PART 2: Better Assistive Technology Decision Making

PART 2: Better Assistive Technology Decision Making Through Research By Penny Reed

research

PART 2: Better Assistive Technology Decision Making Through Research

In the first article of this two-part series, I briefly reviewed some of the major findings in research about AAC, power mobil- ity and AT for individuals with significant cognitive disabilities. In this second part, the focus is on research about the use of AT to support reading and writing for students with high incidence disabilities.

There is a learning curve to using TTS, not just its operation, but how to make it work effectively for the individual student. Some students with similar disabilities may be more skilled at decoding than others and may benefit differently from TTS. Some may have additional diagnoses, such as attention deficit/ hyperactive disorder, which may affect their reading perfor- mance. In addition, personality and social factors interact with each student’s disability and may either facilitate or inhibit TTS use. TTS increases vocabulary, increases reading speed and pro- vides exposure to correct pronunciation. In two studies Stodden, Roberts, Takahishi, Park, & Stodden (2012) found that TTS needs to be used for at least 40 minutes per week for one semester. They postulated that its use allows more room in active memory for constructing meaning and leaves students less fatigued. One interesting finding about TTS is that students may feel they finish reading tasks more quickly and read more fluently even when they don’t (Meyer & Bouck, 2014). This may be relat- ed to feeling less fatigued after using TTS to access text. Addi- tionally, TTS allows students to customize viewing, interacting and pacing of the text. These enhance student engagement, interest and motivation (Reinking, 2005; Strangman & Dalton, 2005). Using TTS doesn’t mean that students don’t need to be skilled readers; it means the computer has become their decod- ing eyes. Parr (2013) points out that they must then: add expres- sion, reread with fluency, create pictures in their mind, make connections and make sense of it. The Iowa Text Reader Longitudinal study of TTS (Hodapp & Rachow, 2010) found students accessed the computer passag- es using TTS at 160 words per minute, while they read paper probes at 79 words per minute. The researchers alternated con- ditions (TTS vs. paper book) each week on probes to eliminate

AT for Reading for Students with High Incidence Disabilities

Traditional Reading Instruction is designed to support read- ers’ ability to decode and make the connection between the sounds heard and letters read. It leaves behind a group of stu- dents who may never achieve an adequate level of speed, fluen- cy and accuracy. And it leaves the struggling reader with little to no energy or capacity left to figure out the word, make sense of it, and then do something with it (i.e., comprehend or respond) (Hirsch, 2003). About 90% of students with learning disabilities (LD) have significant difficulties in literacy (Vaugh, Linan-Thomp- son, & Hickman, 2003). These students are more likely than their peers to be disengaged from the learning process and to sub- sequently drop out of school (Seo, Brownell, Bishop, & Dingle, 2005). AT to support reading Text-to-speech (TTS) software is the most common AT used for students struggling with reading. It works well for some, but not all. It must be tried for multiple sessions to see if it will make a difference. Programs have varying features, including reading rate, voice type, document tagging (which affects reading order) and dynamic highlighting, so some experimenting to find the best match may be required.

Dr. Penny Reed is an independent consultant who provides consultation and training on a variety of topics related to assistive technology with a special focus on helping school districts improve their delivery of assistive technology services. She is the author of numerous publications about assistive technology services. She can be reached at 1happypenny@gmail.com.

