Frequency of judgment as a context-like determinant of predictive judgments (original) (raw)

Abstract

Several studies have shown that predictive and causal judgments vary depending on whether the question used to assess the relationship between events is presented after each piece of information or only after all the available information has been observed. This effect could be understood by assuming that in the two cases people perceive that the test question requires that different sets of evidence be taken into account. This hypothesis is tested in the present experiments through contextual manipulations that take place at the time of training and at the time of test. Our results show that people use this contextual information to infer which set of events should be considered when making their subjective assessments. The results are at odds with current theoretical approaches, but it is possible to develop mechanisms that would allow these models to account for the observed evidence.

Loading...

Loading Preview

Sorry, preview is currently unavailable. You can download the paper by clicking the button above.

References (41)

  1. Allan, L. G. (1980). A note on measurement of contingency between two binary variables in judgment tasks. Bulletin of the Psychonomic Society, 15, 147-149.
  2. Bouton, M. E. (1993). Context, time, and memory retrieval in the in- terference paradigms of Pavlovian conditioning. Psychological Bul- letin, 114, 80-99.
  3. Bouton, M. E. (1997). Signals for whether versus when an event will occur. In M. E. Bouton & M. S. Fanselow (Eds.), Learning, motiva- tion, and cognition: The functional behaviorism of Robert C. Bolles (pp. 385-409). Washington, DC: American Psychological Association.
  4. Bouton, M. E., & Bolles, R. C. (1979). Contextual control of the ex- tinction of conditioned fear. Learning & Motivation, 10, 445-466.
  5. Catena, A., Maldonado, A., & Cándido, A. (1998). The effect of the frequency of judgment and the type of trials on covariation learning. Journal of Experimental Psychology: Human Perception & Perfor- mance, 24, 481-495.
  6. Cheng, P. W. (1997). From covariation to causation: A causal power theory. Psychological Review, 104, 367-405.
  7. Cheng, P. W. (2000). Causality in the mind: Estimating contextual and conjunctive causal power. In F. C. Keil & R. A. Wilson (Eds.), Ex- planation and cognition (pp. 227-253). Cambridge, MA: MIT Press.
  8. Cheng, P. W., & Holyoak, K. J. (1995). Complex adaptive systems as intuitive statisticians: Causality, contingency and prediction. In H. L. Roitblat & J.-A. Meyer (Eds.), Comparative approaches to cognitive science (pp. 271-302). Cambridge, MA: MIT Press.
  9. Cheng, P. W., & Novick, L. R. (1992). Covariation in natural causal in- duction. Psychological Review, 99, 365-382.
  10. Cobos, P. L., Caño, A., López, F. J., Luque, J. L., & Almaraz, J. (2000). Does the type of judgement required modulate cue competi- tion? Quarterly Journal of Experimental Psychology, 53B, 193-207.
  11. Collins, D. J., & Shanks, D. R. (2002). Momentary and integrative re- sponse strategies in causal judgment. Memory & Cognition, 30, 1138-1147.
  12. De Houwer, J., Beckers, T., & Glautier, S. (2002). Outcome and cue properties modulate blocking. Quarterly Journal of Experimental Psychology, 55A, 965-985.
  13. Dennis, M. J., & Ahn, W.-K. (2001). Primacy in causal strength judg- ments: The effect of initial evidence for generative versus inhibitory relationships. Memory & Cognition, 29, 152-164.
  14. Dickinson, A., & Burke, J. (1996). Within-compound associations mediate the retrospective revaluation of causality judgements. Quar- terly Journal of Experimental Psychology, 49B, 60-80.
  15. Goddard, M. J. (1999). Renewal to the signal value of an uncondi- tioned stimulus. Learning & Motivation, 30, 15-34.
  16. Hogarth, R. M., & Einhorn, H. J. (1992). Order effects in belief up- dating: The belief-adjustment model. Cognitive Psychology, 24, 1-55.
  17. Jenkins, H., & Ward, W. (1965). Judgment of contingency between re- sponses and outcomes. Psychological Monographs, 7, 1-17.
  18. Lewandowsky, S. (1991). Gradual unlearning and catastrophic inter- ference: A comparison of distributed architectures. In W. E. Hockley & S. Lewandowsky (Eds.), Relating theory and data: Essays on human memory in honor of Bennet B. Murdock (pp. 445-476). Hills- dale, NJ: Erlbaum.
  19. Matute, H., Arcediano, F., & Miller, R. R. (1996). Test question modulates cue competition between causes and between effects. Journal of Experimental Psychology: Learning, Memory, & Cogni- tion, 22, 182-196.
  20. Matute, H., & Pineño, O. (1998). Cue competition in the absence of compound training: Its relation to paradigms of interference between outcomes. In D. L. Medin (Ed.), The psychology of learning and mo- tivation (Vol. 38, pp. 45-81). San Diego: Academic Press.
