Series Editor BRIAN H ROSS Beckman Institute and Department of Psychology University of Illinois, Urbana, Illinois Academic Press is an imprint of Elsevier 225 Wyman Street, Waltham, MA 02451, USA 525 B Street, Suite 1800, San Diego, CA 92101-4495, USA 125, London Wall, EC2Y 5AS, UK The Boulevard, Langford Lane, Kidlington, Oxford OX5 1GB, UK First edition 2015 Copyright © 2015 Elsevier Inc All rights reserved No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher Details on how to seek permission, further information about the Publisher’s permissions policies and our arrangements with organizations such as the Copyright Clearance Center and the Copyright Licensing Agency, can be found at our website: www.elsevier.com/permissions This book and the individual contributions contained in it are protected under copyright by the Publisher (other than as may be noted herein) Notices Knowledge and best practice in this field are constantly changing As new research and experience broaden our understanding, changes in research methods, professional practices, or medical treatment may become necessary Practitioners and researchers must always rely on their own experience and knowledge in evaluating and using any information, methods, compounds, or experiments described herein In using such information or methods they should be mindful of their own safety and the safety of others, including parties for whom they have a professional responsibility To the fullest extent of the law, neither the Publisher nor the authors, contributors, or editors, assume any liability for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions, or ideas contained in the material herein ISBN: 978-0-12-802273-3 ISSN: 0079-7421 For information on all Academic Press publications visit our website at http://store.elsevier.com/ CONTRIBUTORS Genna Angello Department of Psychology, Texas A&M University, College Station, TX, USA Sarah Brown-Schmidt Department of Psychology, University of Illinois, Urbana-Champaign, IL, USA Dorothy R Buchli Department of Psychology, University of California, Los Angeles, CA, USA Sarah H Creem-Regehr Department of Psychology, University of Utah, UT, USA Wim De Neys , UMR 8240, France CNRS, LaPsyDE , France Université Paris Descartes, Sorbonne Paris Cité, LaPsyDE , France Université de Caen Basse-Normandie, LaPsyDE Simon J Handley Cognition Institute, School of Psychology, Plymouth University, Plymouth, UK Jason L Hicks Department of Psychology, Louisiana State University, Baton Rouge, LA, USA Rebecca H Koppel Department of Psychology, University of Illinois at Chicago, Chicago, IL, USA Jeri L Little Department of Psychology, Washington University in St Louis, St Louis, MO, USA John F Nestojko Department of Psychology, Washington University in St Louis, St Louis, MO, USA Rachel Anna Ryskin Department of Psychology, University of Illinois, Urbana-Champaign, IL, USA Jeffrey J Starns Department of Psychological and Brain Sciences, University of Massachusetts Amherst, Amherst, MA, USA Jeanine K Stefanucci Department of Psychology, University of Utah, UT, USA Benjamin C Storm Department of Psychology, University of California, Santa Cruz, CA, USA William B Thompson School of Computing, University of Utah, UT, USA Dries Trippas Cognition Institute, School of Psychology, Plymouth University, Plymouth, UK Si On Yoon Department of Psychology, University of Illinois, Urbana-Champaign, IL, USA ix j CHAPTER ONE Heuristic Bias and Conflict Detection During Thinking Wim De Neys*, x, {, , UMR 8240, France *CNRS, LaPsyDE x , France Université Paris Descartes, Sorbonne Paris Cité, LaPsyDE { , France Université de Caen Basse-Normandie, LaPsyDE Corresponding author: E-mail: wim.de-neys@parisdescartes.fr Contents Introduction Review of Conflict Detection Studies 2.1 In the Beginning 2.2 The Brain in Conflict 2.3 More Memory Effects 2.4 Gut Conflict Feelings 2.5 Biased but in Doubt 2.6 Review Conclusion A Case for Logical Intuitions? 3.1 Implicit Detection 3.2 Automatic Detection 3.3 “Blink don’t Think?” and Other Misconceptions 3.3.1 3.3.2 3.3.3 3.3.4 11 13 14 15 17 18 18 19 20 Boundary Conditions: Elementary Logical Principles Can Detection be Hard?: Conflict and the Parallel Activation View Blink don’t Think? Power to the Unconscious? Where Do Logical Intuitions Come from? Does God Put Logical Intuitions in Our Brains? Further Implications 4.1 Of Blind Heuristic Thinkers and Rational Psychopaths 4.2 Switching from Intuitive to Deliberate Thinking 4.3 Individual Differences in Bias Susceptibility Conclusion and Take-Home Message References 21 22 22 23 24 24 25 27 28 29 Abstract Decades of reasoning and decision-making research have established that human judgment is often biased by intuitive heuristics Although this heuristic bias is well documented and widely featured in psychology textbooks, its precise nature is less clear A key question is whether reasoners detect the biased nature of their judgments My research is focusing on this detection process In a nutshell, results indicate that Psychology of Learning and Motivation, Volume 62 ISSN: 0079-7421 http://dx.doi.org/10.1016/bs.plm.2014.09.001 © 2015 Elsevier Inc All rights reserved j Wim De Neys despite their illogical response, people demonstrate a remarkable sensitivity to possible conflict between their heuristic judgment and elementary logical or probabilistic principles In this chapter, I present a detailed overview of the empirical studies that I have run and discuss theoretical implications I will clarify why the empirical detection findings have led me to hypothesize that people not only have heuristic intuitions but also logical intuitions I also explore implications for ongoing debates concerning our view of human rationality (“Are humans blind and ignorant heuristic thinkers?”), dual process theories of reasoning (“How intuitive and deliberate thinking interact?”), and the nature of individual differences in bias susceptibility (“when and why biased and unbiased reasoners start to diverge?”) INTRODUCTION One of my all-time favorite movie scenes comes from the iconic parody “This Is Spinal Tap.” The faux documentary covers a tour by the fictional British band “Spinal Tap.” In my favorite scene, Nigel, the band’s dimwitted lead guitarist, is giving the documentary director, Marty, a tour of his stage equipment1 When Nigel shows off his Marshall amplifiers, he points out that his volume knobs all have the highest setting of 11, unlike standard amplifiers, whose volume settings are typically numbered from to 10 Nigel proudly boasts that this is making his amplifiers sound “one louder” than the other amplifiers