30 found
Sort by:
  1. David R. Shanks, Insight and Strategy in Multiple Cue Learning.
    Insight and strategy 2 Abstract In multiple-cue learning (also known as probabilistic category learning) people acquire information about cue-outcome relations and combine these into predictions or judgments. Previous studies claim that people can achieve high levels of performance without explicit knowledge of the task structure or insight into their own judgment policies. It has also been argued that people use a variety of suboptimal strategies to solve such tasks. In three experiments we re-examined these conclusions by introducing novel measures of (...)
    No categories
    Translate to English
    | Direct download  
     
    My bibliography  
     
    Export citation  
  2. David R. Shanks, Learning in a Changing Environment.
    Multiple cue probability learning studies have typically focused on stationary environments. We present three experiments investigating learning in changing environments. A fine-grained analysis of the learning dynamics shows that participants were responsive to both abrupt and gradual changes in cue-outcome relations. We found no evidence that participants adapted to these types of change in qualitatively different ways. Also, in contrast to earlier claims that these tasks are learned implicitly, participants showed good insight into what they learned. By fitting formal learning (...)
    No categories
    Translate to English
    | Direct download  
     
    My bibliography  
     
    Export citation  
  3. David R. Shanks, Learning Strategies in Amnesia.
    Previous research suggests that early performance of amnesic individuals in a probabilistic category learning task is relatively unimpaired. When combined with impaired declarative knowledge, this is taken as evidence for the existence of separate implicit and explicit memory systems. The present study contains a more fine-grained analysis of learning than earlier studies. Using a dynamic lens model approach with plausible learning models, we found that the learning process is indeed indistinguishable between an amnesic and control group. However, in contrast to (...)
    Translate to English
    | Direct download  
     
    My bibliography  
     
    Export citation  
  4. Rosalind Potts & David R. Shanks (forthcoming). The Benefit of Generating Errors During Learning. Journal of Experimental Psychology: General.
    No categories
    Direct download  
     
    My bibliography  
     
    Export citation  
  5. Ben R. Newell & David R. Shanks (2014). Unconscious Influences on Decision Making: A Critical Review. Behavioral and Brain Sciences 37 (1):1-19.
    Direct download (2 more)  
     
    My bibliography  
     
    Export citation  
  6. David R. Shanks & Ben R. Newell (2014). The Primacy of Conscious Decision Making. Behavioral and Brain Sciences 37 (1):45-61.
    Direct download (2 more)  
     
    My bibliography  
     
    Export citation  
  7. Tom Beesley, Fergal W. Jones & David R. Shanks (2012). Out of Control: An Associative Account of Congruency Effects in Sequence Learning. Consciousness and Cognition 21 (1):413-421.
    Direct download (3 more)  
     
    My bibliography  
     
    Export citation  
  8. Christopher J. Berry, David R. Shanks, Maarten Speekenbrink & Richard N. A. Henson (2011). Models of Recognition, Repetition Priming, and Fluency: Exploring a New Framework. Psychological Review 24.
    We present a new modeling framework for recognition memory and repetition priming based on signal detection theory. We use this framework to specify and test the predictions of 4 models: (a) a single-system (SS) model, in which one continuous memory signal drives recognition and priming; (b) a multiple-systems-1 (MS1) model, in which completely independent memory signals (such as explicit and implicit memory) drive recognition and priming; (c) a multiple-systems-2 (MS2) model, in which there are also 2 memory signals, but some (...)
    Direct download  
     
    My bibliography  
     
    Export citation  
  9. Maarten Speekenbrink & David R. Shanks (2011). Is Everyone Bayes? On the Testable Implications of Bayesian Fundamentalism. Behavioral and Brain Sciences 34 (4):213-214.
    A central claim of Jones & Love's (J&L's) article is that Bayesian Fundamentalism is empirically unconstrained. Unless constraints are placed on prior beliefs, likelihood, and utility functions, all behaviour is consistent with Bayesian rationality. Although such claims are commonplace, their basis is rarely justified. We fill this gap by sketching a proof, and we discuss possible solutions that would make Bayesian approaches empirically interesting.
    Direct download (6 more)  
     
