Abstract
Two experiments were conducted in which the effects of different feedback displays on decision criterion learning were examined in a perceptual categorization task with unequal cost-benefits. In Experiment 1, immediate versus delayed feedback was combined factorially with objective versus optimal classifier feedback. Immediate versus delayed feedback had no effect. Performance improved significantly over blocks with optimal classifier feedback and remained relatively stable with objective feedback. Experiment 2 used a within-subjects design that allowed a test of model-based instantiations of the flat-maxima (von Winterfeldt & Edwards, 1982) and competition between reward and accuracy (Maddox & Bohil, 1998a) hypotheses in isolation and of a hybrid model that incorporated assumptions from both hypotheses. The model-based analyses indicated that the flat-maxima model provided a good description of early learning but that the assumptions of the hybrid model were necessary to account for later learning. An examination of the hybrid model parameters indicated that the emphasis placed on accuracy maximization generally declined with experience for optimal classifier feedback but remained high, and fairly constant for objective classifier feedback. Implications for cost-benefit training are discussed.
Article PDF
Similar content being viewed by others
Avoid common mistakes on your manuscript.
References
Akaike, H. (1974). A new look at the statistical model identification.IEEE Transactions on Automatic Control,19, 716–723.
Ashby, F. G. (1992a). Multidimensional models of categorization. In F. G. Ashby (Ed.),Multidimensional models of perception and cognition (pp. 449–484). Hillsdale, NJ: Erlbaum.
Ashby, F. G. (1992b). Multivariate probability distributions. In F. G. Ashby (Ed.),Multidimensional models of perception and cognition (pp. 1–34). Hillsdale, NJ: Erlbaum.
Ashby, F. G., Alfonso-Reese, L. A., Turken, A. U., &Waldron, E. M. (1998). A neuropsychological theory of multiple systems in category learning.Psychological Review,105, 442–481.
Ashby, F. G., &Gott, R. E. (1988). Decision rules in the perception and categorization of multidimensional stimuli.Journal of Experimental Psychology: Learning, Memory, & Cognition,14, 33–53.
Ashby, F. G., Maddox, W. T., &Lee, W. W. (1994). On the dangers of averaging across subjects when using multidimensional scaling or the similarity-choice model.Psychological Science,5, 144–150.
Ashby, F. G., &Perrin, N. A. (1988). Toward a unified theory of similarity and recognition.Psychological Review,95, 124–150.
Ashby, F. G., &Townsend, J. T. (1986). Varieties of perceptual independence.Psychological Review,93, 154–179.
Bohil, C. J., &Maddox, W. T. (2001). Category discriminability, baserate, and payoff effects in perceptual categorization.Perception & Psychophysics,63, 361–376.
Busemeyer, J. R., &Myung, I. J. (1992). An adaptive approach to human decision making: Learning theory, decision theory, and human performance.Journal of Experimental Psychology: General,121, 177–194.
Busemeyer, J. R., &Rappaport, A. (1988). Psychological models of deferred decision making.Journal of Mathematical Psychology,32, 91–134.
Duker, P. C., Hensgens, Y., &Venderbosch, S. (1995). Effectiveness of delayed feedback on the accuracy of teaching communicative gestures to individuals with severe mental retardation.Research in Developmental Disabilities,16, 479–488.
Dusoir, A. E. (1980). Some evidence on additive learning models.Perception & Psychophysics,27, 163–175.
Erev, I. (1998). Signal detection by human observers: A cutoff reinforcement learning model of categorization decisions under uncertainty.Psychological Review,105, 280–298.
Erev, I., Gopher, D., Itkin, R., &Greenshpan, Y. (1995). Toward a generalization of signal detection theory to N-person games: The example of two-person safety problem.Journal of Mathematical Psychology,39, 360–375.
Erev, I., Wallsten, T. S., &Budescu, D. V. (1994). Simultaneous over- and underconfidence: The role of error in judgment processes.Psychological Review,101, 519–527.
Estes, W. K. (1950). The problem of inference from curves based on group data.Psychological Bulletin,53, 134–140.
Garner, W. R. (1974). The processing of information and structure. New York: Wiley.
Green, D. M., &Swets, J. A. (1966).Signal detection theory and psychophysics. New York: Wiley.
Healy, A. F., &Kubovy, M. (1981). Probability matching and the formation of conservative decision rules in a numerical analog of signal detection.Journal of Experimental Psychology: Human Learning & Memory,7, 344–354.
Kubovy, M., &Healy, A. F. (1977). The decision rule in probabilistic categorization: What it is and how it is learned.Journal of Experimental Psychology: General,106, 427–466.
