Developing a theory to guide the process of designing information retrieval systems

ABSTRACT

The dominant approaches to information retrieval system design are based on rational theory and cognitive engineering. However, these theories as well as approaches in other disciplines, reviewed in this paper, do not account for communication, or interaction, among design participants which is critical to design outcomes. This research attempts to develop a descriptive design model that accounts for communication among users, designers, and developers throughout the design process. A pilot study has been completed and a preliminary model that represents a first step in understanding participants' evolving perceptions and expectations of the design process and its outcomes is described in this paper.

References

1. Ancona, D. & Caldwell, D. (1990). Information technology and work groups: The case of new product teams. In J. Galegher, R. Kraut, C. Egido (Eds.), intellectual teamwork (pp. 173- 190). Hitlsdale, NJ: Lawrence Erlbaum Associates, Publishers.
2. Belkin, N., Seeger, T. & Wersig, G. (1983). Distributed expert problem solving as a model for information system analysis and design. Journal of lnformation Sciences, 5, pp. 153-167.
3. Belkin, N., Hennings, R., & Segger, T. (1984). Simulation of a distributed expert-based Information provision mechanism, Information Technology, 3 (3), pp. 122-141.
4. Berger, C.R. (1986). Social cognition and intergroup communication. In W.B. Grudykunst (Ed.), Intergroup communication (pp. 51-61). Baltimore, MD: Edward Arnold Publishers.
5. Brown, J.S. (1991). Research that reinvents the corporation. Harvard Business Review, January-February, 102-11.
6. Cushman, D.P., & King, S. S. (1986). The role of communication rules in explaining intergroup behavior. In W.B. Grudykunst (Ed.), Intergroup communication (pp. 39-50). Baltimore, MD: Edward Arnold Publishers.
7. Curtis, B., Krasner, H., & Iscoe, N. (1988). A field study of the software design process for large systems. Communications of the ACM, 31, 1268-1287.
8. Dorsey, P. (1988). An investigation of the effectiveness of communication between systems analysts and end users in the design of large computer systems. Unpublished doctoral dissertation, The University of Utah.
9. Egan, D., Remde, J., Gomez, L., Landauer, T., Eberhardt, J., & Lochbaum, C. (1989). Formative design-evaluation of Superbook. ACM Transactions on Information Systems, 7(1), 30-57.
10. Elan, P., & Kyng, M. (1987). The collective resource approach to systems design. In G. Bjerknes, P. Ehn, M. Kyng (Eds.), Computers and democracy: A Scandinavian challenge (pp. 17-58). Brookfield, VT: Gower Publishing Company.
11. Fisher, B., & Ellis, D. (1990). Small group decision making: Communication and the group process. New York: McGraw Hill Publishing Co.
12. Guinan, P. (1986). Specialist-generalist communication competence: A field experiment investigating the communication behavior of information systems developers. Unpublished doctoral dissertation, Indiana University, Bloomington, IN.
13. Hutchins, J. (1977). On the structure of scientific texts. UEA Papers in Linguistics, 5, 18-39.
14. Kidder, T. (1985). House. Boston: Houghton Mifflin Company.
15. Kukich, K. (1983). Design of a knowledge-based report generator. In Proceedings of the 21st Annual Meeting of the Association for Computational Linguistics. Cambridge, MA: Association for Computational Linguistics.
16. Kukich, K. (1984, July). Knowledge-based explanation generation. In Second Annual Language Generation Workshop, Stanford University, Stanford, CA.
17. Kukich, K. (1985a). Explanation structures in XSEL. In Proceedings of the 23rd Annual Meeting of the Association for Computational Linguistics (pp. 228-237). Morristown, NJ: Association for Computational Linguistics.
18. Kukich, K. (1985b). The feasibility of automatic natural language report generation. In Proceedings of the 18th Annual Hawaii International Conference on System Sciences. Honalulu, HA" IEEE Computer Society Press.
19. Kukich, K., McDermott, j., & Wang, T. (1985). Explaining XSEL's reasoning. Unpublished manuscript, Carnegie Mellon University, Pittsburg, PA.