    My bibliography  
     
    Export citation  
  10. David R. Shanks (2009). The Associative Nature of Human Associative Learning. Behavioral and Brain Sciences 32 (2):225-226.
    The extent to which human learning should be thought of in terms of elementary, automatic versus controlled, cognitive processes is unresolved after nearly a century of often fierce debate. Mitchell et al. provide a persuasive review of evidence against automatic, unconscious links. Indeed, unconscious processes seem to play a negligible role in any form of learning, not just in Pavlovian conditioning. But a modern connectionist framework, in which phenomena are emergent properties, is likely to offer a fuller account of human (...)
    Direct download (3 more)  
     
    My bibliography  
     
    Export citation  
  11. Christopher J. Berry, David R. Shanks & Richard N. A. Henson (2008). A Unitary Signal-Detection Model of Implicit and Explicit Memory. Trends in Cognitive Sciences 12 (10):367-373.
    Do dissociations imply independent systems? In the memory field, the view that there are independent implicit and explicit memory systems has been predominantly supported by dissociation evidence. Here, we argue that many of these dissociations do not necessarily imply distinct memory systems. We review recent work with a single-system computational model that extends signal-detection theory (SDT) to implicit memory. SDT has had a major influence on research in a variety of domains. The current work shows that it can be broadened (...)
    Direct download (3 more)  
     
    My bibliography  
     
    Export citation  
  12. David A. Lagnado & David R. Shanks (2007). Dual Concerns with the Dualist Approach. Behavioral and Brain Sciences 30 (3):271-272.
    Barbey & Sloman (B&S) attribute all instances of normative base-rate usage to a rule-based system, and all instances of neglect to an associative system. As it stands, this argument is too simplistic, and indeed fails to explain either good or bad performance on the classic Medical Diagnosis problem.
    Direct download (5 more)  
     
    My bibliography  
     
    Export citation  
  13. Christopher J. Berry, David R. Shanks & Richard N. A. Henson (2006). On the Status of Unconscious Memory: Merikle and Reingold (1991) Revisited. Journal of Experimental Psychology 32 (4):925-934.
  14. Annette Kinder, David R. Shanks, Josephine Cock & Richard J. Tunney (2003). Recollection, Fluency, and the Explicit/Implicit Distinction in Artificial Grammar Learning. Journal of Experimental Psychology: General 132 (4):551.
    No categories
    Direct download (2 more)  
     
    My bibliography  
     
    Export citation  
  15. David A. Lagnado & David R. Shanks (2003). The Influence of Hierarchy on Probability Judgment. Cognition 89 (2):157-178.
    Consider the task of predicting which soccer team will win the next World Cup. The bookmakers may judge Brazil to be the team most likely to win, but also judge it most likely that a European rather than a Latin American team will win. This is an example of a non-aligned hierarchy structure: the most probable event at the subordinate level (Brazil wins) appears to be inconsistent with the most probable event at the superordinate level (a European team wins). In (...)
    Direct download (4 more)  
     
    My bibliography  
     
    Export citation  
  16. David R. Shanks (2003). Attention and Awareness in 'Implicit' Sequence Learning. In L. Jiminez (ed.), Attention and Implicit Learning. John Benjamins.
  17. Richard J. Tunney & David R. Shanks (2003). Does Opposition Logic Provide Evidence for Conscious and Unconscious Processes in Artificial Grammar Learning? Consciousness and Cognition 12 (2):201-218.
  18. Richard J. Tunney & David R. Shanks (2003). Subjective Measures of Awareness and Implicit Cognition. Memory and Cognition 31 (7):1060-1071.
  19. David Carmel, Shlomo Bentin, Chang Hong Liu, Avi Chaudhuri, David A. Lagnado & David R. Shanks (2002). Alexandre Pouget, Jean-Christophe Ducom, Jeffrey Torri and Daphne Bavelier (University of Rochester) Multisensory Spatial Representations in Eye-Centered Coordinates for Reaching, B1–B11. Cognition 83:323-325.
     
