The Pennsylvania State University
Kim Hartman (Guest Author)
I am pleased to welcome Kim Hartman as a guest author for Tech Talk. Kim brings a variety of experiences and perspectives to her writing: she is an occupational therapist, a professor at Quinnipiac College in Connecticut, and a doctoral student (with a special interest in learning disabilities) at the University of Connecticut. Kim has had first hand experience in using assistive technology with students with disabilities through her work as a private consultant on assistive technology, and has presented at numerous conference and workshops on this topic.
A postsecondary environment often challenges a student to produce an increased number of written assignments that use professional and technical terminology and are of increasing length and complexity. When creating such texts a critical element is the speed of text entry with correct spelling and syntax. This element may be very difficult for students with specific disabilities.
A successful assistive technology device is one that allows a student with a disability to complete the same assignments in the same time frame as a student who does not have a disability. This article will describe two tools, abbreviation expansion and word prediction, that may be useful in completing assignments by minimizing the barriers of a specific disability on the production of text and allow a student to achieve competitive typing speeds (Newell, Arnott, Booth, & Beattie, 1992).
The usefulness of abbreviation expansion and word prediction for a student must be assessed on an individual basis, and both will require some training of the student. Each product is available in all types of operating systems, and has a growing body of information to support its use in education.
Abbreviation expansion allows the student to assign a letter pattern or abbreviation to a phrase, sentence or even a paragraph. The assigned abbreviation will automatically expand into the complete text item when it is typed with a space before and following the abbreviation. Abbreviations can be used effectively for long vocabulary items or phrases that are used frequently. For example, ast, may be an appropriate abbreviation for assistive technology.
The abbreviations should be short, recognizable and logical in order to facilitate accurate recall of the abbreviation and its meaning. The abbreviation should not be a word that is an actual word that the student may want to use. For example, at would not be an appropriate abbreviation for assistive technology because the student will use at as an actual word.
Abbreviation expansion also can be used as an accommodation for words that are consistently misspelled. For example fr could be used as an abbreviation for friend, and enable the student to correctly spell out friend without having to recite the mnemonic phrase concerning the correct use of I and e. Both of these uses of abbreviation expansion will allow for a decreased number of keystrokes and correct spelling of words, phrases, and paragraphs that are used repeatedly in typing, thus increasing the efficiency of text entry for some users.
The limitations of abbreviation expansion are twofold. Firstly, the abbreviations themselves must be customized to the individual student and not be words that the student may use in the process of text entry. Secondly, the student must actually use the abbreviations. A common mistake is that the student begins to type the phrase and when the typing is complete the student then remembers that the phrase was abbreviated. In assessment and training the student and a professional need to attend to three elements if abbreviation expansion is to be successful: (a) careful identification of the commonly misspelled words or word reversals, (b) creation of abbreviations that are meaningful to the student not the professional, and (c) training of the student to expand the master listing of abbreviations.
Abbreviation expansion may be a useful tool for individuals who have to type the same phrases repeatedly. The programs are usually easy to learn, with the most time consuming aspect being the creation of the abbreviation list which will both not interfere with the use of other words and be logical to the individual student.
Word Prediction is a software program that uses the first few letters typed by an individual to "guess" at the desired word. For example, a student may want to spell "postsecondary", but is unsure of the spelling. After typing the first few letters (e.g., po) a "screen" (a small box containing text) would appear on his computer screen with the following words:
The student visually scans the list, or has the word list read out loud by the word prediction software, and then selects the desired word by entering the number that appears next to the word (e.g., 5). The word will then be placed within the body of the text. If the desired word does not appear on the list produced after the student has entered only one or two letters, the listing will be revised as the student types additional letters for the desired word.
The "rules" used by the software to make decisions about which words to present can be changed by the user (see Hunt-Berg, Rankin, & Beukelman, 1994, for additional information). The software can be directed to present words based upon their frequency of use, or the syntactical context provided by the preceding words. The user can also create specialized word lists for use with a specific writing topic. For example, the student could decide to create a word list to be used to provide predictions for essay writing for an American History class, and predictions would be limited to historical terms (e.g., after typing re, the student would see revolt, revolution, revolutionary).
There can be significant challenges to the effective use of word prediction. Often students will be distracted by the placement of the listing of words on the screen. Vertical and horizontal lists may be used in almost any area of the screen. However, the placement may lead to distraction from the task of text entry, or, alternatively, be so unobtrusive that the student may not utilize the word prediction capabilities. There is no ideal location (Anson, 1997) and several locations may need to be investigated before an exact placement is determined.
The number of words presented in the predicted word list may also need to be adjusted. Some students who have a sophisticated vocabulary may benefit from a longer listing. However, the time required to stop typing and visually scan a long list of words may actually increase text entry time. The task of visual scanning itself may be fatiguing to students with some disabilities. Lastly, the time delay factor that occurs while waiting for the word prediction list to appear may lead to frustration and decreased use of the software. All of these elements should be considered when assessing a student's need for word prediction.
Sometimes professionals expect word prediction to immediately improve the speed of text entry, and this is not always the case. Anson (1993) reported that for those people who were touch typists word prediction slowed down text entry. Text entry speed improved with word prediction for those individuals who looked at the screen while typing or who had some motor incoordination that limited quick sequential key depression (Tyvand, Endestad, Pedersen, & Heim, 1994).
In summary, both abbreviation expansion and word prediction may be useful assistive technology tools to increase text entry speed, decrease spelling errors, and decrease errors where letters are consistently reversed or omitted. The impact will be unique to the individual student (Koester & Levine, 1996), but both seem to be most successful for students who are not touch typists and look back and forth from the screen to the keyboard while typing, who have difficulty coordinating the movements necessary for efficient typing or have a muscular fatigue concern, and who use phrases or words repeatedly.