  21. Matute, H., Vegas, S., & De Marez, P. J. (2002). Flexible use of recent information in causal and predictive judgments. Journal of Experi- mental Psychology: Learning, Memory, & Cognition, 28, 714-725.
  22. McCloskey, M., & Cohen, N. J. (1989). Catastrophic interference in connectionist networks: The sequential learning problem. In G. H. Bower (Ed.), The psychology of learning and motivation (Vol. 24, pp. 109-165). San Diego: Academic Press.
  23. Mitchell, C. J., & Lovibond, P. F. (2002). Backward and forward blocking in human electrodermal conditioning: Blocking requires an assumption of outcome additivity. Quarterly Journal of Experimen- tal Psychology, 55B, 311-329.
  24. Nakajima, S., Tanaka, S., Urushihara, K., & Imada, H. (2000). Re- newal of extinguished lever-press responses upon return to the train- ing context. Learning & Motivation, 31, 416-431.
  25. Pavlov, I. P. (1927). Conditioned reflexes (G. V. Anrep, Trans.). Lon- don: Oxford University Press.
  26. Pearce, J. M. (1987). A model for stimulus generalization in Pavlov- ian conditioning. Psychological Review, 94, 61-73.
  27. Pearce, J. M. (1994). Similarity and discrimination: A selective review and a connectionist model. Psychological Review, 101, 587-607.
  28. Pennington, N., & Hastie, R. (1992). Explaining the evidence: Tests of story model for juror decision making. Journal of Personality & Social Psychology, 62, 189-206.
  29. Pineño, O., & Matute, H. (2000). Interference in human predictive learning when associations share a common element. International Journal of Comparative Psychology, 13, 16-33.
  30. Ratcliff, R. (1990). Connectionist models of recognition memory: Constraints imposed by learning and forgetting functions. Psycho- logical Review, 97, 285-308.
  31. Rescorla, R. A., & Wagner, A. R. (1972). A theory of Pavlovian con- ditioning: Variations in the effectiveness of reinforcement and non- reinforcement.
  32. In A. H. Black & W. F. Prokasy (Eds.), Classical con- ditioning II: Current research and theory (pp. 64-99). New York: Ap- pleton-Century-Crofts.
  33. Rosas, J. M., Vila, N. J., Lugo, M., & López, L. (2001). Combined ef- fect of context change and retention interval on interference in causal- ity judgments. Journal of Experimental Psychology: Animal Behavior Processes, 27, 153-164.
  34. Tamai, N., & Nakajima, S. (2000). Renewal of formerly conditioned fear in rats after extensive extinction training. International Journal of Comparative Psychology, 13, 137-146.
  35. Van Hamme, L. J., & Wasserman, E. A. (1994). Cue competition in causality judgments: The role of nonpresentation of compound stim- ulus elements. Learning & Motivation, 25, 127-151.
  36. Vila, N. J., & Rosas, J. M. (2001). Reinstatement of acquisition per- formance by the presentation of the outcome after extinction in causality judgments. Behavioural Processes, 56, 147-154.
  37. Wasserman, E. A. (1990). Attribution of causality to common and dis- tinctive elements of compound stimuli. Psychological Science, 1, 298-302.
  38. Wasserman, E. A., Kao, S.-F., Van Hamme, L. J., Katagari, M., & Young, M. E. (1996). Causation and association. In D. R. Shanks, K. J. Holyoak, & D. L. Medin (Eds.), The psychology of learning and motivation: Vol. 34. Causal learning (pp. 207-264). San Diego: Aca- demic Press. NOTES
  39. By using different centuries as our symbolic contexts, we do not mean to extract any particular conclusions with respect to the role of real temporal contexts. The only point we mean to make is that contex- tual cues (of one type or another) associated with one or the other block of trials can counteract the response mode effect. In Experiment 3, we use (perhaps more natural) symbolic physical contexts.
  40. Tamai & Nakajima, 2000), the results show that when testing takes place in a novel context, the expression of the excitatory associa- tion is not complete and is usually weaker than when it is tested in the context in which it was acquired. This suggests that when the test con- text is novel, the two associations, and not only the one acquired first, are partially active in memory. This is a slight deviation from Bouton's (1993) predictions, but it does not weaken the extension of this theory that we are suggesting to account for human predictive learning.
  41. Although Cheng's (2000) analysis applies theoretically only to causal relations and our task requires just predictive judgments (whose normative referents are different), the causal scenario used in these ex- periments could induce participants to make their predictive judgments on the basis of the underlying causal structure. (Manuscript received July 17, 2003; revision accepted for publication February 19, 2004.)