Signal to noise ratio of information in documentation

ABSTRACT

The signal to noise ratio is a common concept in radio communications and electronic communication in general. For a radio, the static is the noise. Too much static and the storm report gets drowned out, or at least you must listen closely to understand the announcer. Unfortunately, information designers do not posses a clear cut set of techniques available to electrical engineers. For information systems, taking the raw data in a system and deciding what is signal and what is noise proves to be extremely difficult. This paper will examine how the concept of signal to noise ratio can be applied to documentation. It will consider how the need to address different tasks and audience forces compromises on the writer to meet those different needs, when each audience has different definitions of which information constitutes signal and which constitutes noise.

References

1. Albers, M. (1999). Information design considerations for improving situation awareness in complex problem-solving. 17th Annual International Conference on Computer Documentation.
2. Albers, M. (in press). Design for complex situations: Analysis and creation of dynamic web information. Mahwah, NJ: Erlbaum.
3. Bereiter, C. & Scardamalia, M. (1987). The psychology of written composition. New Jersey: Erlbaum.
4. Bettman, J., Johnson, E. and Payne, J. (1990) A componential analysis of cognitive effort and choice. Organizational Behavior and Human Decision Processes 45, 111--139.
5. Blandford, A. & Young, R. (November 1996). Specifying user knowledge for the design of interactive systems. Software Engineering Journal, 323--333.
6. Casaday, G. (1991). Balance. Taking software design seriously: Practical Techniques for Human-Computer Interaction Design. Ed. John Karat. San Diego: Academic Press, 45--62.
7. Cooper, A. (1999). The inmates are running the asylum. Indianapolis, IN: Sams.
8. Duin, A. (1991). Reading to learn and do. Proceedings of 38th STC Conference.
9. Endsley, M. (1995). Toward a theory of situation awareness in dynamic systems. Human Factors. 37(1) 32--64.
10. Ganzach, Y & Schul, Y. (1995). The influence of quantity of information and goal framing on decisions. Acta Psychologia, 89, 23--36.
11. Gerlach, J., & Kuo, F. (1991). Understanding human-computer interaction for information system design. MIS Quarterly, 15(4), 527--550.
12. Hallgren, C. (1997). Using a problem focus to quickly aid users in trouble. Proceedings of the 1997 STC Annual Conference. Washington, DC: STC.
13. Herbig, P., & Kramer, H. (1992) The phenomenon of innovation overload. Technology in Society 14, 441--461.
14. Hsee, C. (1995). Elastic justification: How tempting but task irrelevant factors influence decisions. Organizational Behavior and Human Decision Processes 62.3, 330--337.
15. Johnson, E., Payne, J., & Bettman, J. (1988). Information displays and preference reversals. Organizational Behavior and Human Decision Processes, 42, 1--21.
16. Klein, G. (1999). Sources of Power: How People make Decisions. Cambridge, MA: MIT.
17. Laplante, P., & Flaxman, H. (1995) The convergence of technology and creativity in the corporate environment. IEEE Transactions on Professional Communication 38.1, 20--23.
18. McNamara, D.S., & Kintsch, W. (1996). Learning from text: Effects of prior knowledge and text coherence. Discourse Processes, 22, 247--287.
19. Mirel, B. (1992). Analyzing audiences for software manuals: A survey of instructional needs for 'real world tasks'. Technical Communication Quarterly, 1.1, 15--35.
20. Rasmussen, J. (1986). Information Processing and Human-Machine Interaction: An Approach to Cognitive Engineering. New York: North-Holland.
21. Rubens, P., & Rubens, B. (1988). Usability and format design. Effective Documentation: What We Have Learned. From Research Ed. Steven Doheny-Farina. Cambridge, MA: MIT. 213--234.
22. Russo, J. (1977). The value of unit price information. Journal of Marketing Research, 14, 193--201.
23. Simon, H. (1979). Models of Thought. New Haven, CT: Yale UP.
24. Sweller, J., et al. (1990) Cognitive load as a factor in the structuring of technical material. Journal of experimental psychology: general. 119(2) 176--192.
25. Treu, S. (1992). Interface structures: Conceptual, logical, and physical patterns applicable to human-computer interaction. International Journal of Man-Machine Studies, 37, 565--593.
26. Tufte, E. (1983). The Visual Display of Quantitative Information. Cheshire, CT: Graphics Press.
27. Tversky, A. & Kahneman, D. (1981). The framing of decisions an the psychology of choice. Science, 211, 453--458.
28. Webster, D., & Kruglanski, A. (1994). Individual differences in need. for cognitive closure. Journal of Personality and Social Psychology 67.6, 1049--1672.
29. Wickens, C. (1992). Engineering Psychology and Human Performance. New York: HarperCollins.
30. Woods, D., & Roth. E. (1988). Cognitive engineering: Human problem solving with tools. Human Factors, 30.4, 415--430.

Index Terms

• Computing methodologies

  • Artificial intelligence

    • Philosophical/theoretical foundations of artificial intelligence

      • Cognitive science

• Human-centered computing

  • Human computer interaction (HCI)