Skip to main content
Log in

Word processing programs and weaker writers/readers: a meta-analysis of research findings

  • Published:
Reading and Writing Aims and scope Submit manuscript

Abstract

Since its advent word processing has become a common writing tool, providing potential advantages over writing by hand. Word processors permit easy revision, produce legible characters quickly, and may provide additional supports (e.g., spellcheckers, speech recognition). Such advantages should remedy common difficulties among weaker writers/readers in grades 1–12. Based on 27 studies with weaker writers, 20 of which were not considered in prior reviews, findings from this meta-analysis support this proposition. From 77 independent effects, the following average effects were greater than zero: writing quality (d = 0.52), length (d = 0.48), development/organization of text (d = 0.66), mechanical correctness (d = 0.61), motivation to write (d = 1.42), and preferring word processing over writing by hand (d = 0.64). Especially powerful writing quality effects were associated with word processing programs that provided text quality feedback or prompted planning, drafting, or revising (d = 1.46), although this observation was based on a limited number of studies (n = 3).

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1

Similar content being viewed by others

References

References marked with an asterisk included in the meta-analysis

  • *Bair, R. J. (1990). The effects of word processing on the writing output of emotionally disturbed students. Unpublished Doctoral Dissertation, University of South Florida, St. Petersburg, FL.

  • Bangert-Drowns, R. L. (1993). The word processor as an instructional tool: A meta-analysis of word processing in writing instruction. Review of Educational Research, 63, 69–93.

    Google Scholar 

  • Carlson, P., & Crevoisier, M. (1994). R-WISE: A Computerized environment for tutoring critical literacy. Paper presented at the World Conference on Educational Multimedia and Hypermedia, Vancouver, BC, Canada.

  • *Carlson, P., & Miller, T. (1996). Beyond word processing: Using an interactive learning environment to teach writing (No. AL/-HR-TR-1996-0090). Brooks AFB, TX: Technical Report of the Human Resources Directorate, Technical Training Division.

  • *Cirello, V. J. (1986). The effect of word processing on the writing abilities of tenth grade remedial writing students. Unpublished Doctoral Dissertation, New York University, New York, NY.

  • Cochrane, W. G. (1954). The combination of estimates from different experiments. Biometrics, 10, 101–129.

    Article  Google Scholar 

  • Cortina, J. M., & Nouri, H. (2000). Effect size for ANOVA designs (Vol. 129). Thousand Oaks, CA: Sage.

    Google Scholar 

  • *Crane, B. E. (1988). A comparison of alternative methods of teaching writing to Cherokee students in grades three through eight. Unpublished Dissertation, Oklahoma State University, Stillwater, OK.

  • *Dodson, B. T. (1993). Effects of computer-assisted writing instruction with an integrated learning system on fifth-grade writing achievement. Unpublished Doctoral Dissertation, Baylor University, Waco, TX.

  • Dunlap, W. P., Cortina, J. M., Vaslow, J. B., & Burke, M. J. (1996). Meta-analysis of experiments with matched groups or repeated measures designs. Psychological Methods, 1, 170–177.

    Article  Google Scholar 

  • *Dupuy, C. A. (2001). The role of working memory and transcription automaticity in written language among adolescents with learning disabilities: A comparison of production by hand and by computer. Unpublished Doctoral Dissertation, Northwestern University, Evanston, IL.

  • Egger, M., Smith, G. D., & Phillips, A. N. (1997). Meta-analysis: Principles and procedures. British Medical Journal, 315, 1533–1537.

    Article  Google Scholar 

  • Fitzgerald, J., & Shanahan, T. (2000). Reading and writing relations and their development. Educational Psychologist, 35, 39–50.

    Article  Google Scholar 

  • *Franzke, M., Kintsch, E., Caccamise, D., Johnson, N., & Dooley, S. (2005). Summary street: Computer support for comprehension and writing. Journal of Educational Computing Research, 33, 53–80.

    Google Scholar 

  • Goldberg, A., Russell, M., & Cook, A. (2003). The effect of computers on student writing: A meta-analysis of studies from 1992 to 2002. The Journal of Technology, Learning, and Assessment 2. Retrieved from http://escholarship.bc.edu/jtla/vol2/1/.

  • Graham, S. (1999). Handwriting and spelling instruction for students with learning disabilities: A review. Learning Disability Quarterly, 22, 78–98.

    Article  Google Scholar 

  • Graham, S. (2006). Writing. In P. Alexander & P. Winne (Eds.), Handbook of educational psychology (pp. 457–478). Mahwah, NJ: Erlbaum.

    Google Scholar 

  • Graham, S. (2008). The power of word processing. Wisconsin Rapids, WI: Renaissance Learning.

    Google Scholar 

  • Graham, S., & Harris, K. R. (in press). Writing. In R. Allington & A. McGill-Franzen. (Eds.), Handbook of reading disabilities research. Mahwah, NJ: Erlbaum.

  • Graham, S., & MacArthur, C. (1988). Improving learning disabled students’ skills at revising essays produced on a word processor: Self-instructional strategy training. Journal of Special Education, 22, 133–152.