    My bibliography  
     
    Export citation  
  20. Peter F. Lovibond & David R. Shanks (2002). The Role of Awareness in Pavlovian Conditioning: Empirical Evidence and Theoretical Implications. Journal of Experimental Psychology 28 (1):3-26.
  21. David R. Shanks & David Lagnado (2000). Sub-Optimal Reasons for Rejecting Optimality. Behavioral and Brain Sciences 23 (5):761-762.
    Although we welcome Gigerenzer, Todd, and the ABC Research Group's shift of emphasis from “coherence” to “correspondence” criteria, their rejection of optimality in human decision making is premature: In many situations, experts can achieve near-optimal performance. Moreover, this competence does not require implausible computing power. The models Gigerenzer et al. evaluate fail to account for many of the most robust properties of human decision making, including examples of optimality.
    Direct download (7 more)  
     
    My bibliography  
     
    Export citation  
  22. David R. Shanks & Mark F. St John (1996). Implicit Learning: What Does It All Mean? Behavioral and Brain Sciences 19 (3):557-558.
    In the original target article (Shanks & St. John 1994), one of our principal conclusions was that there is almost no evidence that learning can occur outside awareness. The continuing commentaries raise some interesting questions, especially about the definition of learning, but do not lead us to abandon our conclusion.
    Direct download (3 more)  
     
    My bibliography  
     
    Export citation  
  23. David R. Shanks, R. E. A. Green & J. A. Kolodny (1994). A Critical Examination of the Evidence for Unconscious (Implicit) Learning. In Carlo Umilta & Morris Moscovitch (eds.), Consciousness and Unconscious Information Processing: Attention and Performance 15. MIT Press.
     
    My bibliography  
     
    Export citation  
  24. David R. Shanks & Mark F. St John (1994). Characteristics of Dissociable Human Learning Systems. Behavioral and Brain Sciences 17 (3):367-395.
    Direct download (2 more)  
     
    My bibliography  
     
    Export citation  
  25. David R. Shanks & M. F. St John (1994). Characteristics of Dissociable Human Learning Systems. Behavioral and Brain Sciences 17 (3):367-447.
    A number of ways of taxonomizing human learning have been proposed. We examine the evidence for one such proposal, namely, that there exist independent explicit and implicit learning systems. This combines two further distinctions, (1) between learning that takes place with versus without concurrent awareness, and (2) between learning that involves the encoding of instances (or fragments) versus the induction of abstract rules or hypotheses. Implicit learning is assumed to involve unconscious rule learning. We examine the evidence for implicit learning (...)
    Direct download (4 more)  
     
    My bibliography  
     
    Export citation  
  26. David R. Shanks & Mark F. St John (1994). How Should Implicit Learning Be Characterized? Behavioral and Brain Sciences 17 (3):427-447.
    Direct download (2 more)  
     
    My bibliography  
     
    Export citation  
  27. David R. Shanks & Anthony Dickinson (1990). Contingency Awareness in Evaluative Conditioning: A Comment on Baeyens, Eelen, and van den Bergh. Cognition and Emotion 4 (1):19-30.
  28. David R. Shanks & Anthony Dickinson (1988). The Role of Selective Attribution in Causality Judgment. In Denis J. Hilton (ed.), Contemporary Science and Natural Explanation: Commonsense Conceptions of Causality. New York University Press.
    No categories
     
    My bibliography  
     
    Export citation  
  29. David R. Shanks (1985). Hume on the Perception of Causality. Hume Studies 11 (1):94-108.