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the effect of bias. When using TTS, students accessed twice as much text within the same amount of time. In the second year of the study, students were able to access twice as much infor- mation with improved comprehension, even when material became more difficult. The use of the TTS allowed students to demonstrate improved comprehension scores on factual and inferential (higher level thinking) comprehension questions and the students moved to more fluid use more quickly the second year (week 7 vs. week 11). Their comprehension also improved. Teachers reported improved academic performance, better on- task behavior and more engagement when using TTS. Wood, Moxley, Tighe, & Wagner (2017) completed a definitive meta-analysis of studies of TTS. They excluded students without identified LD and included single subject design studies. They found the use of TTS significantly increased reading comprehen- sion for students with learning disabilities. Although Moorman, Boon, Keller-Bell, Stagliano and Jeffs (2010) found that TTS increased reading rate and comprehen- sion for two students with learning disabilities, TTS alone is usually not enough. Training is still needed in comprehension because students may have missed the opportunity to learn and practice comprehension skills in the past when they were struggling to decode text. It can help them to think aloud about how to self-question and reflect during and after reading. It has also been found to help when students are actively involved in monitoring their understanding and processing text mean- ing (Edmonds, Vaughn, Wexler, Reutebuch, Cable, Tackett, & Schnakenberg, 2009). Use of TTS should be paired with compre- hension strategy training and must be used for a long enough time period for the student to become skilled in its use before expecting to see results. It is best to talk with each student about how it is working/not working for him or her. Parr (2013) reviewed the research on TTS and suggests that it appears to work best for students with: • Slow or inaccurate decoding that is below their cognitive and intellectual potential (i.e., less than 90% accuracy); • Lower levels of fluency, (i.e., less than 92 words per minute); • Good listening comprehension that can be stimulated by TTS; • A reluctance to read due to low levels of confidence and/or internal motivation; • Pacing and attentional difficulties that can be accommodat- ed or regulated by TTS; and • Those who often require multiple readings of assigned text. Other AT to Support Students Struggling with Reading Graphic Organizers can help students take notes, improve comprehension of content, make connections within and be- tween information and participate more in class (Strangman, Vue, Hall & Meyer, 2004; Gajria, Jitendra, Sood, & Sacks, 2007). In a thorough review of research Manoli and Papadopoulou (2012)

concluded that students with learning disabilities who had the lowest abilities were helped the most by their use. Even the use of E-books has been shown to be beneficial for some students with disabilities because they allow changes of font size that may significantly increase legibility for them. Sie- genthaler, Wurtz, & Groner, (2011) collected eye-tracking data on participants and found a significant decreased fixation on the text when compared to paper books, they found the decreased time of fixation represented an increase in legibility for those students. While some studies have found the use of audio books can improve comprehension when compared to reading (Boyle, Rosenberg, Connelly, Washburn, Brinckerhoff, & Banerjee, 2003) other studies suggest it is possibly better suited to recreation- al reading than text book reading. Daniel & Woody (2010) had students without disabilities listen to podcasts or read a text book. Students initially reported preferring to listen, but on a test two days later the listeners scored 59% while the readers scored 81%. Student’s individual preferences and abilities affect the utility and effectiveness of AT for reading.

AT for Writing for Students with High Incidence Disabilities

65% of students referred for learning disabilities have a writ- ing disability (Mayes, Calhoun, and Crowell, 2000). Smith and Okolo (2010) reviewed the National Assessment of Education- al Progress (2009) and noted that only six percent of students with disabilities scored at a proficient level on writing tests. 46% scored below basic level, and 48% performed at basic level. Stu- dents with LD are more likely to have errors in spelling, punctu- ation, capitalization and word usage. Their writing is more likely to be shorter and illegible (DeLaPaz, 1999). Personal computer spell checkers, digitized text, word pre- diction software, speech recognition and alternative writing tools are the most common computer features used in schools to facilitate writing (Cullen, Richards, & Lawless-Frank, 2008; Bar- betta & Spears-Bunton, 2007). Compared to handwriting, even word processing makes a difference. Hetzroni & Shcreiber (2004) found that students had fewer spelling errors, fewer reading er- rors and improved organization and structure when using the computer. MacArther, Graham, Schwartz, and Schafer (1995) found that improved performance depends on how well stu- dents are trained to use the features. Batorowicz, Missiuna, & Pollock, (2012) did a very thorough review of the research on AT for writing. They looked at word processing software, spell checkers, word prediction, speech recognition, concept mapping/organizing software and multi- media. Although the studies are limited, they suggest a positive influence on quality of written text, organization, transcription and revising. AT combined with instruction yields the most pos- itive results. Collaborating with peers when using technology appears beneficial for both composing and revising. They deter-

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mined that technology motivates children and enhances their opportunities to practice writing.