    Article  Google Scholar 

  • Graham, S., & Perin, D. (2007a). Writing next: Effective strategies to improve writing of adolescent middle and high school. Alliance for Excellence in Education. Washington, DC (Commissioned by the Carnegie Corp. of New York).

  • Graham, S., & Perin, D. (2007b). A meta-analysis of writing instruction for adolescent students. Journal of Educational Psychology, 99, 445–476.

    Article  Google Scholar 

  • Harbord, R. M., & Higgins, J. P. T. (2008). Meta-regression in Stata. Stata Journal, 8, 493–519.

    Google Scholar 

  • Hasselblad, V., & Hedges, L. V. (1995). Meta-analysis of screening and diagnostic tests. Psychological Bulletin, 117, 167–178.

    Article  Google Scholar 

  • Hedges, L. V. (1982). Estimation of effect size from a series of independent experiments. Psychological Bulletin, 92, 490–499.

    Article  Google Scholar 

  • Hedges, L. V. (2007a). Correcting a significance test for clustering. Journal of Educational and Behavioral Statistics, 32, 151–179.

    Article  Google Scholar 

  • Hedges, L. V. (2007b). Effect sizes in cluster-randomized designs. Journal of Educational and Behavioral Statistics, 32, 341–370.

    Article  Google Scholar 

  • Hedges, L. V., & Hedberg, E. C. (2007). Intraclass correlation values for planning group-randomized trials in education. Educational Evaluation and Policy Analysis, 29, 60.

    Article  Google Scholar 

  • Higgins, J. P. T., Thompson, S. G., Deeks, J. J., & Altman, D. G. (2003). Measuring inconsistency in meta-analyses. British Medical Journal, 327, 557–560.

    Article  Google Scholar 

  • Higgins, J. P. T., & Thompson, S. G. (2004). Controlling the risk of spurious findings from meta-analysis. Statistics in Medicine, 23, 1663–1682.

    Article  Google Scholar 

  • Hillocks, G. (1984). What works in teaching composition: A meta-analysis of experimental treatment studies. American Journal of Education, 92, 133–170.

    Article  Google Scholar 

  • Hillocks, G., Jr. (1986). Research on written composition: New directions for teaching. Illinois: National Conference on Research in English.

    Google Scholar 

  • *Johnson, M. A. (1986). Effects of using the computer as a tool for writing on the vocabulary, reading, and writing of first and second grade Spanish-speaking students. Unpublished Doctoral dissertation, Texas Woman’s University, Dallas, TX.

  • *Karda, T. P. (2003). Effects of writing instruction method on low-achieving students’ planning and revision capabilities. Unpublished Doctoral Dissertation, SUNY, Buffalo.

  • *Kerchner, L. B., & Kistinger, B. J. (1984). Language processing/word processing: Written expression, computers and learning disabled students. Learning Disability Quarterly, 7, 329–335.

    Google Scholar 

  • Knapp, G., & Hartung, J. (2003). Improved tests for a random effects meta-regression with a single covariate. Statistics in Medicine, 22, 2693–2710.

    Article  Google Scholar 

  • *Lerew, E. L. (1997). The use of computers to improve writing skills among low-achieving Hispanic students. Unpublished Doctoral Dissertation, University of La Verne, La Verne, CA.

  • *Lewis, R. B., Ashton, T. M., Haapa, B., Kieley, C. L., & Fielden, C. (1999). Improving the writing skills of students with learning disabilities: Are word processors with spelling and grammar checkers useful? Learning Disabilities, 9, 87–98.

    Google Scholar 

  • Lipsey, M., & Wilson, D. (2001). Practical meta-analysis. Thousand Oaks, CA: Sage.

    Google Scholar 

  • MacArthur, C. (2006). The effects of new technologies on writing and writing processes. In C. MacArthur, S. Graham, & J. Fitzgerald (Eds.), Handbook of writing research (pp. 248–261). New York, NY: Guilford.

    Google Scholar 

  • *MacArthur, C. A., & Cavalier, A. (2004). Dictation and speech recognition technology as accommodations in large-scale assessments for students with learning disabilities. Exceptional Children, 71, 43–58.

    Google Scholar 

  • *MacArthur, C. A., & Graham, S. (1987). Learning disabled students’ composing under three methods of text production: Handwriting, word processing, and dictation. The Journal of Special Education, 21(3), 22–42.

    Google Scholar 

  • *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, 278–291.

  • Morphy, P. (2007). From best-evidence synthesis to mixed-methods meta-analysis: Making research synthesis useful to larger audiences. Unpublished article.

  • Page, E. B., & Petersen, N. S. (1995). The computer moves into essay grading: Updating the ancient test. Phi Delta Kappan, 76, 561–566.

    Google Scholar 

  • *Pearce-Burrows, A. J. (1991). The differential effects of using the computer in a process writing program on the writing quality and quantity of third and fourth-grade pupils. Unpublished Doctoral Dissertation, University of Alberta, Edmonton, AB.