When Marty asks him why the 10 setting is not simply set to be louder, Nigel pauses, clearly confused, and meekly responds “But these go to eleven!” (Up to Eleven, 2014) I like the “Going to eleven” scene so much because it is presenting us with a hilarious but quite illustrative example of the biased nature of human judgment Nigel demonstrates here what is known as ratio bias or denominator neglect He is merely focusing on the absolute difference (11 is more than 10) but fails to think things through and take the denominator or relative difference (10/10 ¼ 11/11) into account The striking thing is that although it is great to laugh at Nigel in the movie scene, numerous studies have shown that even well-educated university students are not immune to this bias (e.g., Epstein, 1994) To illustrate, consider the following problem: You are faced with two trays each filled with white and red jelly beans You can draw one jelly bean without looking from one of the trays The For those who have not seen the scene yet, check https://www.youtube.com/watch? v¼4xgx4k83zzc Heuristic Bias and Conflict Detection During Thinking small tray contains a total of 10 jelly beans of which is red The large tray contains a total of 100 jelly beans of which are red From which tray should you draw to maximize your chance of drawing a red jelly bean? a The small tray b The large tray When presented with this problem many participants have a strong intuitive preference for the large tray From a logical point of view, this is not correct of course Although the large tray contains more red beans than the small tray (9 vs 1), there are also a lot more white beans in the large tray If you take the ratio of red and white beans in both trays into account it is clear that the small tray is giving you a 10% chance of picking a red bean (i.e., 1/10) while the large tray only offers a 9% chance (i.e., 9/100) However, just like Spinal Tap’s Nigel, many educated reasoners are tricked by the absolute difference and fail to solve this basic “ratio” problem (e.g., Epstein, 1994) The fact that the absolute number of red beans is higher in the large tray has such a strong intuitive pull on people’s thinking that they seem to neglect the ratio principle and end up being biased Decades of reasoning and decision-making research have shown that similar intuitive judgments are biasing people’s reasoning in a wide range of situations and tasks (Evans & Over, 1996; Evans, 2008; Kahneman & Frederick, 2002; Kahneman & Tversky, 1973) In general, this literature indicates that human reasoners have a strong tendency to base their inferences on fast intuitive impressions rather than on more demanding, deliberative reasoning In and by itself, this intuitive or so-called “heuristic” thinking can be useful because it is fast and effortless and can often provide valid problem solutions For example, in some situations there is no need to take ratios into account If you are playing around with your radio, you intuitively and rightly grasp that setting the volume knob to “10” will make it sound louder than setting it to “1.” For educated adults (in contrast to, say, my 2-year old son), there is no need to engage in much deliberation to arrive at this conclusion However, the problem is that our intuitions can also cue responses that conflict with more logical or probabilistic principles As the denominator neglect example illustrates, relying on mere intuitive thinking will bias our reasoning in that case (Evans, 2003; Kahneman, 2011; Stanovich & West, 2000) Although it is well established that our thinking can be biased by intuitive heuristics, the precise nature of this bias is less clear A wide range of views and potential key factors have been identified (e.g., Brainerd & Wim De Neys Reyna, 2001; De Neys & Bonnefon, 2013; Evans, 2007; Reyna & Brainerd, 2011; Stanovich, 2010; Stein, 1996) In my work I have focused on the role of the conflict monitoring or detection process The importance of this process follows from the simple fact that, as clarified above, relying on heuristic thinking can sometimes be useful but also runs the risk of arriving at logically biased answers2 Hence, for sound reasoning it is important to monitor our heuristic intuitions for possible conflict with logical or probabilistic considerations In the absence of any conflict it is perfectly fine to rely on mere heuristic intuitions but in case conflict is detected, one should refrain from it Unfortunately, although there is wide agreement concerning the importance of the conflict monitoring and detection process (Evans & Stanovich, 2013; Evans, 2007; Kahneman, 2011), there have been some quite different views on its efficiency For example, in the influential work of Kahneman (e.g., Kahneman & Frederick, 2002; Kahneman, 2011) heuristic bias is primarily attributed to lax monitoring In Kahnemans’ view, one of the main reasons for people ending up being biased is simply that they tend to overrely on heuristic thinking and will not detect conflict with logical considerations In other words, under this interpretation people are biased because they not realize that their heuristic answer is logically questionable However, other scholars suggested that conflict detection will typically be successful and argued that the difficulty lies in the resolution of this conflict (e.g., Epstein, 1994; Houdé, 1997; Sloman, 1996) That is, people would have little trouble detecting that a cued heuristic is not logically warranted but subsequently face difficulties when they try to block or inhibit the salient and tempting heuristic response, for example The answer to the bias or conflict detection efficiency question (“do we detect that we are biased or not?”) has far-stretching implications for our view of human rationality and related core debates in the reasoning and decision-making field My research over the past couple of years has dealt with these issues Together with my colleagues I have run an extensive set of empirical studies to test the efficiency of the conflict detection process I have also spent quite some time reflecting on the theoretical implications For completeness, the expert reader might want to note that I will be using the label “correct” or “logical” response as a handy shortcut to refer to “the response that has traditionally been considered as correct or normative according to standard logic or probability theory.” The appropriateness of these traditional norms has sometimes been questioned in the reasoning field (e.g., see Stanovich & West, 2000; for a review) Under this interpretation, the heuristic response should not be labeled as “incorrect” or “biased.” For the sake of simplicity I stick to the traditional labeling In the same vein, I use the term “logical” as a general header to refer both to standard logic and probability theory Heuristic Bias and Conflict Detection During Thinking My goal in this chapter is to present a comprehensive and accessible overview of this work In the first section, I will present a detailed review of our empirical conflict detection studies The following sections focus on the theoretical implications I will clarify why the conflict detection findings have led me to hypothesize that people not only have heuristic intuitions but also logical intuitions Next, I discuss implications for our view of human rationality (“Are humans blind and ignorant heuristic thinkers?”), dual process theories of reasoning (“How intuitive and deliberate thinking interact?”), and the nature of individual differences in bias susceptibility (“when and why biased and unbiased reasoners start to diverge?”) I should stress that I have written this chapter with the nonexpert educated reader in mind I have tried to present a comprehensive and accessible sketch of the key points and why I personally believe that they matter The interested expert reader can always refer to a number of recent publications (e.g., De Neys & Bonnefon, 2013; De Neys, 2012, 2014) for a more specialized discussion REVIEW OF CONFLICT DETECTION STUDIES My research on conflict detection during thinking has focused on people’s processing of the (in)famous classic tasks that have been studied for decades in the reasoning and decision-making field (e.g., ratio-bias task, base-rate neglect task, conjunction fallacy, belief bias syllogisms, bat-and-ball problem, etc.; illustration of these tasks can be found in Table 1) Giving the correct response in these tasks only requires the application of some very basic logical or probabilistic principles However, as the introductory ratio-bias example illustrated, the tasks are constructed such that they intuitively cue a tempting heuristic response that conflicts with these principles The basic question that the detection studies have been trying to answer is whether people are sensitive to this conflict and notice that their heuristic response is questionable As I will illustrate, to this the studies typically contrast people’s processing of the classic problems with newly constructed control versions In the control or no-conflict versions the conflict is removed and the cued heuristic response is consistent with the logical response For example, a no-conflict control version of the introductory ratio-bias problem could simply state that the large tray contains 11 (instead of 9) red beans Everything else stays the same In this case both the absolute number of red beans (i.e., vs 11) and the ratio of red beans (i.e., 1/10 vs 11/100) would be higher in the large tray Hence, Wim De Neys Table Illustrations of the classic reasoning tasks that have been used in the conflict detection studies The left panel (A) shows the classic, standard versions and the right panel (B) shows the control versions The standard versions cue a heuristic response that conflicts with the correct logical response (i.e., the response considered correct according to standard logic or probability theory principles) In the control versions small content transformations guarantee that the cued heuristic response is consistent with the logical response A Standard “Conflict” versions B Control “No-conflict” versions Ratio-bias task: You are faced with two trays each filled with white and red jelly beans You can draw one jelly bean without looking from one of the trays Tray A contains a total of 10 jelly beans of which are red Tray B contains a total of 100 jelly beans of which 19 are red From which tray should you draw to maximize your chance of drawing a red jelly bean? Tray A* Tray Bỵ You are faced with two trays each lled with white and red jelly beans You can draw one jelly bean without looking from one of the trays Tray A contains a total of 10 jelly beans of which are red Tray B contains a total of 100 jelly beans of which 21 are red From which tray should you draw to maximize your chance of drawing a red jelly bean? Tray A Tray B*ỵ Base-rate neglect task: A psychologist wrote thumbnail descriptions of a sample of 1000 participants consisting of 995 females and males The description below was chosen at random from the 1000 available descriptions Jo is 23 years old and is finishing a degree in engineering On Friday nights, Jo likes to go out cruising with friends while listening to loud music and drinking beer Which one of the following two statements is most likely? Jo is a woman* Jo is a manỵ A psychologist wrote thumbnail descriptions of a sample of 1000 participants consisting of 995 males and females The description below was chosen at random from the 1000 available descriptions Jo is 23 years old and is finishing a degree in engineering On Friday nights, Jo likes to go out cruising with friends while listening to loud music and drinking beer Which one of the following two statements is most likely? Jo is a woman Jo is a man*ỵ Heuristic Bias and Conict Detection During Thinking Table Illustrations of the classic reasoning tasks that have been used in the conflict detection studies The left panel (A) shows the classic, standard versions and the right panel (B) shows the control versions The standard versions cue a heuristic response that conflicts with the correct logical response (i.e., the response considered correct according to standard logic or probability theory principles) In the control versions small content transformations guarantee that the cued heuristic response is consistent with the logical responsedcont'd A Standard “Conflict” versions B Control “No-conflict” versions Conjunction fallacy task: Bill is 34 He is intelligent, punctual but unimaginative, and somewhat lifeless In school, he was strong in mathematics but weak in social studies and humanities Which one of the following statements is most likely? Bill plays in a rock band for a hobby* Bill is an accountant and plays in a rock band for a hobbyỵ Bill is 34 He is intelligent, punctual but unimaginative, and somewhat lifeless In school, he was strong in mathematics but weak in social studies and humanities Which one of the following statements is most likely? Bill is an accountant*ỵ Bill is an accountant and plays in a rock band for a hobby Syllogistic reasoning task: Premises: all flowers need water roses need water Conclusion: roses are owers The conclusions follows logicallyỵ The conclusion does not follow logically* Premises: all flowers need water roses are owers Conclusion: roses need water The conclusions follows logically*ỵ The conclusion does not follow logically Bat-and-ball problem: A bat and a ball together cost $1.10 The bat costs $1 more than the ball How much does the ball cost? _ (* ¼ cents, ỵ ẳ 10 cents) *, Logical response; ỵ, heuristic response A bat and a ball together cost $1.10 The bat costs $1 How much does the ball cost? _ (* ẳ 10 cents, ỵ ẳ 10 cents) INDEX Note: Page numbers followed by “f” and “t” indicate figures and tables respectively A Above-chance-dependent retrieval, 112–113 Absolute distance perception, 198, 202–204 absolute spatial information, 198 affordance judgments, 199–200 egocentric distances, 198–199 human space perception, 199–200 paucity of visual information, 199 Absolute egocentric distance perception, 199–200 Absolute scale perception, 196–197 absolute distance perception, 202–204 affordance judgments, 204–205 blind walking, 201–202 distance-compression effect, 204 established effects of distance underestimation, 203t HMDs, 200–201, 204 large screen-based displays, 200–201 response measures for probing judgments, 202f VE distance perception evaluations, 201 Absolute spatial information, 198 Action space, 199 perceiving absolute scale in, 200–205 Affordance judgments, 199–200 Anterior cingulate cortex (ACC), 11–12 Aristotelian syllogisms, 53–54 Audience design, 61–64 experimental displays, 62f memory contributions, 78 in multiparty conversation, 67–71, 68f Autobiographical memory, 168–169, 171f, 183 comments and future directions, 174–175 individual differences, 170–172 remembering and forgetting trauma, 173–174 retrieval-induced forgetting and depression, 172–173 self-relevant memories, 169–170 Automatic detection, 19–20 Avatar See Virtual self-avatar B “Baby logic” studies, 23–24 Base-rate information, 18–19 neglect, 34–35, 36t, 46–47 problem, 39 Behaviors, 165–167 Belief bias, 36t, 42, 46–47 Bias-free method, 126–127 Biased reasoners, 18–19, 25, 28 detecting bias, 24–25 detecting conflict, 18 with lowest accuracy scores, 19–20 Biases, 15–17 Binding variability hypothesis, 120–121 Body-based feedback, 211–216 perception, 196–197 Brain in conflict, 11–13 logical intuitions, 23–24 C Casual observation, Category–cued recall, 156 Category–exemplar pairs, 156 Cognitive modeling approach, 47 Cognitive processes, 60 Common ground, 61–62, 67, 78, 90–91 assessment, 78 cup, 71–72 in language production, 62–63, 65 multiple distinct representations, 70–71 referential ambiguity, 65 225 j 226 Conflict, 54–56 brain in, 11–13 implicit conflict signal, 15–16 sensitivity, 19–20 Conflict activation view, 22 Conflict detection, 5–8, 38 See also Dual process theory (DPT); Heuristic bias; Logical intuitions base-rate problem, 39 biased but in doubt, 15–17 brain in conflict, 11–13 classic reasoning tasks, 6-7t efficiency, 8–11 evidence, 40 gut conflict feelings, 14–15 implicit measures, 39–40 knowledge-based response, 40 memory effects, 13–14 Conjunction fallacy, 39, 48–49, 36t “Context/feature”, 134–136 Context–context bindings, 121f, 125–126 Contextual cue, conversational partners as, 82–86 Contextual information, 78 partner-specific, 78–79 Converging methods, 17–18 Conversation See also People as contexts in conversation audience design, 61–64 experimental displays, 62f in multiparty conversation, 67–71, 68f participant role in conversation, 89–91 perspective-taking, 61–62, 65–67 conversational goals and, 71–72 interim summary, 76–77 spatial, 72–76 Conversational partners as contextual cue, 82 less relevancy, 85–86 memorial benefit, 83–84 motivation to encode, 83 partner-specific effects, 84 semantic representations, 83 Index Creative cognition, 175 comments and future directions, 180 predictor of ability to overcome fixation, 175–177 problem-solving-induced forgetting, 177–178 thinking-induced forgetting, 178–179 Cue independence, 182 Cue-specific forgetting, 183 Cued trials, 127–127 D De Neys’ model, 51–53 Decision-making, 165–167 field, 5–8 problems, 12 research, Default interventionist account (DI account), 35, 37, 50 Denominator neglect See Ratio bias Depression, retrieval-induced forgetting and, 172–173 Depth perception, 198–199 Destination memory, 111 DI account See Default interventionist account DI-PC hybrid model, 51 Disjunctive syllogism, 41–42 Double-face cuing method, 127 Dual process theory (DPT), 34 See also Conflict detection; Reasoning DI account, 35, 37 Handley & Trippas PC dual process model, 55f knowledge-based system, 50–51 PC account, 35 problem for, 26 of reasoning, 4–5 RLPFC, 38 T1 processing, 36–38 T1–T2 conflict, 35 T2 processing, 36–38 of thinking, 25–26 typical paradigms, 36t working memory load, 37 227 Index E G Ecological cue, 47–48 Effortful beliefs, 46 See also Dual process theory (DPT) belief bias, 46–47 cognitive modeling approach, 47 ecological cue, 47–48 effortless nature of knowledge, 48 knowledge effects in reasoning, 49 retrieval and integration of knowledge, 48–49 Egocentric distances, 198–199 Einstein’s razor, 180–181 Elementary logical principles, 20–21 Encoding factors ERP implicating, 118–120 fMRI evidence, 115–118 Encoding mechanisms, 77 association-based view, 78 attentional and memorial constraints on learning, 80–82 number of behaviorally relevant associations, 80–82 contextual information, 78 conversational partners as contextual cue, 82–86 interim summary, 86–87 motivation for limits on partner-specific representation formation, 79–80 partner-specific contextual information, 78–79 processing, 77–78 Environmental context, 62–63 Episodic memory, 102–103 Event-related potential (ERP), 118–120 implicating encoding factors, 118–120 External cuing, 123–123 Eyewitness memory, 155 comments and future directions, 161–162 experiments, 157t eyewitness information types, 158–159 methodology and typical results, 156 misinformation effects, 161 questions of durability, 159–160 “Gaze-tracking” procedure, 11–12 Gut conflict feelings, 14–15 F L Feeling of knowing (FOK), 113–114 Language comprehension, 65 H Handley & Trippas PC dual process model, 55f Head-mounted displays (HMDs), 200–201 Head-mounted displays-virtual environments (HMD-VEs), 207–208, 210 Heuristic bias, 3–4, 24 intuition, 4–5, 15–16 response, 51–52 thinking, Holistic memory representation, 112–113 Human memory, 102–103 Human rationality, 4–5, 24 Human space perception, 199–200 I Implicit conflict signal, 15–16 Implicit detection, 18–19 Intuitive logical reasoning, 52–53 Intuitive sensitivity, 46 Item-to-context binding, 121f, 124–125 “Item/object”, 134–136 Item–context bindings, 121f J “Joint retrieval” parameter, 106–107 K Knowledge effects