ger than their writing skills (Li & Hamel, 2003). A good guide is Speech Recognition as AT for Writing (Cochrane & Key, 2014). It can be downloaded from http://pub.lucidpress.com/2f091482- 82da-44a9-b8da-0f9c52f81482/ One of the most compelling reasons to provide AT to stu- dents with disabilities comes from comparing postsecondary outcomes of students with high incidence disabilities who re- ported receiving AT in high school to those who reported not receiving AT (Bouck, E., 2106). Bouck analyzed the data from the National Longitudinal Transition Study-2. She found that 99.8% of the students who received AT graduated versus 79.6% of those who did not receive AT. 80.9% of students who received AT attended a post-secondary institution compared to 40.1% of students who did not receive AT. 80% of those who received AT had a paying job after high school, while only 50.8% of those who did not receive AT had a paying job at the time of the study. While this data does not show a causative relationship, because there is no way to know if there were other significant differenc- es in services or abilities, it does provide a picture of the broad impact of AT use for at least some students with disabilities. Finding AT Research Look for research articles in peer-reviewed professional journals such as Augmentative and Alternative Communica- tion-www.isaac-online.org/en/publications/aac.html, Assistive Technology-www.resna.org, Journal of Research on Technology in Education- www.iste.org, or the Journal of Special Education Technology-https://journals.sagepub.com/home/jst. Then com- pare to find the “best evidence”, evaluate the applicability of re- search to your situation, then use it to make better decisions. Finding a meta-analysis of multiple studies can be very helpful because it gives you an overview of the findings on a specific topic. The material I have included in this two-part series can be found on the National Assistive Technology in Education (NATE) Network website under the AT Research section- https://www. natenetwork.org/. I will periodically update that section, so you can check there for more information. The NATE network web- site is also currently developing a section of information for AT Teams that will include both research and resources, so keep checking there for useful tips and ideas. References Barbetta, P. M. & Spears-Bunton, L. A. (2007). Learning to write: Technology for students with disability in secondary in- clusive classroom. The English Journal, 96(4) 86-93. Batorowicz, B., Missiuna, C. A., & Pollock, N. A. (2012). Tech- nology supporting written productivity in children with learning disabilities: A critical review. Canadian Journal of Occupational Therapy, 79(4), 211-224. Blair, R. B., Ormsbee, C., & Brandes, J. (2002, March). Using writing strategies and visual thinking software to enhance the

Word Prediction The term word prediction may include both word completion (guessing the remainder of a word based on the first letter or two) and true word prediction (guessing the next word based on the current word) aspects. Studies of word prediction software prior to 2003 did not have phonetic spelling, so word prediction was less accurate. However, even older studies showed benefit. Word prediction alone and in combination with TTS have had a positive impact on the written output of students with identi- fied learning disabilities (Silió & Barbetta, 2010; Cullen, Richards, & Lawless-Frank, 2008; Tam, Archer, Mays, & Skidmore, 2005). Most studies look at number of words written, spelling accuracy and writing rubric scores (including total unit length). Graphic Organizers to Support Writing Studies of the use of graphic organizers as AT for writing show increases in number of words written, amount of time spent on planning and common story elements (Blair, Ormsbee, & Brandes, 2002; Sturm & Rankin-Erickson, 2002; Unzueta & Bar- betta, 2012; Gonzalez-Ledo, Barbetta, Unzueta, 2015). Changes in overall organization of the written product were found in some, but not all of these studies. In addition, electronic graphic organizers allow educators to change the visual representation of the images and text, convert the information in a concept map to an outline, and add audio and text and allow students to manipulate text, alternate between concept map and outlin- ing, and insert information. Englert, Wu, and Zhao (2005) found that the 12 students in their study performed significantly bet- ter when using the graphic organizer than without it. Sturm and Rankin-Erickson (2002) found students demonstrated a more positive attitude to the computer based graphic organizer than to the hand drawn graphic organizer or a no organizer condi- tion. Speech Recognition In several studies the use of speech recognition produced passages with more words and fewer errors than handwritten passages (Quinlan, 2004; MacArthur & Cavalier 2004; McCullum, Nation, & Gunn 2014). However, the use of speech recognition requires the ability to plan phrases and sentences and to dictate without stopping to correct every error (Cullen, Richards, & Law- less-Frank, 2008). It has a large impact for some, but not all, stu- dents. McCullum, Nation, & Gunn (2014) looked at total words, total multisyllabic words and correct writing sequences. They determined writing sequences by looked at every pair of words. For some students, changes were dramatic, going from writing 18 words in the pre-test to 118 in the post-test. For others, the performance changes were much smaller. Speech recognition is particularly beneficial for those whose oral skills are stron-

