Keystroke-level models for user performance with word prediction

AAC: Augmentative and Alternative Communication

Volumn 13, Issue 4, 1997, Pages 239-257

  Koester, Heidi Horstmann ^a   Levine, Simon P ^b  

^a Koester Performance Research   (United States)

^b UNIVERSITY OF MICHIGAN   (United States)

Author keywords

Augmentative communication; Group designs; Rate enhancement; User modeling; Word prediction

Indexed keywords

COMPUTER SIMULATION; DATA STRUCTURES; MATHEMATICAL MODELS;

AUGMENTATIVE AND ALTERNATIVE COMMUNICATION (AAC); KEYSTROKES LEVEL MODELS;

COMPUTER AIDED INSTRUCTION;

EID: 0031352912     PISSN: 07434618     EISSN: None     Source Type: Journal    
DOI: 10.1080/07434619712331278068     Document Type: Article

References (29)

1. Baker, B. R., Barry, R. F. (1990). A mathematical model of Minspeak. Second annual European Minspeak Conference.
2. Card, S., Moran, T., Newell, A. (1983). The psychology of human-computer interaction. Hillsdale, NJ: Lawrence Erlbaum Associates.
3. Card, S. K. (1982). User perceptual mechanisms in the search of computer command menus. In Human factors in computer systems proceedings (pp. 190-196). Gaithersburg, MD: National Bureau of Standards.
4. Dabbagh, H. H., Damper, R. I. (1985). Average selection length and time as predictors of communication rate. In Proceeding of the 8th Annual RESNA Conference (pp. 404-406). Washington, DC: RESNA.
5. Damper, R. I. (1984). Text composition by the physically disabled: A rate prediction model for scanning input. Applied Ergonomics, 15, 289-296.
6. Gibier, C. D., Childress, D. S. (1982). Language anticipation with a computer-based scanning communication aid. In Proceedings of the IEEE Computer Society Workshop on Computing to Aid the Handicapped (pp. 11-15). Charlottesville, VA: IEEE.
7. Girden, E. R. (1992). ANOVA: Repeated measures. Sage University Paper Series on Quantitative Applications in the Social Sciences, 07-084. Newbury Park, CA: Sage.
8. Gong, R. (1993). Validating and refining the GOMS model methodology for software user interface design and evaluation. Doctoral dissertation, Department of Industrial and Operations Engineering, University of Michigan, Ann Arbor, Michigan.
9. Goodenough-Trepagnier, C, Rosen, M. J., Jandura L., Getschow, C. O., Genoese-Zerbi, F., & Felts, T. (1987). Preliminary validation of prescription guide for selection of communication aids. In Proceedings of the 10th Annual RESNA Conference (pp. 100-102). Washington, DC: RESNA.
10. Goodenough-Trepagnier, C., Rosen, M. J. (1988). Predictive assessment for communication aid prescription: Motor-determined maximum communication rate. In L. Bernstein (Ed.), The vocally impaired (pp. 167-185). Philadelphia: Grune and Stratton.
11. Higginbotham, D. J. (1992). Evaluation of keystroke savings across five assistive communication technologies. Augmentative and Alternative Communication, 8, 258-272.
12. Horstmann, H. M., Levine, S. P. (1990). Modeling of user performance with computer access and augmentative communication systems for handicapped people. Augmentative and Alternative Communication, 6, 231-241.
13. Horstmann, H. M., Levine, S. P. (1992). Modeling AAC user performance: Response to Newell, Arnott, and Waller. Augmentative and Alternative Communication, 8, 92-97.
14. John, B. E. (1988). Contributions to engineering models of humancomputer interaction. Doctoral dissertation, Carnegie Mellon University, Pittsburgh, PA.
15. Jones, L., Wepman, E. (1966). A spoken word count. Chicago: Language Research Associates.
16. Koester, H. H., Levine, S. P. (1994). Modeling the speed of text entry with a word prediction interface. IEEE Transactions on Rehabilitation Engineering, 2, 177-187.
17. Koester, H. H., Levine, S. P. (1996). The effect of a word prediction feature on user performance. Augmentative and Alternative Communication, 12, 155-168.
18. Koester, H. H., Levine, S. P. (in press). Model simulations of user performance with word prediction. Augmentative and Alternative Communication, 13, 000-000.
19. Landauer, T. K., Nachbar, D. W. (1985). Selection from alphabetic and numeric menu trees using a touch screen. In CHI '85 Proceedings (pp. 73-78). New York: Association for Computing Machinery.
20. Levine, S. P., Gauger, J. R. D., Bowers, L. D., Khan, K. J. (1986). A comparison of mouthstick and Morse code text inputs. Augmentative and Alternative Communication, 2, 51-55.
21. Neisser, U. (1963). Decision time without reaction time: Experiments in visual scanning. American Journal of Psychology, 76, 376-385.
22. Newell, A. F., Arnott, J., Waller, A. (1992). On the validity of usermodeling in AAC: Comments on Horstmann and Levine (1990). Augmentative and Alternative Communication, 8, 89-92.
23. Newell, A., Card, S. K. (1985). The prospects for psychological science in human-computer interaction. Human Computer Interaction, 1, 209-242.
24. Olson, J.R., Nilsen, E. (1988). Analysis of the cognition involved in spreadsheet software interaction. Human Computer Interaction, 3, 309-350.
25. Olson, J. R., Olson, G. M. (1990). The growth of cognitive modeling in human-computer interaction since GOMS. Human Computer Interaction, 5, 221-265.
26. Pollak, I. V. (1982). Microprocessor-based communications system for the non-verbal person with serious motor handicaps: A preliminary report. Bulletin of Prosthetics Research, 19, 7-17.
27. Pollak, I. V., Gallagher, B. (1989). A fast communication aid for non-verbal subjects with severe motor handicaps. Journal of Medical Engineering and Technology, 13(1/2), 23-27.
28. Somberg, B. L. (1987). A comparison of rule-based and positionally constant arrangements of computer menu items. In Proceedings of CHI'87 (pp. 255-260). New York: Association for Computing Machinery.
29. Vanderheiden, G. C. (1988). A unified quantitative modeling approach for selection-based augmentative communication systems. In L. Bernstein (Ed.), The vocally impaired. Philadelphia: Grune and Stratton.