in reasoning, 49 effortless nature, 48 knowledge-based response, 40 system, 50–51 retrieval and integration, 48–49 shared knowledge, 63–64 shared linguistic experience, 66 228 Language production common ground in, 62–63, 65 memory contributions to audience design, 78 Large screen-based displays, 200–201 Learning attentional and memorial constraints, 80–82 number of behaviorally relevant associations, 80–82 Logical intuitions, 4–5, 18, 23–24, 40–41, 51 See also Conflict detection; Dual process theory (DPT) automatic detection, 19–20 examples of problem, 43t geographical knowledge, 41 implicit detection, 18–19 instructional conditions, 42–44 instructional manipulation, 44 interference with knowledge-based judgments, 45 intuitive sensitivity, 46 knowledge and problem structure, 44–45 misconceptions, 20 conflict and parallel activation view, 22 elementary logical principles, 20–21 “unconscious thinking” movement, 22–23 rudimentary sensitivity to logical structure, 41–42 studies of belief bias, 42 syllogistic arguments, 45–46 M Modus ponens, 41–42 Multidimensional encoding paradigm, 113–114, 116–117 Multidimensional paradigms, 102–104 evidence for source-dependent retrieval, 106–107 related work in object recognition using, 132–134 stochastic dependence in absence of retrieval, 113–114 association with recollection, 107–108 relationship to attentional resources, 108–113 Index Mutual cuing mechanism, 120–121 retrieval cuing efforts to exploring evidence, 122–124 N Neural activation, 115–116 Neural conflict detection signal, 15–16 Neurophysiological recording methods, 120–120 Neuroscience, 130–130 Nrp items, 143–144, 144f, 152f, 161 O Object recognition, 132–134 Offender characteristics, 158–159 “Online” processing of language, 65 P Parallel activation view, 22 Parallel competitive dual process account (PC dual process account), 35 Partner-specific bindings, 87–88 context, 62–64 knowledge domains, 88–89 processing, 77–78 Paucity of visual information, 199 PC dual process account See Parallel competitive dual process account People as contexts in conversation See also Conversation encoding mechanisms, 77 association-based view, 78 attentional and memorial constraints on learning, 80–82 contextual information, 78 conversational partners as contextual cue, 82–86 interim summary, 86–87 motivation for limits on partnerspecific representation formation, 79–80 partner-specific contextual information, 78–79 partner–specific processing, 77–78 participant role in conversation, 89–91 partner-specific Index bindings, 87–88 knowledge domains, 88–89 people as contexts in language use, 61 Perceptual fidelity, 197–198, 200–201 Personal space, 199 Person–object association task, 109–110 Perspective-taking, 61–62, 65–67 conversational goals and, 71–72 interim summary, 76–77 spatial, 72–76 Problem-solving-induced forgetting, 177–178 Proximal stimuli, 198 R RAT See Remote Associates Test Ratio bias, 2–3, 5–8, 52–53 Realistic dual process model, 26–27 Reasoning belief bias, 42 biasing, classic reasoning tasks, 6-7t dual process theories, 4–5 electrodermal activation, 14–15 knowledge effects in, 49 sound, 3–4 Recollection, 118–118 of specific autobiographical information, 102–103 stochastic dependence, 105–106, 107–108 Referential ambiguity, 65 Remote Associates Test (RAT), 175–176 Retrieval cuing, 122–124 Retrieval-induced forgetting, 142–143, 180–181 autobiographical memory, 168–169, 171f, 183 comments and future directions, 174–175 individual differences, 170–172 remembering and forgetting trauma, 173–174 retrieval-induced forgetting and depression, 172–173 self-relevant memories, 169–170 in context, 181 229 cue independence, 182 experimental controls, 184–185 observations, 181–182 persistence, 183–184 theoretical assumptions, 182 creative cognition, 175 comments and future directions, 180 predictor of ability to overcome fixation, 175–177 problem-solving-induced forgetting, 177–178 thinking-induced forgetting, 178–179 eyewitness memory, 155 comments and future directions, 161–162 experiments, 157t eyewitness information types, 158–159 methodology and typical results, 156 misinformation effects, 161 questions of durability, 159–160 inhibition-based accounts, 145–147 noninhibitory-based accounts, 146 observed with visual scenes, 145 retrieval-practice paradigm, 143–144 social cognition, 162–163 behaviors, 165–167 comments and future directions, 168 decision-making, 165–167 information about other people, 163 social judgments, 165–167 socially shared retrieval-induced forgetting, 167–168 stereotypes and retrieval-induced forgetting, 163–165, 164f testing use in education, 148 comments and future directions, 153–155 competition role, 150–151 delay and integration, 149–150 fostering facilitation, 151–153 theoretical mechanisms, 147 Retrieval-practice phase, 156 Right lateral prefrontal cortex (RLPFC), 11–12, 38 Rp+ items, 143–144, 144f, 161 Rp–items, 143–144, 144f, 152f, 161 Rule-based logical reasoning, 50–51 230 S Salience, 51–52 Self-relevant memories, 169–170 Separate monitoring condition, 122–123 Simultaneous monitoring condition, 122–123 Skin conductance, 15 SMF See Source monitoring framework Social cognition, 162–163 behaviors, 165–167 comments and future directions, 168 decision-making, 165–167 information about other people, 163 social judgments, 165–167 socially shared retrieval-induced forgetting, 167–168 stereotypes and retrieval-induced forgetting, 163–165, 164f Social judgments, 165–167 Socially shared retrieval-induced forgetting, 167–168 Source memory, 102–104 Source monitoring framework (SMF), 103–103 Source retrieval parameters, 108–108 Source-dependent retrieval, 107–108, 110–111 Spatial perspective-taking conversational situation, 73f face-to-face conversation, 72–73 listeners, 75–76 speakers function, 74–75 Stochastic dependence in absence of retrieval, 113–114 association with recollection, 107–108 evidence from neuroscience, 115–115 ERP implicating encoding factors, 118–120 fMRI evidence for importance of encoding factors, 115–118 summary, 120–120 implications for memory representation and feature (in)dependence, 130–130 distinction between “item/object” and “context/feature”, 134–136 related work in object recognition, 132–134 Index responses, 130–131, 131 relationship to attentional resources, 108–113 theoretical mechanisms, 121f binding variability hypothesis, 120–121 mutual cuing mechanism, 120–121 retrieval cuing, 122–124 within-dimension cuing, 124–128 Syllogistic arguments, 45–46 T T1 processing, 36–38 heuristic response, 51–52 reliance on alignment, 52 T2 processing, 36–38 Target monitoring, 111 Thinking See also Conflict detection; Logical intuitions