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written performance of students with mild disabilities. In No Child Left Behind: The Vital Role of Rural Schools, 22nd Annual National Conference Proceedings of the American Council on Rural Special Education (ACRES). Reno, NV: ERIC Clearinghouse on Disabilities and Gifted Education. ERIC Document Reproduc- tion Service No. ED463125. Bouck, E. (2106). A National Snapshot of Assistive Technology for Students with Disabilities. Journal of Special Education Tech- nology, 31(1). Boyle, E. A., Rosenberg, M.S,, Connelly, V.J., Washburn, S.G., Brinckerhoff, L.C., & Banerjee, M. (2003). Effects of audio texts on the acquisition of secondary-level content by students with mild disabilities. Learning Disabilities Quarterly, 26, 203-214. Cochrane, D. & Key, K. (2014). Speech Recognition as AT for Writing. Downloaded from http://pub.lucidpress.com/2f091482- 82da-44a9-b8da-0f9c52f81482/ Cullen, J., Richards, S. B., & Lawless-Frank, C. (2008). Using Software to Enhance the Writing Skills of Students with Special Needs. Journal of Special Education Technology, 23(2), 33-43. Daniel, D.B. & Woody, W.D. (2010). They hear, but do not listen: Retention for podcasted material in a class- room context, Teaching of Psychology, 37(3), 199-203, DOI: 10.1080/00986283.2010.488542 DeLaPaz, S. (1999). Composing via dictation and speech rec- ognition systems: Compensatory technology for students with learning disabilities. Learning Disabilities Quarterly 22(3), 173- 182 Edmonds, M.S., Vaughn, S., Wexler, J., Reutebuch, C., Cable, A., Tacket, K., & Schnakenberg, J.W. (2009). A synthesis of reading interventions and effects on reading comprehension outcomes for older struggling readers. Review of Educational Research, 79, 262-300. Englert, C.S., Wu, X., & Zhao, Y. (2005). Cognitive tools for writ- ing: Scaffolding the performance of student through technolo- gy. Learning Disabilities Research and Practice 20(3), 184-198. Gajria,M., Jitendra, A.K., Sood, S., & Sacks, G. (2007). Improving comprehension of expository text in student with LD: A research synthesis. Journal of Learning Disabilities, 40(3), 210-225. Gonzalez-Ledo, M., Barbetta, P.M., Unzueta, C. (2015). The Ef- fects of Computer Graphic Organizers on the Narrative Writing of Elementary School Students with Specific Learning Disabili- ties. Journal of Special Education Technology, 30(1), 29-42. Hetzroni, O.E. & Schreiber, B. (2004). Word processing as an assistive technology tool for enhancing academic outcomes for students with writing disabilities in the general classroom. Jour- nal of Learning Disabilities 37(2). 143-154. Hirsh, E.D., Jr. (2003). Reading comprehension requires knowl- edge – of words and the world: Specific insights into the fourth grade slump and the nation’s stagnant comprehension scores. American Educator, Spring, 10–29. Hodapp, J. B., & Rachow, C. (2010). Impact of text-to-speech software on access to print: A longitudinal study. In S. Seok, E.E.

