Can we change how people reason? Effects of instructions to reason differently and reasoning strategy.

Mental model (Johnson-Laird, 2001) and probabilistic theories (Oaksford & Chater, 2009) claim to provide distinct explanations of human reasoning. However, the dual strategy model of reasoning suggests that this distinction corresponds to different reasoning strategies, termed counterexample and statistical, respectively. There is clear evidence that most people have a preference for a given strategy, and that this predicts performance on a variety of forms of reasoning and judgment (Thompson & Markovits, 2021). To date, however, the evidence for this conclusion has been correlational in nature; in the current studies, we manipulated strategy use. To this end, we gave people (N = 885) explicit instructions to reason either using a counterexample strategy or a probabilistic strategy. In two studies, we observed that the ability to follow these instructions was constrained by people's spontaneous strategy use, and that the effect of instructions carried over to two subsequent forms of reasoning (a) belief-biased inferences and (b) base-rate judgments. Finally, the ability to follow instructions was correlated with reasoning accuracy on both tasks. These results provide strong evidence for the underlying reality of the dual strategy model and show that explicit instructions to reason differently can modify performance on different forms of reasoning. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Not feeling right about uncertainty monitoring.

De Neys proposed a "switch" model to address what he argued to be lacuna in dual-process theory, in which he theorized about the processes that initiate and terminate analytic thinking. We will argue that the author neglected to acknowledge the abundant literature on metacognitive functions, specifically, the meta-reasoning framework developed by Ackerman and Thompson (2017), that addresses just those questions.

When Type 2 Processing Misfires: The Indiscriminate Use of Statistical Thinking about Reasoning Problems.

Research on dual-process theories of judgment makes abundant use of reasoning problems that present a conflict between Type 1 intuitive responses and Type 2 rule-based responses. However, in many of these reasoning tasks, there is no way to discriminate between the adequate and inadequate use of rules based on logical or probabilistic principles. To experimentally discriminate between the two, we developed a new set of problems: rule-inadequate versions of standard base-rate problems (where base rates are made irrelevant). Across four experiments, we observed conflict sensitivity (measured in terms of response latencies and response confidence) in responses to standard base-rate problems but also in responses to rule-inadequate versions of these problems. This failure to discriminate between real and merely apparent (or spurious) conflict suggests that participants often misuse statistical information and draw conclusions based on irrelevant base rates. We conclude that inferring the sound use of statistical rules from normatively correct responses to standard conflict problems may be unwarranted when this kind of reasoning bias is not controlled for.

Logical intuition is not really about logic.

Recent research suggests that reasoners are able to draw simple logical or probabilistic inferences relatively intuitively and automatically, a capacity that has been termed "logical intuition" (see, e.g., De Neys & Pennycook, 2019). A key finding in support of this interpretation is that conclusion validity consistently interferes with judgments of conclusion believability, suggesting that information about logical validity is available quickly enough to interfere with belief judgments. In this study, we examined whether logical intuitions arise because reasoners are sensitive to the logical features of a problem or another structural feature that just happens to align with logical validity. In three experiments (N = 113, 137, and 254), we presented participants with logical (determinate) and pseudological (indeterminate) arguments and asked them to judge the validity or believability of the conclusion. Logical arguments had determinately valid or invalid conclusions, whereas pseudological arguments were all logically indeterminate, but some were pseudovalid (possible strong arguments) and others pseudoinvalid (possible weak arguments). Experiments 1 and 2 used simple modus ponens and affirming the consequent structures; Experiment 3 used more complex denying the antecedent and modus tollens structures. In all three experiments, we found that pseudovalidity interfered with belief judgments to the same extent as real validity. Altogether, these findings suggest that while people are able to draw inferences intuitively, and these inferences impact belief judgments, they are not logical intuitions. Rather, the intuitive inferences are driven by the processing of more superficial structural features that happen to align with logical validity. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Reasoning strategy vs cognitive capacity as predictors of individual differences in reasoning performance.

The dual strategy model posits that reasoners rely on two information processing strategies when making inferences: The statistical strategy generates a rapid probabilistic estimate based on associative access to a wide array of information, and the counterexample strategy uses a more focused representation allowing for a search for potential counterexamples. In this paper, we focused on individual differences in strategy use as a predictor of performance on four reasoning tasks: Belief bias, base rate neglect, conjunction fallacy, and denominator neglect. Predictions from the strategy use model were contrasted with predictions from Dual Process Theories, which suggest that individual differences in performance reflect variations in cognitive ability. In each of four studies, a large number (N ≈ 200) completed one of the above reasoning tasks, a strategy use diagnostic questionnaire, and measures of IQ, cognitive reflection, and numeracy. In three of four studies, individual differences in strategy use predicted differences in reasoning performance when the effects of the other variables were eliminated. Bayesian analysis indicated that none of the individual differences measures predicted a significant portion of variance on the conjunction fallacy task, and that strategy use was a strong predictor on the remaining three tasks. This research suggests that the type of strategy that is adopted paves a road to successful reasoning that is independent of cognitive capacity.

