent on this task, and instead focus on conveying their ideas effectively and editing their work. Additionally, word processors often have built-in text-to-speech features and automatic spelling and grammar checkers, which provide students with immediate feedback to help them refine their writing at the composition stage.
Other features that can support students during the composing stage of writing include speech-to-text and word prediction.
Examples of word processing software:
- OpenOffice Writer
- Microsoft Office – Word
- Google Docs
- Apple iWork - Pages
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. Programs 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 LDs (Higgins & Raskind, 2000). MacArthur and Cavalier (2004) found that for students with LDs, 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 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 LDs 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 (Peterson-Karlan, 2011) 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. In one particular study (Tam, Archer, Mays, & Skidmore, 2005), children and their families generally found WordQ to be helpful, and reported improved vocabulary use and increased independence, productivity, and motivation to write. 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, 1999); 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.
For the revision stage, there are many editing software options to choose from. For one, electronic dictionaries can support students to correct their spelling and find synonyms to improve their vocabulary. Similarly, for students who have difficulties with spelling, modern spell-checkers can predict the word students are trying to spell as they type, therefore offering instant feedback as well as more accurate suggestions to correct misspelled words.
It is important to note, however, that these tools are not necessarily permitted to all students during assessments and evaluations. For this reason, other writing and revising strategies should also be taught explicitly and alternative tools should be offered.
Examples of editing software:
- Read&Write (for Google Chrome, Windows PCs, iPad, Macs)
- WordQ and SpeakQ
The final stage of a written task involves sharing your work with others, and technology greatly increases opportunities to do just that. First of all, collaboration tools allow students to post their work, read others’ work, and to share constructive feedback with each other. As such, it is best to use these collaboration tools before the final draft so that students can integrate feedback from their peers.
Educators can guide student feedback with prompts, such as:
- Tell your partner what you think is the strongest part of their text.
- Have they completed their work according to the instructions?
- Has your partner provided rich descriptions?
- Is the ending predictable or unexpected?
- Have they included all the elements in the rubric?
Examples of collaboration tools:
- Google Docs
Digital portfolios have similar benefits as the collaborative tools discussed above. These are online portfolios where students can post, organize, and share their work as well as spaces to guide reflection. They have the added benefit of contributing to the development of metacognition and self-esteem.
Examples of digital portfolios:
Finally, there are a variety of software and applications that allow students to produce the work in an interesting format, such as book or newspaper creators. Creating an exciting and professional-looking final product can act as motivation for students who may otherwise tire of the long writing process.
Examples of book and comic creators:
- Book Creator
- UDL Book Builder
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.
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
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
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.
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.
MacArthur, C. A. (1999). Word prediction for students with severe spelling problems. Learning Disability Quarterly, 22, 158–172. doi:10.2307/1511283
MacArthur, C., & Cavalier, A. (2004). Dictation and speech recognition technology as test accommodations. Exceptional Children, 71(1), 43-58. doi:10.1177/001440290407100103
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.
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.
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:10.1177/00084174050