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Using technology 'toolkit' to cue written expression: Which features help? What are the effects?

Dr. Colin J. Laine
The University of Western Ontario
1137, Western Road
London, Ontario, Canada.
laine@julian.uwo.ca 

This paper will report on the implementation of and classroom observations related to the introduction and use of word-prediction technology with a range of elementary settings and students. Given the acceleration of educational and employment legislation and policies in the past decade, many educators and employers have turned to technology in the hope of making their environments more accessible for individuals with disabilities. Further complicating the inclusion dilemma, has been the explosion of information and the demand that students and employees to be linguistically capable. Thus, our society is demanding learning and working settings be more inclusive concurrent with pressures on those settings to produce individuals with the competencies to deal with an information-burgeoning work world.

A major concern relating technology designed to assist written expression to students with disabilities, is discerning "what works". Assistance through word completion or word prediction has been extensively promoted in the past decade as a productivity tool for all; but, does its use help a writer’s productivity? Despite vendors’ claims of considerable positive results, the results of research into this area are equivocal (cf, Burger, 1997; Koester & Levine, 1994a, 1994b; Sommers, at al 1994; Treviranus & Norris, 1987; Venkatagiri, 1994). Little research exists regarding the efficacy of implementing specialised access systems to increase personal or professional written productivity for persons with disabilities; its role in learning; or, its impact on independence. This is especially true of word-prediction programs, whether operated manually (by keystroke) or orally (voice-activated). The primary question for this exploratory work was whether or not word-prediction provided more immediate cuing to facilitate word finding & fluency (through word count) and flexibility (through variety of words used) - elements critical to effective written expression (Wiig & Semmel, 1980).

Issues

Several issues from the literature are focussing our attention in relating word-prediction and written expression.

1. Written language in language-delayed students is improved significantly through intervention in Word Finding, Fluency & Flexibility (Corrigan & Stevenson, 1994; Wiig & Semmel, 1980); and, word-prediction (Heinisch & Hecht, 1993; Laine & Follansbee, 1994; MacArthur, 1998).

2. The use of cues in intervention facilitate or improve word recall and retrieval (e.g., German, 1991; Hutchinson, 1983; MacArthur, 1996, 1998; McGregor, 1989; Wing, 1990). However, the word-finding efforts of language delayed individuals result in idiosyncratic patterns of expression in spontaneous speech and writing.

3. Such interventions facilitate language use better if used across the curriculum and in non language-class environments (Wiig & Semmel, 1980).

4. Using word-processing on computers is directly related to significant growth in writing ability and motivation for writing in children with severe learning disabilities (Crealock & Sitko, 1990).

5. There is substantial literature supporting the use of (voice) feedback with word-processing (e.g., Cochran-Smith, 1991; MacArthur, 1996, 1998; Morocco & Neuman, 1986; Sitko, Sitko & McBride, 1991) to improve writing with adolescents with severe learning and language disabilities.

6. Students are effective in using simple fact-retrieval especially when it was menu-driven (Edyburne, 1991).

7. Word-generation and engaged time are key to written-language development - maintaining a semantic flow (e. g., McGregor, 1989; Smith, 1982; Wiig & Semmel, 1980).

The critical task seems to be to get the writer past the wall of words. Placing a word-list in the hands of the writer so that words or phrases emerge as the letters unfold should cue the writer by predicting what word might be wanted - adding an aural cue would be especially useful to visually dysfunctional writers. A package conceived as a writing "toolkit", which would allow users to switch on any of the tools they might need, would provide the most effective, individualised environment. The writer should thus be able to maintain a semantic flow by choosing settings; choosing the word or phrase offered; copying the letter patterns; or using specialised keystrokes. For the technology to be effective, it is critical to ensure that the cueing device is appropriate to the needs that have been assessed (Heinisch & Hecht, 1993).

Current investigations

A word-prediction program was introduced into a variety of settings (special class; resource room; regular classroom); observations focussed on twenty-three students between grades 5 & 8. None of the settings had experienced the particular program before. Teachers were given an initial one-day training on the application by the researcher. Students were introduced to and used the program over at least one term. Observations of the students’ use of and comments about the program, as well as samples of their written work, are being collected over a twelve-week period.

Having the teacher allocate ‘tools’ that are appropriate to the students' needs and abilities has thus far resulted in significant increases in written expression by minimal language proficient students. They are writing more when we divided the writing process into separate components (conceptualising, mechanics, and publishing). As the manual word-prediction users write more, they gain access to a wider range of words which encourages a greater flow of ideas. Given the sample size, the data are being treated as case-studies using baselines. No significant differences have been found so far between males and females nor for age. Although the mean word count is increasing in all cases, there is also considerable increase in the variation among students. Three-quarters of the cases have statistically significant improvements over baseline writing with doubling of fluency (word count) when assisted with WriteAway2000.

Discussion and Conclusions

Reflecting on the original issues, the results of these preliminary studies do point to a better understanding of how word-prediction technology impacts on the classroom and on the workplace. By next spring, we anticipate more concrete results. The technology and the training have resulted in significant improvements to the work environment for the clients.

Students are staying on-task for a greater length of time using computers for writing over pencil and paper. They remain marginally longer on task using WriteAway2000 than when they used another word-processor. While the differences between the two computer programs are not statistically significant thus far, the students are, according to the teacher, more focussed on the task of composing written work while using Writeaway2000. Word-generation (fluency) has been demonstrated as a precursor to effective written expression.