Eye-tracking IQ: Cognitive capacity and strategy use on a ratio-bias task.

This study tested the relationship between strategy use (assessed by eye-gaze patterns), cognitive ability (CA), and reasoning performance on a ratio-bias task. For the ratio-bias problems, participants (N = 125) chose which of two ratios was larger; each ratio was represented both as a fraction and as a picture. Problems were solved in two blocks: once under a deadline (Time1) and once in free time (Time2). Consistent with the assumption of dual process theories that CA is needed to overturn a pre-potent, initial response (Evans & Stanovich, 2013), CA was positively associated with correct performance at Time2, as well as the increase in performance from Time1 to Time2. However, strategy use predicted performance independently of CA at Time2, and accounted for the relationship between CA and improvement between Time1 and Time2: reasoners who attended to the fractions rather than to the misleading pictures performed better, regardless of CA. CA also predicted performance at Time1. Together, these findings suggest that the robust relationship between CA and reasoning (Stanovich, 1999) may arise because 1) high capacity reasoners are more likely to "intuit" the initial answer and 2) because CA is correlated with good strategy use, which, in turn, predicts performance.

The smart intuitor: Cognitive capacity predicts intuitive rather than deliberate thinking.

Cognitive capacity is commonly assumed to predict performance in classic reasoning tasks because people higher in cognitive capacity are believed to be better at deliberately correcting biasing erroneous intuitions. However, recent findings suggest that there can also be a positive correlation between cognitive capacity and correct intuitive thinking. Here we present results from 2 studies that directly contrasted whether cognitive capacity is more predictive of having correct intuitions or successful deliberate correction of an incorrect intuition. We used a two-response paradigm in which people were required to give a fast intuitive response under time pressure and cognitive load and afterwards were given the time to deliberate. We used a direction-of change analysis to check whether correct responses were generated intuitively or whether they resulted from deliberate correction (i.e., an initial incorrect-to-correct final response change). Results showed that although cognitive capacity was associated with the correction tendency (overall r = 0.22) it primarily predicted correct intuitive responding (overall r = 0.44). These findings force us to rethink the nature of sound reasoning and the role of cognitive capacity in reasoning. Rather than being good at deliberately correcting erroneous intuitions, smart reasoners simply seem to have more accurate intuitions.

Do smart people have better intuitions?

There is much evidence that high-capacity reasoners perform better on a variety of reasoning tasks (Stanovich, 1999), a phenomenon that is normally attributed to differences in either the efficacy or the probability of deliberate (Type II) engagement (Evans, 2007). In contrast, we hypothesized that intuitive (Type I) processes may differentiate high- and low-capacity reasoners. To test this hypothesis, reasoners were given a reasoning task modeled on the logic of the Stroop Task, in which they had to ignore one dimension of a problem when instructed to give an answer based on the other dimension (Handley, Newstead, & Trippas, 2011). Specifically, in Experiment 1, 112 reasoners were asked to give judgments consistent with beliefs or validity for 2 different types of deductive reasoning problems. In Experiment 2, 224 reasoners gave judgments consistent with beliefs (i.e., stereotypes) or statistics (i.e., base-rates) on a base rate task; half responded under a strict deadline. For all 3 problem types and regardless of the deadline, high-capacity reasoners performed better for logic/statistics than did belief judgments when the 2 conflicted, whereas the reverse was true for low-capacity reasoners. In other words, for high-capacity reasoners, statistical information interfered with their ability to make belief-based judgments, suggesting that, for them, probabilities may be more intuitive than stereotypes. Thus, at least part of the accuracy-capacity relationship observed in reasoning may be because of intuitive (Type I) processes. (PsycINFO Database Record

An analysis of the Canadian cognitive psychology job market (2006-2016).

