In this paper I argue that we can understand incommensurability in a naturalistic, psychological manner. Cognitive habits can be acquired and so differ between individuals. Drawing on psychological work concerning analogical thinking and thinking with schemata, I argue that incommensurability arises between individuals with different cognitive habits and between groups with different shared cognitive habits.

This study explored how historians with different background knowledge read a series of primary source documents. Two university-based historians thought aloud as they read documents about Abraham Lincoln and the question of slavery, with the broad goal of understanding Lincoln's views on race. The first historian brought detailed content knowledge to the documents; the second historian was familiar with some of the themes in the documents but quickly became confused in the details. After much cognitive flailing, the second historian was (...) able to piece together an interpretative structure that brought him by the task's end to where his more knowledgeable colleague began. Data analysis focused on how, lacking detailed content knowledge, this historian was able to regain his intellectual footing, work through confusion, and resist the urge to simplify. Implications of this work for cognitive analyses in history and education are discussed. (shrink)

We do not all make choices, reason, interpret our experience, or respond to our environment in the same way. A recent surge of scientific interest has thrust these individual differences into the spotlight: researchers in cognitive psychology and neuroscience are now devoting increasing attention to cognitive variation. The philosophical dimensions of this research, however, have yet to be systematically explored. Here I make an initial foray by considering how cognitive variation is characterized. I present a central dilemma facing descriptions of (...) individual differences, discuss several distinctions used to categorize variation, and show that these distinctions require further elaboration. Finally, by canvassing several philosophical topics for which the characterization of cognitive variation may have significant implications, I argue that philosophers should take note of how and why our minds differ. (shrink)

Toulmin’s (1958) model of argument was employed in the analysis of verbal protocols obtained during the solving of ill-structured problems. The participants were experts in the domain under study. For the analysis the Toulmin model was extended in order to enable description of lines of argument found in protocols as long as 10 paragraphs. Results included: (1) That while the protocol was comprised of a large number of specific arguments, the analysis provided for tracing a solver’s line of argument. (2) (...) On occasion datum and backing were difficult to distinguish. (3) Warrants essentially were not stated, although substantial backing was provided. However, as perhaps would be expected, the Toulmin model did not provide for delineation of components of the problem-solving process. A second analysis assuming a “higher level” problem-solving structure and a “lower level” argument structure produced an integrated problem-solving – argumentation structure depicting how reasoning is used in relation to particular task goals. Finally, at a more general level, problem solving was considered as a classical rhetorical structure. (shrink)

The term conceptual simulation refers to a type of everyday reasoning strategy commonly called “what if” reasoning. It has been suggested in a number of contexts that this type of reasoning plays an important role in scientific discovery; however, little direct evidence exists to support this claim. This article proposes that conceptual simulation is likely to be used in situations of informational uncertainty, and may be used to help scientists resolve that uncertainty. We conducted two studies to investigate the relationship (...) between conceptual simulation and informational uncertainty. Study 1 was an in vivo study of expert scientists; the results suggest that scientists do use conceptual simulation in situations of informational uncertainty, and that they use conceptual simulation to make inferences from their data using the analogical reasoning process of alignment by similarity detection. Study 2 experimentally manipulated experts' level of uncertainty and provides further support for the hypothesis that conceptual simulation is more likely to be used in situations of informational uncertainty. Finally, we discuss the relationship between conceptual simulation and other types of reasoning using qualitative mental models. (shrink)

Penn et al. argue that the complexity of relational learning is beyond animals. We discuss a model that demonstrates relational learning need not involve complex processes. Novel stimuli are compared to previous experiences stored in memory. As learning shifts attention from featural to relational cues, the comparison process becomes more analogical in nature, successfully accounting for performance across species and development.

This work examines the influence of reference dependence, including value selection bias and congruence effects, on diagnostic reasoning. Across two studies, we explored how dependence on the initial problem structure influences the ability to solve simplified precursors to the more traditional Bayesian reasoning problems. Analyses evaluated accuracy and types of response errors as a function of congruence between the problem presentation and question of interest, amount of information, need for computation, and individual differences in numerical abilities. Across all problem variations, (...) there was consistent and strong evidence of a value selection bias in that incorrect responses almost always conformed to values that were provided in the problem rather than other errors including those related to computation. The most consistent and unexpected error across all conditions in the first experiment was that people were often more likely to utilize the superordinate value as part of their solution rather than the anticipated reference class values. This resulted in a weakened effect of congruence, with relatively low accuracy even in congruent conditions, and a dominant response error of the superordinate value. Experiment 2 confirmed that the introduction of a new sample drew attention away from the provided reference class, increasing reliance on the overall sample size. This superordinate preference error, along with the benefit of repeating the PPV reference class within the question, demonstrated the importance of reference dependence based on the salience of information within the response prompt. Throughout, higher numerical skills were generally associated with higher accuracy, whether calculations were required or not. (shrink)