blind heuristic thinkers, 24–25 individual differences in bias susceptibility, 27–28 from intuitive to deliberate thinking, 25–27 rational psychopaths, 24–25 thinking-induced forgetting, 178–179 Three-party condition, 68 conversation, 68–69 situations, 68 Trauma, remembering and forgetting, 173–174 U Unbiased reasoners, 27–28 “Unconscious thinking” movement, 22–23 Uncued test trials, 127 V Ventral medial prefrontal cortex (VMPFC), 38 Virtual environments (VEs), 196 absolute distance perception, 198–200 absolute scale perception in action space, 200–205 body-movement importance, 205 231 Index approaches to feedback, 210–211 calibration of locomotion, 206–207 feedback effects and proposed mechanisms, 207–208 within-VE adaptation and performance, 208–210 perceptual fidelity, 197–198 virtual self-avatar, 211 Virtual self-avatar, 211 affordance judgments, 214–215 distance perception, 212–214 experimental conditions, 213f rubber hand illusion, 211–212 size estimation, 215–216 Vista space, 199 Visual cues, 199f Visual space perception, 198 VMPFC See Ventral medial prefrontal cortex W Within-dimension cuing analogous approach, 125–125 bias-free method, 126–127 context-to-context binding, 125–126 double-face cuing method, 127–127 Hicks and Starns study results, 129f item-to-context binding, 124–125 CONTENTS OF PREVIOUS VOLUMES VOLUME 40 Different Organization of Concepts and Meaning Systems in the Two Cerebral Hemispheres Dahlia W Zaidel The Causal Status Effect in Categorization: An Overview Woo-kyoung Ahn and Nancy S Kim Remembering as a Social Process Mary Susan Weldon Neurocognitive Foundations of Human Memory Ken A Paller Structural Influences on Implicit and Explicit Sequence Learning Tim Curran, Michael D Smith, Joseph M DiFranco, and Aaron T Daggy Recall Processes in Recognition Memory Caren M Rotello Reward Learning: Reinforcement, Incentives, and Expectations Kent C Berridge Spatial Diagrams: Key Instruments in the Toolbox for Thought Laura R Novick Reinforcement and Punishment in the Prisoner’s Dilemma Game Howard Rachlin, Jay Brown, and Forest Baker Index VOLUME 41 Categorization and Reasoning in Relation to Culture and Expertise Douglas L Medin, Norbert Ross, Scott Atran, Russell C Burnett, and Sergey V Blok On the Computational basis of Learning and Cognition: Arguments from LSA Thomas K Landauer Multimedia Learning Richard E Mayer Memory Systems and Perceptual Categorization Thomas J Palmeri and Marci A Flanery Conscious Intentions in the Control of Skilled Mental Activity Richard A Carlson Brain Imaging Autobiographical Memory Martin A Conway, Christopher W Pleydell-Pearce, Sharon Whitecross, and Helen Sharpe The Continued Influence of Misinformation in Memory: What Makes Corrections Effective? Colleen M Seifert Making Sense and Nonsense of Experience: Attributions in Memory and Judgment Colleen M Kelley and Matthew G Rhodes Real-World Estimation: Estimation Modes and Seeding Effects Norman R Brown Index VOLUME 42 Memory and Learning in FiguredGround Perception Mary A Peterson and Emily Skow-Grant Spatial and Visual Working Memory: A Mental Workspace Robert H Logie Scene Perception and Memory Marvin M Chun Spatial Representations and Spatial Updating Ranxiano Frances Wang Selective Visual Attention and Visual Search: Behavioral and Neural Mechanisms Joy J Geng and Marlene Behrmann 233 j 234 Categorizing and Perceiving Objects: Exploring a Continuum of Information Use Philippe G Schyns From Vision to Action and Action to Vision: A Convergent Route Approach to Vision, Action, and Attention Glyn W Humphreys and M Jane Riddoch Eye Movements and Visual Cognitive Suppression David E Irwin What Makes Change Blindness Interesting? Daniel J Simons and Daniel T Levin Index VOLUME 43 Ecological Validity and the Study of Concepts Gregory L Murphy Social Embodiment Lawrence W Barsalou, Paula M Niedinthal, Aron K Barbey, and Jennifer A Ruppert The Body’s Contribution to Language Arthur M Glenberg and Michael P Kaschak Using Spatial Language Laura A Carlson In Opposition to Inhibition Colin M MacLeod, Michael D Dodd, Erin D Sheard, Daryl E Wilson, and Uri Bibi Evolution of Human Cognitive Architecture John Sweller Cognitive Plasticity and Aging Arthur F Kramer and Sherry L Willis Index VOLUME 44 Goal-Based Accessibility of Entities within Situation Models Mike Rinck and Gordon H Bower Contents of Previous Volumes The Immersed Experiencer: Toward an Embodied Theory of Language Comprehension Rolf A Zwaan Speech Errors and Language Production: Neuropsychological and Connectionist Perspectives Gary S Dell and Jason M Sullivan Psycholinguistically Speaking: Some Matters of Meaning, Marking, and Morphing Kathryn Bock Executive Attention, Working Memory Capacity, and a Two-Factor Theory of Cognitive Control Randall W Engle and Michael J Kane Relational Perception and Cognition: Implications for Cognitive Architecture and the Perceptual-Cognitive Interface Collin Green and John E Hummel An Exemplar Model for Perceptual Catego-rization of Events Koen Lamberts On the Perception of Consistency Yaakov Kareev Causal Invariance in Reasoning and Learning Steven Sloman and David A Lagnado Index VOLUME 45 Exemplar Models in the Study of Natural Language Concepts Gert Storms Semantic Memory: Some Insights From Feature-Based Connectionist Attractor Networks Ken McRae On the Continuity of Mind: Toward a Dynamical Account of Cognition Michael J Spivey and Rick Dale Action and Memory Peter Dixon and Scott Glover Self-Generation and Memory Neil W Mulligan and Jeffrey P Lozito 235 Contents of Previous Volumes Aging, Metacognition, and Cognitive Control Christopher Hertzog and John Dunlosky The Psychopharmacology of Memory and Cognition: Promises, Pitfalls, and a Methodological Framework Elliot Hirshman Conversation as a Site of Category Learning and Category Use Dale J Barr and Edmundo Kronmuller Using Classification to Understand the Motivation-Learning Interface W Todd Maddox, Arthur B Markman, and Grant C Baldwin Index Index VOLUME 46 The Role of the Basal Ganglia in Category Learning F Gregory Ashby and John M Ennis Knowledge, Development, and Category Learning Brett K Hayes Concepts as Prototypes James A Hampton An Analysis of Prospective Memory Richard L Marsh, Gabriel I Cook, and Jason L Hicks Accessing Recent Events Brian McElree SIMPLE: Further Applications of a Local Distinctiveness Model of Memory Ian Neath and Gordon D.A Brown What is Musical Prosody? Caroline Palmer and Sean Hutchins Index VOLUME 47 Relations and Categories Viviana A Zelizer and Charles Tilly Learning Linguistic Patterns Adele E Goldberg Understanding the Art of Design: Tools for the Next Edisonian