How accomplished does one need to be to compete in the Canadian cognitive psychology job market? We looked at the publication record of everyone who was hired as an assistant professor in Canadian cognitive psychology divisions with PhD programs between 2006 and 2016 (N = 64). Individuals who were hired from 2006 to 2011 averaged 10 journal-article publications up to and including the year they were hired. However, this number increased by 57% to 18 publications between 2012 and 2016. Notably, this increase (a) occurred despite an increase in the number of positions since 2010, (b) was not restricted to top-ranked institutions, (c) did not come at the cost of decreasing quality in research (based on citations), and (d) was not driven by longer postdoctoral fellowships. To supply context, we obtained data on the publication records of 98 eminent and early-career award-winning cognitive psychologists when they obtained their first faculty positions. The correlation between year of hire and publication number in the full sample was strongly positive (r = .47) and driven primarily by a substantial increase in recent years, which suggests that the increasingly competitive job market is not specific to Canada. Finally, we found that behaviour (as opposed to neuroscience) researchers and those who obtained their PhDs from Canadian universities may be at particular risk in the job market. At a time when increasing numbers of PhDs are graduating from cognitive psychology programs, it has likely never been more difficult to obtain a faculty position. (PsycINFO Database Record

Utilitarian Moral Judgment Exclusively Coheres with Inference from Is to Ought.

Faced with moral choice, people either judge according to pre-existing obligations (deontological judgment), or by taking into account the consequences of their actions (utilitarian judgment). We propose that the latter coheres with a more general cognitive mechanism - deontic introduction, the tendency to infer normative ('deontic') conclusions from descriptive premises (is-ought inference). Participants were presented with vignettes that allowed either deontological or utilitarian choice, and asked to draw a range of deontic conclusions, as well as judge the overall moral rightness of each choice separately. We predicted and found a selective defeasibility pattern, in which manipulations that suppressed deontic introduction also suppressed utilitarian moral judgment, but had little effect on deontological moral judgment. Thus, deontic introduction coheres with utilitarian moral judgment almost exclusively. We suggest a family of norm-generating informal inferences, in which normative conclusions are drawn from descriptive (although value-laden) premises. This family includes deontic introduction and utilitarian moral judgment as well as other informal inferences. We conclude with a call for greater integration of research in moral judgment and research into deontic reasoning and informal inference.

Interactions between inferential strategies and belief bias.

The dual strategy model of reasoning proposed by Verschueren, Schaeken, and d'Ydewalle (Thinking & Reasoning, 11(3), 239-278, 2005a; Memory & Cognition, 33(1), 107-119, 2005b) suggests that people can use either a statistical or a counterexample-based strategy to make deductive inferences. Subsequent studies have supported this distinction and investigated some properties of the two strategies. In the following, we examine the further hypothesis that reasoners using statistical strategies should be more vulnerable to the effects of conclusion belief. In each of three studies, participants were given abstract problems used to determine strategy use and three different forms of syllogism with believable and unbelievable conclusions. Responses, response times, and feeling of rightness (FOR) measures were taken. The results show that participants using a statistical strategy were more prone to the effects of conclusion belief across all three forms of reasoning. In addition, statistical reasoners took less time to make inferences than did counterexample reasoners. Patterns of variation in response times and FOR ratings between believable and unbelievable conclusions were very similar for both strategies, indicating that both statistical and counterexample reasoners were aware of conflict between conclusion belief and premise-based reasoning.

Meta-Reasoning: Monitoring and Control of Thinking and Reasoning.

Meta-Reasoning refers to the processes that monitor the progress of our reasoning and problem-solving activities and regulate the time and effort devoted to them. Monitoring processes are usually experienced as feelings of certainty or uncertainty about how well a process has, or will, unfold. These feelings are based on heuristic cues, which are not necessarily reliable. Nevertheless, we rely on these feelings of (un)certainty to regulate our mental effort. Most metacognitive research has focused on memorization and knowledge retrieval, with little attention paid to more complex processes, such as reasoning and problem solving. In that context, we recently developed a Meta-Reasoning framework, used here to review existing findings, consider their consequences, and frame questions for future research.

Rule-based reasoning is fast and belief-based reasoning can be slow: Challenging current explanations of belief-bias and base-rate neglect.

It is commonly assumed that belief-based reasoning is fast and automatic, whereas rule-based reasoning is slower and more effortful. Dual-Process theories of reasoning rely on this speed-asymmetry explanation to account for a number of reasoning phenomena, such as base-rate neglect and belief-bias. The goal of the current study was to test this hypothesis about the relative speed of belief-based and rule-based processes. Participants solved base-rate problems (Experiment 1) and conditional inferences (Experiment 2) under a challenging deadline; they then gave a second response in free time. We found that fast responses were informed by rules of probability and logical validity, and that slow responses incorporated belief-based information. Implications for Dual-Process theories and future research options for dissociating Type I and Type II processes are discussed. (PsycINFO Database Record

When fast logic meets slow belief: Evidence for a parallel-processing model of belief bias.