  • Penuel, W. R. (2006). Implementation and effects of one-to-one computing initiatives: A research synthesis. Journal of Research on Technology in Education, 38, 329–348.

    Google Scholar 

  • *Pernia, S. S. (1987). Effects of microcomputer use and word-processing on the writing skills of learning-disabled middle school students. Unpublished Doctoral Dissertation, University of Michigan.

  • *Philhower, S. C. (1985). The effects of the use of a word processing program on the writing skills of mildly handicapped secondary students. Unpublished Doctoral Dissertation, University of Iowa, Iowa City, IA.

  • *Pivarnik, B. A. (1985). The effect of training in word processing on the writing of eleventh grade students. Unpublished Doctoral Dissertation, The University of Connecticut, Storrs, CT.

  • *Quinlan, T. (2004). Speech recognition technology and students with writing difficulties: Improving fluency. Journal of Educational Psychology, 96, 337–346.

    Google Scholar 

  • *Roberts, R. J. (1999). Use of computer dictation by students with learning disabilities. Unpublished Doctoral Dissertation, Syracuse University, Syracuse, NY.

  • Rock, J. L. (2007). The impact of short-term use of Criterion (SM) on writing skills in ninth grade (No. RR-07-07). Princeton, NJ: ETS.

  • Rowley, K., Carlson, P., & Miller, T. (1998). A cognitive technology to teach composition skills: Four studies with the R-WISE writing tutor. Journal of Educational Computing Research, 18, 259–296.

    Article  Google Scholar 

  • Salomon, G., & Perkins, D. (2005). Do technologies make us smarter? In R. J. Sternberg & D. D. Preiss (Eds.), Intelligence and technology: The impact of tools on the nature and development of human abilities (pp. 71–75). Mahwah, NJ: Lawrence Erlbaum.

    Google Scholar 

  • *Sapona, R. H. (1985). Writing productivity of learning disabled students: The effects of using a word processing program. Unpublished Doctoral Dissertation, University of Virginia, Charlottesville, VA.

  • Shadish, W. R., Robinson, L., & Congxiao, L. (1999). ES: A computer program for effect size calculation. Memphis, TN: University of Memphis.

    Google Scholar 

  • *Shinn, J. A. (1986). The effectiveness of word-processing and problem-solving computer use on the social skills of learning-disabled students. Unpublished doctoral dissertation, United States International University, Los Angeles, CA.

  • *Silver, N. W., & Repa, J. T. (1993). The effect of word processing on the quality of writing and self-esteem of secondary school English-as-second-Language students: Writing without censure. Journal of Educational Computing Research, 9, 265–283.

    Google Scholar 

  • *Smith, C. A. (1989). The effects of handwriting versus word processing on learning-disabled students’ written compositions. Unpublished Doctoral dissertation, Columbia University Teachers College, New York, NY.

  • Smith, M. L., Glass, G. V., & Miller, T. I. (1980). The benefits of psychotherapy. Baltimore: Johns Hopkins University Press.

    Google Scholar 

  • Tukey, J. (1977). Exploratory data analysis. Reading, MA: Addison-Wesley.

    Google Scholar 

  • *Utay, C. M. (1992). Peer-assisted learning: The effects of cooperative learning and cross-age peer-tutoring on writing skills of students with learning disabilities. Unpublished Doctoral Dissertation, East Texas State University, Commerce, TX.

  • Valentine, J. C., & Cooper, H. (2003). Effect size substantive interpretation guidelines: Issues in the interpretation of effect sizes. Washington, DC: What Works Clearinghouse.

    Google Scholar 

  • What Works Clearinghouse (2007). Technical details of WWC-conducted computations. Retrieved from http://www.whatworks.ed.gov/reviewprocess/conducted_computations.pdf.

  • Welch, B. L. (1947). The generalization of ‘Student’s’ problem when several different population variances are involved. Biometrika, 34(1–2), 28–35.

    Google Scholar 

  • Zellermayer, M., Salomon, G., Globerson, T., & Givon, H. (1991). Enhancing writing-related metacognitions through a computerized writing partner. American Educational Research Journal, 28, 373–391.

    Google Scholar 

  • *Zhang, Y. (1993). Robowriter and Microsoft Word: Comparative effects on improvement of writing skills of primary grade LD students. Unpublished Doctoral Dissertation, University of Nebraska, Lincoln, NE.

  • Zhao, Y. (2001). Recent developments in technology and language learning; A literature review and meta-analysis. Retrieved from http://ott.educ.msu.edu/elanguage/about/literature.asp.

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Paul Morphy.

Additional information

Paul Morphy’s work was supported by Vanderbilt’s Experimental Education Research Training (ExpERT) grant. (David S. Cordray, Director; grant number R305B040110). The opinions expressed are those of the authors and do not represent the views of the US Department of Education.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Morphy, P., Graham, S. Word processing programs and weaker writers/readers: a meta-analysis of research findings. Read Writ 25, 641–678 (2012). https://doi.org/10.1007/s11145-010-9292-5

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11145-010-9292-5

Keywords

Navigation