Innovators Kristin L Wood and Julie S Linsey Categorizing the Social World: Affect, Motivation, and Self-Regulation Galen V Bodenhausen, Andrew R Todd, and Andrew P Becker Reconsidering the Role of Structure in Vision Elan Barenholtz and Michael J Tarr VOLUME 48 The Strategic Regulation of Memory Accuracy and Informativeness Morris Goldsmith and Asher Koriat Response Bias in Recognition Memory Caren M Rotello and Neil A Macmillan What Constitutes a Model of Item-Based Memory Decisions? Ian G Dobbins and Sanghoon Han Prospective Memory and Metamemory: The Skilled Use of Basic Attentional and Memory Processes Gilles O Einstein and Mark A McDaniel Memory is More Than Just Remembering: Strategic Control of Encoding, Accessing Memory, and Making Decisions Aaron S Benjamin The Adaptive and Strategic Use of Memory by Older Adults: Evaluative Processing and Value-Directed Remembering Alan D Castel Experience is a Double-Edged Sword: A Computational Model of the Encoding/Retrieval Trade-Off With Familiarity Lynne M Reder, Christopher Paynter, Rachel A Diana, Jiquan Ngiam, and Daniel Dickison Toward an Understanding of Individual Differences In Episodic Memory: Modeling The Dynamics of Recognition Memory Kenneth J Malmberg Memory as a Fully Integrated Aspect of Skilled and Expert Performance K Anders Ericsson and Roy W Roring Index 236 VOLUME 49 Short-term Memory: New Data and a Model Stephan Lewandowsky and Simon Farrell Theory and Measurement of Working Memory Capacity Limits Nelson Cowan, Candice C Morey, Zhijian Chen, Amanda L Gilchrist, and J Scott Saults What Goes with What? Development of Perceptual Grouping in Infancy Paul C Quinn, Ramesh S Bhatt, and Angela Hayden Co-Constructing Conceptual Domains Through Family Conversations and Activities Maureen Callanan and Araceli Valle The Concrete Substrates of Abstract Rule Use Bradley C Love, Marc Tomlinson, and Todd M Gureckis Ambiguity, Accessibility, and a Division of Labor for Communicative Success Victor S Ferreira Lexical Expertise and Reading Skill Sally Andrews Index VOLUME 50 Causal Models: The Representational Infrastructure for Moral Judgment Steven A Sloman, Philip M Fernbach, and Scott Ewing Moral Grammar and Intuitive Jurisprudence: A Formal Model of Unconscious Moral and Legal Knowledge John Mikhail Law, Psychology, and Morality Kenworthey Bilz and Janice Nadler Protected Values and Omission Bias as Deontological Judgments Jonathan Baron and Ilana Ritov Attending to Moral Values Rumen Iliev, Sonya Sachdeva, Daniel M Bartels, Craig Joseph, Satoru Suzuki, and Douglas L Medin Contents of Previous Volumes Noninstrumental Reasoning over Sacred Values: An Indonesian Case Study Jeremy Ginges and Scott Atran Development and Dual Processes in Moral Reasoning: A Fuzzy-trace Theory Approach Valerie F Reyna and Wanda Casillas Moral Identity, Moral Functioning, and the Development of Moral Character Darcia Narvaez and Daniel K Lapsley “Fools Rush In”: AJDM Perspective on the Role of Emotions in Decisions, Moral and Otherwise Terry Connolly and David Hardman Motivated Moral Reasoning Peter H Ditto, David A Pizarro, and David Tannenbaum In the Mind of the Perceiver: Psychological Implications of Moral Conviction Christopher W Bauman andLinda J Skitka Index VOLUME 51 Time for Meaning: Electrophysiology Provides Insights into the Dynamics of Representation and Processing in Semantic Memory Kara D Federmeier and Sarah Laszlo Design for a Working Memory Klaus Oberauer When Emotion Intensifies Memory Interference Mara Mather Mathematical Cognition and the Problem Size Effect Mark H Ashcraft and Michelle M Guillaume Highlighting: A Canonical Experiment John K Kruschke The Emergence of Intention Attribution in Infancy Amanda L Woodward, Jessica A Sommerville, Sarah Gerson, Annette M.E Henderson, and Jennifer Buresh 237 Contents of Previous Volumes Reader Participation in the Experience of Narrative Richard J Gerrig and Matthew E Jacovina Aging, Self-Regulation, and Learning from Text Elizabeth A L Stine-Morrow and Lisa M.S Miller Toward a Comprehensive Model of Comprehension Danielle S McNamara and Joe Magliano Index VOLUME 52 Naming Artifacts: Patterns and Processes Barbara C Malt Causal-Based Categorization: A Review Bob Rehder The Influence of Verbal and Nonverbal Processing on Category Learning John Paul Minda and Sarah J Miles The Many Roads to Prominence: Understanding Emphasis in Conversation Duane G Watson Defining and Investigating Automaticity in Reading Comprehension Katherine A Rawson Rethinking Scene Perception: A Multisource Model Helene Intraub Components of Spatial Intelligence Mary Hegarty Toward an Integrative Theory of Hypothesis Generation, Probability Judgment, and Hypothesis Testing Michael Dougherty, Rick Thomas, and Nicholas Lange The Self-Organization of Cognitive Structure James A Dixon, Damian G Stephen, Rebecca Boncoddo, and Jason Anastas Index VOLUME 53 Adaptive Memory: Evolutionary Constraints on Remembering James S Nairne Digging into Dé a Vu: Recent Research on Possible Mechanisms Alan S Brown and Elizabeth J Marsh Spacing and Testing Effects: A Deeply Critical, Lengthy, and At Times Discursive Review of the Literature Peter F Delaney, Peter P J L Verkoeijen, and Arie Spirgel How One’s Hook Is Baited Matters for Catching an Analogy Jeffrey Loewenstein Generating Inductive Inferences: Premise Relations and Property Effects John D Coley and Nadya Y Vasilyeva From Uncertainly Exact to Certainly Vague: Epistemic Uncertainty and Approximation in Science and Engineering Problem Solving Christian D Schunn Event Perception: A Theory and Its Application to Clinical Neuroscience Jeffrey M Zacks and Jesse Q Sargent Two Minds, One Dialog: Coordinating Speaking and Understanding Susan E Brennan, Alexia Galati, and Anna K Kuhlen Retrieving Personal Names, Referring Expressions, and Terms of Address Zenzi M Griffin Index VOLUME 54 Hierarchical Control of Cognitive Pro-cesses: The Case for Skilled Typewriting Gordon D Logan and Matthew J.C Crump Cognitive Distraction While Multitasking in the Automobile David L Strayer, Jason M Watson, and Frank A Drews 238 Psychological Research on Joint Action: Theory and Data G€ unther Knoblich, Stephen Butterfill, and Natalie Sebanz Self-Regulated Learning and the Allocation of Study Time John Dunlosky and Robert Ariel The Development of Categorization Vladimir M Sloutsky and Anna V Fisher Systems of Category Learning: Fact or Fantasy? Ben R Newell, John C Dunn, and Michael Kalish Abstract Concepts: Sensory-Motor Grounding, Metaphors, and Beyond Diane Pecher, Inge Boo, and Saskia Van Dantzig Thematic Thinking: The Apprehension and Consequences of Thematic