Kubovy, M., &Healy, A. F. (1980). Process models of probabilistic categorization. In T. S. Wallsten (Ed.),Cognitive processes in choice and decision behavior (pp. 239–262). Hillsdale, NJ: Erlbaum.
Macmillan, N. A., &Creelman, C. D. (1991). Detection theory: A user’s guide. New York: Cambridge University Press.
Maddox, W. T. (1995). Base-rate effects in multidimensional perceptual categorization.Journal of Experimental Psychology: Learning, Memory, & Cognition,21, 288–301.
Maddox, W. T. (1999). On the dangers of averaging across observers when comparing decision bound models and generalized context models of categorization.Perception & Psychophysics,61, 354–374.
Maddox, W. T., &Ashby, F. G. (1993). Comparing decision bound and exemplar models of categorization.Perception & Psychophysics,53, 49–70.
Maddox, W. T., &Ashby, F. G. (1998). Selective attention and the formation of linear decision boundaries: Comment on McKinley and Nosofsky (1996).Journal of Experimental Psychology: Human Perception & Performance,24, 301–321.
Maddox, W. T., &Bohil, C. J. (1998a). Base-rate and payoff effects in multidimensional perceptual categorization.Journal of Experimental Psychology: Learning, Memory, & Cognition,24, 1459–1482.
Maddox, W. T., &Bohil, C. J. (1998b). Overestimation of base-rate differences in complex perceptual categories.Perception & Psychophysics,60, 575–592.
Maddox, W. T., &Bohil, C. J. (2000). Costs and benefits in perceptual categorization.Memory & Cognition,28, 597–615.
Maddox, W. T., & Dodd, J. L. (in press). On the relation between baserate and cost-benefit learning in simulated medical diagnosis.Journal of Experimental Psychology: Learning, Memory, & Cognition.
Maddox, W. T., & Estes, W. K. (1996, August).A dual process model of category learning. Paper presented at the 31st Annual Meeting of the Society for Mathematical Psychology, University of North Carolina, Chapel Hill.
Rankin, R. J., &Trepper, T. (1978). Retention and delay of feedback in a computer-assisted instructional task.Journal of Experimental Education,46, 67–70.
Reid, D. H., &Parsons, M. B. (1996). A comparison of staff acceptability of immediate versus delayed verbal feedback in staff training.Journal of Organizational Behavior Management,16, 35–47.
Roth, A. E., &Erev, I. (1995). Learning in extensive form games: Experimental data and simple dynamic models in the intermediate term.Games & Economic Behavior,3, 3–24.
Sassenrath, J. M. (1975). Theory and results on feedback and retention.Journal of Educational Psychology,67, 894–899.
Schroth, M. L. (1995). Variable delay of feedback procedures and subsequent concept formation transfer.Journal of General Psychology,122, 393–399.
Schroth, M. L. (1997). The effects of different training conditions on transfer in concept formation.Journal of General Psychology,124, 157–165.
Smith, J. D., &Minda, J. P. (1998). Prototypes in the mist: The early epochs of category learning.Journal of Experimental Psychology: Learning, Memory, & Cognition,24, 1411–1436.
Stevenson, M. K., Busemeyer, J. R., &Naylor, J. C. (1991). Judgment and decision-making theory. In M. D. Dunnette & L. M. Hough (Eds.),Handbook of industrial and organizational psychology (2nd ed., Vol. 1, pp. 283–374). Palo Alto, CA: Consulting Psychologists Press.
Takane, Y., &Shibayama, T. (1992). Structures in stimulus identification data. In F. G. Ashby (Ed.),Probabilistic multidimensional models of perception and cognition (pp. 335–362). Hillsdale, NJ: Erlbaum.
Thomas, E. A., &Legge, D. (1970). Probability matching as a basis for detection and recognition decisions.Psychological Review,77, 65–72.
von Winterfeldt, D., &Edwards, W. (1982). Costs and payoffs in perceptual research.Psychological Bulletin,91, 609–622.
Wallsten, T. S., &Gonzalez-Vallejo, C. (1994). Statement verification: A stochastic model of judgment and response.Psychological Review,101, 490–504.
Wickens, T. D. (1982).Models for behavior: Stochastic processes in psychology. San Francisco: Freeman.
Author information
Authors and Affiliations
Corresponding author
Additional information
This research was supported in part by National Science Foundation Grant SBR-9796206 and NIH Grant R01 MH59196.
Rights and permissions
About this article
Cite this article
Maddox, W.T., Bohil, C.J. Feedback effects on cost-benefit learning in perceptual categorization. Memory & Cognition 29, 598–615 (2001). https://doi.org/10.3758/BF03200461
Received:
Accepted:
Issue Date:
DOI: https://doi.org/10.3758/BF03200461