Meyen, & B. DaCosta (Eds.) Handbook of research on human cognition & assistive technology (pp. 199-219). Li, H., & Hamel, C. M. (2003). Writing issues in college students with learning disabilities: A synthesis of the literature from 1990 to 2000. Learning Disability Quarterly, 26(1), 29-46. MacArthur, C. A., & Cavalier, A. R. (2004). Dictation and Speech Recognition Technology as Test Accommodations. Exceptional Children, 71(1), 43-58. MacArthur, C.A., Graham, S., Schwartz, S.S., & Schafer, W.D. (1995). Evaluation of a writing instruction model that integrated a process approach, strategy instruction, and word processing. Learning Disability Quarterly 18(4), 278-291. Mayes, S. D., Calhoun., S. L., & Crowell, E. W. (2000). Learning Disabilities and ADHD: Overlapping Spectrum Disorders. Jour- nal of Learning Disabilities, 33(5), 417-424 McCollum, D., Nation, S., & Gunn, S. (2014). The effects of a speech-to-text software application on written expression for students with various disabilities. National Forum of Special Ed- ucation Journal, 25(1), 1-13. Meyer, N.K. & Bouck, E. (2014). The impact of text-to-speech on expository reading for adolescents with LD. Journal of Special Education Technology 29(1). 21-33. Moorman, A., Boon, R.T., Keller-Bell, Y., Stagliano, C., & Jeffs, T. (2010). Effects of text-to-speech software on the reading rate and comprehension skills of high school students with specif- ic learning disabilities. Learning Disabilities: A Multidisciplinary Journal, 16(1), 41-49. Parr, M. (2013). Text-to-Speech Technology as Inclusive Reading Practice: Changing Perspectives, Overcoming Barriers. LEARNing Landscapes 6(2), 303-322. Quinlan, T. (2004). Speech Recognition Technology and Stu- dents With Writing Difficulties: Improving Fluency. Journal of Educational Psychology, 96(2), 337. Reinking, D. (2005). Multimedia learning of reading. In R. E. Mayer (Ed.), The Cambridge handbook of multimedia learning, 355–376. New York: Cambridge University Press. Seo, S., Brownell, M., Bishop, A., & Dingle, M. (2005). An exam- ination of beginning teacher instruction in special education in- structional reading practices that result in student engagement. Retrieved from http://www.coe.ufl.edu/copsse/docs/Engage- ment-LDW/1/Engagement-LDW.pdf Siegenthaler, E., Wurtz, P., & Groner, R. (2011). Improving the usability of e-book readers. Journal of Usability Studies, 6(1), 25- 38. Silió, M. C., & Barbetta, P. M. (2010). The effects of word pre- diction and text-to-speech technologies on the narrative writ- ing skills of Hispanic students with specific learning disabilities. Journal of Special Education Technology, 25(4), 17–32. Smith, S. J., & Okolo, C. (2010). Response to intervention and evidence-based practices: Where does technology fit? Learning Disability Quarterly, 33, 257-272. Stodden, R.A., Roberts, K.D., Takahashi, K., Park, H.J. & Stod-

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den, N. J. (2012). Use of text-to-speech software to improve read- ing skills of high school struggling readers. Procedia Computer Science, 14, 359-362. Strangman, N. & Dalton, B. (2005). Using technology to sup- port struggling readers: A review of the research. In D. Edyburn, K. Higgins, & R. Boone (Eds.), The handbook of special education technology research and practice (pp. 545-569), Whitefish Bay, WI: Knowledge by Design. Strangman, N., Vue, G., Hall, T., & Meyer A. (2004). Graphic Organizers and Implications for Universal Design for Learning: Curriculum Enhancement Report. Wakefield, MA: National Cen- ter on Accessing the General Curriculum. (Links updated 2014). Retrieved [February 14, 2019] from http://aem.cast.org/about/ publications/2003/ncac-graphic-organizers-udl.htmlSturm, J. M., & Rankin‐Erickson, J. L. (2002). Effects of hand‐drawn and computer‐generated concept mapping on the expository writ- ing of middle school students with learning disabilities. Learn- ing Disabilities Research & Practice, 17(2), 124-139. Tam, C., Archer, J., Mays, J., & Skidmore, G. (2005). Measuring the outcomes of word cueing technology. Canadian Journal of Occupational Therapy, 72(5), 301–308.

Unzueta, C., & Barbetta, P. (2012). The effects of computer graphic organizers on the persuasive writing of Hispanic mid- dle school students with specific learning disabilities. Journal of Special Education, 27, 15-30 Vaughn, S., Linan-Thompson, S., & Hickman, P. (2003). Re- sponse to instruction as a means of identifying students with reading/ learning disabilities. Exceptional Children, 69, 391–409. Wood, S.G., Moxley, J.H., Tighe, E.L., & Wagner, R.K. (2017). Does use of text-to-speech and Related read-aloud tools im- prove reading comprehension for students with reading dis- abilities? A meta-analysis. Journal of Learning Disabilities, 51(1), 73-84.

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