A brief description of these and other software resources is available at: http://www.edc.org/FSC/NCIP/TAM.html
Typelt4Me R. Ettore
67 Rue de la Limite
Help U Type for Windows World Communications
245 Tonopah Drive
Fremont, CA 94539
KeyCache OMS Development
1921 Highland Avenue
Wilmette, IL 60091
Kimberly Hartmann, MHS, OTR/L, FAOTA
Assistant Professor and Chair, Occupational Therapy
Hamden, CT 06518
Private Consultant in Assistive Technology
Anson, D. (1993). The effect of word prediction on typing speed. American Journal of Occupational Therapy, 47, 11-16.
Anson, D. (1997). Alternative Computer Access. Philadelphia, PA: F. A. Davis.
Horstmann, H. M. & Levine, S. P. (1991). The effectiveness of word prediction. Proceedings of the 14th Annual RESNA Conference, 11, 100102.
Hunt-Berg, M., Rankin, J. L. & Beukelman, D. R. (1994). Ponder the possibilities: Computer supported writing for struggling writers. Learning Disabilities Research and Practice, 9, 169-178.
Klund, J. & Novak, M. (1997). If word prediction can help, which program do you choose? Technology Special Interest Section Quarterly, 7, 1.
Koester, H. H.,& Levine, S. P. Effect of a word prediction feature on user performance. Augmentative and Alternative Communication, 12, 155-168.
Newell, A. F., Arnott, J. L., Booth, L., & Beattie, W. (1992). Effect of the "PAL" word prediction system on the quality and quantity of text generation. Augmentative and Alternative Communication, 8, 304-311.
Tyvand, S., Endestad, T., Pedersen, D. & Heim, J. (1994). Improved user interface for word prediction. Proceedings of the 17th Annual RESNA Conference, 14.
On The Net
The DSSHE-L Listserv has served many purposes in the past five years, as an informational "Town Hall", as a place where products are critiqued, and even as an intellectual/emotional release with the occasional humorous anecdote. This summer, however, it served a new purpose, as a vehicle for mobilizing political influence on an important legislative matter. In June of this year before 7:00 a.m. one morning, Jane Jarrow (DAIS) informed the list membership that The Reauthorization of the Rehabilitation Act had been passed by both houses of Congress. She said "it was ushered through very quickly and quietly, tacked on as an amendment to the Workforce Investment Partnership Act (WIPA). The bill has now been sent to a Joint Conference Committee for resolution of differences."
What years earlier would have been one of those situations where you wake up and find that important legislation that affects you had been quietly signed into law, in the age of the Internet, was now merely a call to arms. One version of the bill would have drastically changed the way service providers conducted business, by shifting costs of auxiliary aids from State Vocational Rehabilitation offices on to College and University DSS offices.
Jane's missive directed service providers to a website where the text of the bill could be found, and urged the readers to make their bosses know what the potential impact of the bill might be. By noon of that day, Jane followed up with a web address for folks who wished to contact their congressional representatives via e-mail. At 2:00 p.m. that afternoon, Scott Lissner of Longwood College sent a copy of a memo to the list that he had sent to the decision makers on his campus. He encouraged the list members to feel free to modify it for use on their own campuses.
Memos like that had their desired effect, as College Presidents reacted and spoke with the governmental relations folks at the American Council on Education and other members of the Higher Education Secretariat. Wayne Cocchi of Columbus State Community College stated that "we are getting responses written from all levels of administration on our campus including the President."
Within minutes of midnight on the following Monday, Jane Jarrow updated the list on events that had transpired in Washington. It was evident that the voice of the DSS community was heard, but now a new message had to be sent, that opposition to the Bill was not related to a desire to shirk serving persons with disabilities. She asked for specific information on the level of service that was currently being provided on campuses across the country. The Big Ten weighed in, with Phyllis Thompson of Ohio State and Sam Goodin of Michigan responded with some level of indignation that anyone would question higher education and its commitment to meet the needs of students with disabilities.
Sam, Deborah McCune, Dan Miller, and others responded with information on their institutions, which could then be assembled and presented to decision makers in Washington. Once the information was sent on to Washington, Jan came back on the list (again at around midnight--probably just killing time until Dave's Top Ten) and called off the dogs. She said that the DSS community had been heard, and projected that we would hear within 48 hours what the fate of the legislation might be.
Suzette Dyer of Oklahoma joined the discussion on Wednesday, with the suggestion that the group maintain its momentum, and prepare to begin discussions with Commissioner Fred Schroeder of the VR system. On Thursday the 25th, Jane informed the group that the congressional staff working on the Reauthorization of the Vocation Rehabilitation Act had reached agreement on compromise language for the bill addressing the concerns raised by the higher education community over the previous 10 days. She also included a hotlink to the language of the bill itself, as well as her analysis of it. She also offered the political advice of sharing the news of the victory with fellow administrators on our own individual campuses. On Friday, Brian Rose shared the news that the story had been reported on the Chronicle's Academe Today.
And there it is. Within 11 days our profession could have changed dramatically but for the work of really one informed individual energizing 1,000 informed individuals. Had this legislation appeared in 1990, it may very well had made its way into law, and we would have been fighting it out in court. You can imagine the time it would take to organize a phone tree to reach 1,000 members, let alone implement it. On top of that, the time to call or write our legislators would have left us with a collective response that would have been too little, too late. Instead, with the use of a listserv to reach a broad audience with one message, e-mail to discuss how to proceed, websites to widely disseminate the proposed legislation, and more e-mail to contact our legislators, our collective heard. Now, if we could just get it so that our microwaves would stop blinking 12:00 ...