Information Technology Reference
In-Depth Information
We have demonstrated that the theory of cognitive fit applies to problems of varying complex-
ity, to a number of problem domains, and to a number of dimensions of fit. Hence it is clear that
it is, indeed, one aspect of a general theory of problem solving. When applicable, researchers
should examine issues in the context of the theory, thereby adding to a substantial body of knowl-
edge on its efficacy. System designers can use the theory as a substantive basis for designing more
effective and efficient systems to support decision makers.
NOTES
1. Note that the authors may have been unaware of this paper—it did not appear among their references.
2. Note that this model uses the extended model of cognitive fit.
3. See Newell and Simon (1972) for an exposition of the relationship between knowledge states and
problem-solving processes.
4. Recall that these researchers assessed only time in their experiment, and not accuracy.
REFERENCES
Addo, T.B.A. Development of a Valid and Robust Metric for Measuring Question Complexity in Computer
Graphics Experimentation . Doctoral dissertation, Indiana University, 1989.
Agarwal, R.; De, P.; and Sinha, A.P. Comprehending object and process models: an empirical study. IEEE
Transactions on Software Engineering , 25, 4 (1999), 541-556.
Agarwal, R., and Sinha, A.P. Cognitive fit in requirements modeling: a study of object and process method-
ologies. Journal of Management Information Systems , 13, 2 (1996), 137-162.
Agarwal, R.; Sinha, A.P.; and Tanniru, M. The role of prior experience and task characteristics in object-
oriented modeling: an empirical study. International Journal of Human-Computer Studies , 45, 6 (1996),
639-667.
Anderson, J.R. Acquisition of cognitive skill. Psychological Review , 89, 4 (1982), 369-406.
Anderson, J.R. The Architecture of Cognition . Mahwah, N.J: Lawrence Erlbaum Associates, 1996.
Anderson, J.R., and Bower, G.H. Human Associative Memory: A Brief Edition . Hillsdale, NJ: Lawrence
Erlbaum Associates, 1980.
Bailey, K.D. Typologies and Taxonomies: An Introduction to Classification Techniques. Thousand Oaks,
CA: Sage Publications, 1994.
Beach, L.R., and Mitchell, F.R. A contingency model for the selection of decision strategies. Academy of
Management Review , 3 (1978), 439-449.
Beckman, P.A. Concordance between task and interface rotational and translational control improves ground
vehicle performance. Human Factors , 44, 4 (2002), 644-653.
Benbasat, I., and Weber, R. Rethinking “diversity” in information systems research. Information Systems
Research 7, 4 (1996), 389-399.
Bettman, J.R., and Kakkar, P. Effects of information presentation format on consumer information acquisi-
tion strategies. Journal of Consumer Research , 3 (1977), 233-240.
Bettman, J.R., and Zins, M. Information format and choice task in decision making. Journal of Consumer
Research , 6 (1979), 141-153.
Borthick, A.F.; Bowen, P.L.; Jones, D.R.; and Tse, M.H.K. The effects of information request ambiguity and
construct incongruence on query development. Decision Support Systems , 32, 1 (2001), 3-25.
Campbell, D.J. Task complexity: a review and analysis. Academy of Management Journal , 13, 1 (1988),
40-52.
Card, S.K.; Moran, T.P.; and Newell, A. The keystroke-level model for user performance time with interac-
tive systems. Communications of the ACM , 23, 7 (1980), 396-410.
Card, S.K.; Moran, T.P.; and Newell, A. The Psychology of Human-Computer Interaction . Hillsdale, NJ:
Lawrence Erlbaum Associates, 1983.
Chan, S.Y. The use of graphs as decision aids in relation to information overload and managerial decision
quality. Journal of Information Science , 27, 6 (2001), 417-425.
Chandra, A., and Krovi, R. Representational congruence and information retrieval: towards an extended
model of cognitive fit. Decision Support Systems , 25, 4 (1999), 271-288.
Search WWH ::




Custom Search