20. Lakoff, G., & Johnson, M. (1980). Metaphors we live by. Chicago: University of Chicago Press.
21. Leonard-Barton, D. (1987). The case for integrative innovation: an expert system at Digital. Sloan Management Review, Fall, 7-19.
22. Lesk. M. (1991). SIGIR 91: The more things change, the more the stay the same. SIGIR Forum, 25, 4-7.
23. Lievrouw, L., & Finn, T. (1990). Identifying the common dimensions of communication: The communication systems model. In B. Ruben, L. Lievrouw (Eds.), Mediation, ir~ormation, and communication, information and behavior (Vol. 3, pp. 37-65), New Brunswick, NJ: Transaction Publishers.
24. McDermott, J. (1981). Domain knowledge and the design process. In Proceedings of the 18th Design Automation Conference (pp. 580-588). Piscataway, NJ: IEEE.
25. McDermott, J. (1982a). RI: A rule-based configurer of computer systems. Artificial Intelligence, 19(1), 39-88.
26. McDermott, J. (1982b). XSEL: A computer sales person's assistant. In J. Hayes, D. Michie, Y. Pao (Eds.), Machine Intelligence 10 (pp. 325-337). New York: John Wiley and Sons.
27. McDermott, J. (1984). Building expert systems, in W. Reitman (Ed.), Artificial Intelligence Applications for Business: Proceedings of the NYU Symposium, May 1983 (pp. 11-22). Norwood, NJ: Ablex Publishing Corp.
28. Mackie, R., & Wylie, C. (1988). Factors influencing acceptance of computer-based innovations. In M. Helander (Ed.), Handbook of Human-Computer Interaction (pp. 1081-1106). New York: Elsevier Science Publishers B.V.
29. Markus, M. (1983). Power, politics, and MIS implementation. Communications of the ACM, 26, 430-444.
30. Mumford, E. (1987). Sociotechnical systems design: Evolving theory and practice. In G. Bjerknes, P. Ehn, M. Kyng (Eds.), Computers and democracy: A Scandinavian challenge (pp. 59-76). Brookfield, VT: Gower Publishing Company.
31. Mumford, E., & MacDonald, W. (1989). XSEL's Progress: The Continuing Journey of an Expert System. New York: John Wiley.
32. O'Conner, D. (1984). Using expert systems to manage change and complexity in manufacturing. In W. Reitman (Ed.), Artificial Intelligence Applications for Business: Proceedings of the NYU Symposium, May 1983 (pp. 149-158). Norwood, NJ: Ablex Publishing Corp.
33. Pejtersen, A. (1989). A library system for information retrieval based on a cognitive task analysis and supported by an iconbased interface. In N. Belkin, C. van Rijsbergen (Eds.), SIGIR Conference Proceedings (pp. 40-47). Baltimore, MD: The Association for Computing Machinery.
34. Poole, M. S. (1983). Decision development in small groups: iIi. A multiple sequence model of group decision development. Communication Monographs, 50, 321-341.
35. Rifkin, G. (1986). A whole new DEC. Computer World, 20(38A), 14-22.
36. Sanders, R., & Cushman, D. (1984). Rules, constraints, and strategies. In C. Arnold, J. Bowers, (Eds.), Handbook of rhetoric and communication. Boston: Allyn and Bacon.
37. Simon, H. (1985). Sciences of the Artificial (2nd ed.). Cambridge, MA: The MIT Press.
38. Tajfel, H. (1970). Experiments in intergroup discrimination. Scientific America, 223, 96-102.
39. Walz, D. (1988). A longitudinal study of the group design process. Unpublished doctoral dissertation, The University of Texas at Austin.
40. Woods, D., & Roth, E. (1988). Cognitive systems engineering. In M. Helander, (Ed.), Handbook of Human-Computer Interaction (pp. 3-43). M. Helander (Ed.), New York: Elsevier Science Publishers B.V.
41. WylIys, R. (1979). System design-principles and techniques, In M. Williams (Ed.), Annual Review of Information Science and Technology, (Vol. 14, pp. 3-21), New York: American Society for Information Science.

Index Terms

• Computing methodologies

  • Artificial intelligence

    • Knowledge representation and reasoning

      • Cognitive robotics

    • Philosophical/theoretical foundations of artificial intelligence

      • Cognitive science

• Human-centered computing

  • Human computer interaction (HCI)

• Information systems

  • Information retrieval

    • Retrieval models and ranking