Two experiments pitted the default-interventionist account of belief bias against a parallel-processing model. According to the former, belief bias occurs because a fast, belief-based evaluation of the conclusion pre-empts a working-memory demanding logical analysis. In contrast, according to the latter both belief-based and logic-based responding occur in parallel. Participants were given deductive reasoning problems of variable complexity and instructed to decide whether the conclusion was valid on half the trials or to decide whether the conclusion was believable on the other half. When belief and logic conflict, the default-interventionist view predicts that it should take less time to respond on the basis of belief than logic, and that the believability of a conclusion should interfere with judgments of validity, but not the reverse. The parallel-processing view predicts that beliefs should interfere with logic judgments only if the processing required to evaluate the logical structure exceeds that required to evaluate the knowledge necessary to make a belief-based judgment, and vice versa otherwise. Consistent with this latter view, for the simplest reasoning problems (modus ponens), judgments of belief resulted in lower accuracy than judgments of validity, and believability interfered more with judgments of validity than the converse. For problems of moderate complexity (modus tollens and single-model syllogisms), the interference was symmetrical, in that validity interfered with belief judgments to the same degree that believability interfered with validity judgments. For the most complex (three-term multiple-model syllogisms), conclusion believability interfered more with judgments of validity than vice versa, in spite of the significant interference from conclusion validity on judgments of belief.

Uncertain deduction and conditional reasoning.

There has been a paradigm shift in the psychology of deductive reasoning. Many researchers no longer think it is appropriate to ask people to assume premises and decide what necessarily follows, with the results evaluated by binary extensional logic. Most every day and scientific inference is made from more or less confidently held beliefs and not assumptions, and the relevant normative standard is Bayesian probability theory. We argue that the study of "uncertain deduction" should directly ask people to assign probabilities to both premises and conclusions, and report an experiment using this method. We assess this reasoning by two Bayesian metrics: probabilistic validity and coherence according to probability theory. On both measures, participants perform above chance in conditional reasoning, but they do much better when statements are grouped as inferences, rather than evaluated in separate tasks.

Disfluent fonts don't help people solve math problems.

Prior research suggests that reducing font clarity can cause people to consider printed information more carefully. The most famous demonstration showed that participants were more likely to solve counterintuitive math problems when they were printed in hard-to-read font. However, after pooling data from that experiment with 16 attempts to replicate it, we find no effect on solution rates. We examine potential moderating variables, including cognitive ability, presentation format, and experimental setting, but we find no evidence of a disfluent font benefit under any conditions. More generally, though disfluent fonts slightly increase response times, we find little evidence that they activate analytic reasoning.

Deontic introduction: A theory of inference from is to ought.

Humans have a unique ability to generate novel norms. Faced with the knowledge that there are hungry children in Somalia, we easily and naturally infer that we ought to donate to famine relief charities. Although a contentious and lively issue in metaethics, such inference from "is" to "ought" has not been systematically studied in the psychology of reasoning. We propose that deontic introduction is the result of a rich chain of pragmatic inference, most of it implicit; specifically, when an action is causally linked to a valenced goal, valence transfers to the action and bridges into a deontic conclusion. Participants in 5 experiments were presented with utility conditionals in which an action results in a benefit, a cost, or neutral outcome (e.g., "If Lisa buys the booklet, she will pass the exam") and asked to evaluate how strongly deontic conclusions (e.g., "Lisa should buy the booklet") follow from the premises. Findings show that the direction of the conclusions was determined by outcome valence (Experiments 1a and 1b), whereas their strength was determined by the strength of the causal link between action and outcome (Experiments 1, 2a, and 2b). We also found that deontic introduction is defeasible and can be suppressed by additional premises that interfere with any of the links in the implicit chain of inference (Experiments 2a, 2b, and 3). We propose that deontic introduction is a species-specific generative capacity whose function is to regulate future behavior.

Metacognition and abstract reasoning.

The nature of people's meta-representations of deductive reasoning is critical to understanding how people control their own reasoning processes. We conducted two studies to examine whether people have a metacognitive representation of abstract validity and whether familiarity alone acts as a separate metacognitive cue. In Study 1, participants were asked to make a series of (1) abstract conditional inferences, (2) concrete conditional inferences with premises having many potential alternative antecedents and thus specifically conducive to the production of responses consistent with conditional logic, or (3) concrete problems with premises having relatively few potential alternative antecedents. Participants gave confidence ratings after each inference. Results show that confidence ratings were positively correlated with logical performance on abstract problems and concrete problems with many potential alternatives, but not with concrete problems with content less conducive to normative responses. Confidence ratings were higher with few alternatives than for abstract content. Study 2 used a generation of contrary-to-fact alternatives task to improve levels of abstract logical performance. The resulting increase in logical performance was mirrored by increases in mean confidence ratings. Results provide evidence for a metacognitive representation based on logical validity, and show that familiarity acts as a separate metacognitive cue.