Relations Zachary Estes, Sabrina Golonka, and Lara L Jones Index VOLUME 55 Ten Benefits of Testing and Their Applications to Educational Practice Henry L Roediger III, Adam L Putnam and Megan A Smith Cognitive Load Theory John Sweller Applying the Science of Learning to Multimedia Instruction Richard E Mayer Incorporating Motivation into a Theoretical Framework for Knowledge Transfer Timothy J Nokes and Daniel M Belenky On the Interplay of Emotion and Cognitive Control: Implications for Enhancing Academic Achievement Sian L Beilock and Gerardo Ramirez There Is Nothing So Practical as a Good Theory Robert S Siegler, Lisa K Fazio, and Aryn Pyke Contents of Previous Volumes The Power of Comparison in Learning and Instruction: Learning Outcomes Supported by Different Types of Comparisons Bethany Rittle-Johnson and Jon R Star The Role of Automatic, Bottom-Up Processes: In the Ubiquitous Patterns of Incorrect Answers to Science Questions Andrew F Heckler Conceptual Problem Solving in Physics Jose P Mestre, Jennifer L Docktor, Natalie E Strand, and Brian H Ross Index VOLUME 56 Distinctive Processing: The Coaction of Similarity and Difference in Memory R Reed Hunt Retrieval-Induced Forgetting and Inhibition: A Critical Review Michael F Verde False Recollection: Empirical Findings and Their Theoretical Implications Jason Arndt Reconstruction from Memory in Naturalistic Environments Mark Steyvers and Pernille Hemmer Categorical Discrimination in Humans and Animals: All Different and Yet the Same? Edward A Wasserman and Leyre Castro How Working Memory Capacity Affects Problem Solving Jennifer Wiley and Andrew F Jarosz Juggling Two Languages in One Mind: What Bilinguals Tell Us About Language Processing and its Consequences for Cognition Judith F Kroll, Paola E Dussias, Cari A Bogulski and Jorge R Valdes Kroff Index 239 Contents of Previous Volumes VOLUME 57 Meta-Cognitive Myopia and the Dilemmas of Inductive-Statistical Inference Klaus Fiedler Relations Between Memory and Reasoning Evan Heit, Caren M Rotello and Brett K Hayes The Visual World in Sight and Mind: How Attention and Memory Interact to Determine Visual Experience James R Brockmole, Christopher C Davoli and Deborah A Cronin Spatial Thinking and STEM Education: When, Why, and How? David H Uttal and Cheryl A Cohen Emotions During the Learning of Difficult Material Arthur C Graesser and Sidney D’Mello Specificity and Transfer of Learning Alice F Healy and Erica L Wohldmann What Do Words Do? Toward a Theory of Language-Augmented Thought Gary Lupyan Index VOLUME 58 Learning Along With Others Robert L Goldstone, Thomas N Wisdom, Michael E Roberts, Seth Frey Space, Time, and Story Barbara Tversky, Julie Heiser, Julie Morrison The Cognition of Spatial Cognition: Domain-General within Domainspecific Holly A Taylor, Tad T Brunyé Perceptual Learning, Cognition, and Expertise Philip J Kellman, Christine M Massey Causation, Touch, and the Perception of Force Phillip Wolff, Jason Shepard Categorization as Causal Explanation: Discounting and Augmenting in a Bayesian Framework Daniel M Oppenheimer, Joshua B Tenenbaum, Tevye R Krynski Individual Differences in Intelligence and Working Memory: A Review of Latent Variable Models Andrew R.A Conway, Kristof Kovacs Index VOLUME 59 Toward a Unified Theory of Reasoning P.N Johnson-Laird, Sangeet S Khemlani The Self-Organization of Human Interaction Rick Dale, Riccardo Fusaroli, Nicholas D Duran, Daniel C Richardson Conceptual Composition: The Role of Relational Competition in the Comprehension of Modifier-Noun Phrases and Noun–Noun Compounds Christina L Gagné, Thomas L Spalding List-Method Directed Forgetting in Cognitive and Clinical Research: A Theoretical and Methodological Review Lili Sahakyan, Peter F Delaney, Nathaniel L Foster, Branden Abushanab Recollection is Fast and Easy: Pupillometric Studies of Face Memory Stephen D Goldinger, Megan H Papesh A Mechanistic Approach to Individual Differences in Spatial Learning, Memory, and Navigation Amy L Shelton, Steven A Marchette, Andrew J Furman When Do the Effects of Distractors Provide a Measure of Distractibility? Alejandro Lleras, Simona Buetti, J Toby Mordkoff Index VOLUME 60 The Middle Way: Finding the Balance between Mindfulness and MindWandering 240 Contents of Previous Volumes Jonathan W Schooler, Michael D Mrazek, Michael S Franklin, Benjamin Baird, Benjamin W Mooneyham, Claire Zedelius, and James M Broadway What Intuitions Are and Are Not Valerie A Thompson The Sense of Recognition during Retrieval Failure: Implications for the Nature of Memory Traces Anne M Cleary About Practice: Repetition, Spacing, and Abstraction Thomas C Toppino and Emilie Gerbier The Rise and Fall of the Recent Past: A Unified Account of Immediate Repetition Paradigms David E Huber Does the Concept of Affordance Add Anything to Explanations of Stimulus– Response Compatibility Effects? Robert W Proctor and James D Miles The Function, Structure, Form, and Content of Environmental Knowledge David Waller and Nathan Greenauer The Control of Visual Attention: Toward a Unified Account Shaun P Vecera, Joshua D Cosman, Daniel B Vatterott, and Zachary J.J Roper VOLUME 61 Index Index Descriptive and Inferential Problems of Induction: Toward a Common Framework Charles W Kalish and Jordan T Thevenow-Harrison What Does It Mean to be Biased: Motivated Reasoning and Rationality Ulrike Hahn and Adam J.L Harris Probability Matching, Fast and Slow Derek J Koehler and Greta James Cognition in the Attention Economy Paul Atchley and Sean Lane Memory Recruitment: A Backward Idea About Masked Priming Glen E Bodner and Michael E.J Masson Role of Knowledge in Motion Extrapolation: The Relevance of an Approach Contrasting Experts and Novices André Didierjean, Vincent Ferrari, and Colin Bl€attler Retrieval-Based Learning: An Episodic Context Account Jeffrey D Karpicke, Melissa Lehman, and William R Aue Consequences of Testing Memory Kenneth J Malmberg, Melissa Lehman, Jeffrey Annis, Amy H Criss, and Richard M Shiffrin ... Department of Psychology, University of Utah, UT, USA Benjamin C Storm Department of Psychology, University of California, Santa Cruz, CA, USA William B Thompson School of Computing, University of Utah,... detect the biased nature of their judgments My research is focusing on this detection process In a nutshell, results indicate that Psychology of Learning and Motivation, Volume 62 ISSN: 0079-7421 http://dx.doi.org/10.1016/bs.plm.2014.09.001... Department of Psychology, Texas A&M University, College Station, TX, USA Sarah Brown-Schmidt Department of Psychology, University of Illinois, Urbana-Champaign, IL, USA Dorothy R Buchli Department of Psychology,