In this study, Fluency (word count) is increasing significantly for all students from notebooks to word-processor to Writeaway2000. Word variety (Flexibility) is not, but we do see an increase in the variety and complexity in the words the students using in their journals and in their general written language activities. Given the degrees of severity of the students’ language delay, one might expect their variety of word use to occur more slowly. The number of spelling errors decreased while using Writeaway2000, but the majority of spelling errors appeared to fall into the category of "typos" (neighbouring keys; repeat key errors; capitalization errors) - which may indicate the students are not proof-reading their work before submitting it to the teacher.

While the students actively search the word lists on the screen for the words prior to asking for help, they do not spend time searching their notebook word-list or a hardcopy dictionary. We see them using Writeaway's word list as a means of confirming their memory for the word's spelling; they read the words lists aloud or listen to them being read back while searching out words. This activity shows they are interested in the words they see on the screen and that reading became an integral to using Writeaway2000. Finally, we found that the students are approaching writing their journals in a more positive way. They did not make the disparaging remarks observed at the start of the study and the disruptive behaviour diminished to minimal levels during journal writing time.

We also found that the greatest acceleration in written expression has been experienced by those students with the more diverse communication abilities; where the teachers were fully conversant with the program and used it themselves; where the teachers have incorporated the writing tool as "normal" for everyone in the class regardless of whether or not they had been identified as exceptional and in need of specialised technology; and where the teachers encouraged the students to use any tools as they thought appropriate. Thus any of the classes might have twenty or thirty students using WriteAway2000 with as many variations in the preferences (tools) being set, but their not showing on the computer screens nor determining the teachers’ responses to the students’ compositions.

Summary

We are finding that using word-prediction technology has been associated with increasing time-on-task and diminishing disruptive behaviour. The use of on-screen dictionaries is acting as a motivator and interest focus for the clients. While this relational behaviour may appear trial-and-error, the act of discovery appears to be reinforced by the personalising nature of the dictionary. Over time the use of the technology became more systematic; frustration appeared to ease, disruption diminished and attention improved. We can only speculate what would have occurred over a longer period of time.

Our major concern at this point is the effect that these systems have had on written composition and problem-solving. Any accommodation that helps persons with disabilities is nothing without an accurately planned, individualised training program. To be effective, we believe that these systems are not self-teaching tools. There are many questions that have to be answered, but we maintain that the use of word-prediction is directly associated with the improvement of our clients’ written expression.

References

Burger, S. R. (1997). Spontaneous communication in augmentative and alternative communication (AAC): A comparison of dynamic display and Minspeak®. Lafayette, IN: College of Wooster, Purdue University.

Cochran-Smith, M (1991). Word processing and writing in elementary classrooms: A critical review of the literature. Review of Educational Research. 61, 1, 107-155.

Corrigan, R., & Stevenson, C. (1994). Children's causal attributions to states and events described by different classes of verbs. Cognitive Development, 9, 235-256.

Crealock, C., & Sitko, M. (1990). Comparison between computer and handwriting technologies in writing training with learning disabled students. International Journal of Special Education. 5, 2, 173-183.

Edyburne, D. (1991) Fact retrieval among disabled and non-disabled students comparing print and electronic encyclopaedias. Journal of Special Education Technology,

German, D. J. (1991). Analysis of children's word-finding skills in discourse. Journal of Speech & Hearing Research, 34, 309-316.

Heinisch, B., & Hecht, J. (1993). Predictive word processors: A comparison of six programs. TAM Newsletter, 8, 4-5,8-9.

Hutchinson, A. (1983). The relationship between word-finding ability and reading with an emphasis on the language-learning-disabled child. Special Education in Canada, 57, 27-29; 31-32.

Koester, H. H. , & Levine, S. P. (1994a). Learning and performance of able-bodied individuals using scanning systems with and without word-prediction. Assistive Technology, 6, 42-53.

Koester, H. H. & Levine, S. P. (1994b). Modeling the speed of text entry with a word-prediction interface. IEEE Transactions on Rehabilitation Engineering, 2, 3, 177-187.

Laine, C. J., & Follansbee, R. (1994). Using word-prediction technology to improve the writing of low-functioning hearing-impaired students. Child Language Teaching and Therapy, 11, 283-297.

MacArthur, C. A.. (1996). Using Technology to Enhance the Writing Processes of Students with Learning Disabilities. Journal of Learning Disabilities, 29, 4, p344-54.

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, 2, p151-66.

McGregor, K. K. (1989) Facilitating word-finding skills of language-impaired children. Journal of Speech & Hearing Disorders, 54, 141-147.

Morocco, C. and Neuman, S. (1986). Word processors and the acquisition of writing strategies. Journal of Learning Disabilities, 19, 243-247.

Sitko, C., Sitko, M., & McBride, A. (1991). Effective methods for improving writing skills with technology. Paper presented at the Closing the Gap 1991 Conference; Minneapolis, Minnesota (October)

Smith, F. (1982). Writing and the writer. New York: Holt, Rinehart & Winston.

Sommers, R. K. et al. (1994). Word skills of children normal and impaired in communication skills and measures of language and speech development. Journal of Communication Disorders, 27, 223-240.

Treviranus, J. & Norris, L. (1987). Predictive programs: Writing tools for severely physically disabled students. Proceedings of the 10th RESNA conference. Pp 130-132.

Venkatagiri, H. S. (1994). Effect of window size on rate of communication in a lexical prediction AAC system. Augmentative and Alternative Communication, 10, 105-112.

Wiig, E. H., & Semmel, E. M. (1980). Language assessment and intervention for the learning disabled. Columbus, OH: Merrill.

Wing, C. S. (1990). A preliminary investigation of generalization to untrained words following two treatments of children's word-finding problems. Language, Speech & Hearing Services in Schools, 21, 151-156.


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