Julia Annas is one of the few modern writers on virtue that has attempted to recover the ancient idea that virtues are similar to skills. In doing so, she is arguing for a particular account of virtue, one in which the intellectual structure of virtue is analogous to the intellectual structure of practical skills. The main benefit of this skill model of virtue is that it can ground a plausible account of the moral epistemology of virtue. This benefit, though, is (...) only available to some accounts of virtue. Annas claims that Aristotle rejects this skill model of virtue, and so the model of virtues as a skill that Annas endorses for the modern virtue theory is Socratic. This paper argues that while Aristotle rejects the Socratic model of virtue as a skill, he does not reject the model of virtue as a skill altogether. Annas has mischaracterized Aristotle's position on the skill model, because she has not recognized that Aristotle endorses a different account of the structure of skill than the one put forth by Socrates. In addition, recent research on expertise provides an account of skills very much at odds with the description of skills offered by Annas, but similar to the account endorsed by Aristotle. Contrary to Annas, not only is the skill model of virtue compatible with a neo-Aristotelian account of virtue, but it also appears that basing a skill model of virtue on a Socratic account of virtue is likely to prove unsuccessful. (shrink)

Relational reasoning is a hallmark of human higher cognition and creativity, yet it is notoriously difficult to encourage in abstract tasks, even in adults. Generally, young children initially focus more on objects, but with age become more focused on relations. While prerequisite knowledge and cognitive resource maturation partially explains this pattern, here we propose a new facet important for children's relational reasoning development: a general orientation to relational information, or a relational mindset. We demonstrate that a relational mindset can be (...) elicited, even in 4‐year‐old children, yielding greater than expected spontaneous attention to relations. Children either generated or listened to an experimenter state the relationships between objects in a set of formal analogy problems, and then in a second task, selected object or relational matches according to their preference. Children tended to make object mappings, but those who generated relations on the first task selected relational matches more often on the second task, signaling that relational attention is malleable even in young children. (shrink)

The scientific knowledge needed to engage with policy issues like climate change, vaccination, and stem cell research often conflicts with our intuitive theories of the world. How resilient are our intuitive theories in the face of contradictory scientific knowledge? Here, we present evidence that intuitive theories in 10 domains of knowledge—astronomy, evolution, fractions, genetics, germs, matter, mechanics, physiology, thermodynamics, and waves—persist more than four decades beyond the acquisition of a mutually exclusive scientific theory. Participants were asked to verify two types (...) of scientific statements as quickly as possible: those that are consistent with intuition and those that involve the same conceptual relations but are inconsistent with intuition. Older adults were as accurate as younger adults at verifying both types of statements, but the lag in response times between intuition-consistent and intuition-inconsistent statements was significantly larger for older adults than for younger adults. This lag persisted even among professional scientists. Overall, these results suggest that the scientific literacy needed to engage with topics of global importance may be constrained by patterns of reasoning that emerge in childhood but persist long thereafter. (shrink)

The inductive category formation framework, an influential set of theories of learning in psychology and artificial intelligence, is deeply flawed. In this framework a set of necessary and sufficient features is taken to define a category. Such definitions are not functionally justified, are not used by people, and are not inducible by a learning system. Inductive theories depend on having access to all and only relevant features, which is not only impossible but begs a key question in learning. The crucial (...) roles of other cognitive processes (such as explanation and credit assignment) are ignored or oversimplified. Learning necessarily involves pragmatic considerations that can only be handled by complex cognitive processes.We provide an alternative framework for learning according to which category definitions must be based on category function. The learning system invokes other cognitive processes to accomplish difficult tasks, makes inferences, analyses and decides among potential features, and specifies how and when categories are to be generated and modified. We also examine the methodological underpinnings of the two approaches and compare their motivations. (shrink)

How impartial are managerial decisions? This question is particularly concerning when it comes to making green investment decisions in the face of stakeholder pressures. When managers respond to stakeholder pressures, their personal cognition, judgment, and past experiences play a role in determining their responses. The salience of particular stakeholder claims may be determined by deeply rooted individual preferences. This research investigates how a manager’s past experiences can influence green investments. Data are gathered from 247 managers about their past experience and (...) their employer’s performance data. These data are combined with managerial responses to a vignette-based experiment, which required managers to make green investments based on a decision scenario where they are exposed to different types and strength of stakeholder pressure. Results suggest that managers’ years of experience, their employers’ financial performance, and their employers’ market performance influence investment decisions even when making decisions under new and different set of circumstances. While the employers’ financial performance influences managers to invest more, the employers’ market performance only influences managers’ investment in the presence of either high consumer or high community pressure. Compared to less-experienced managers, experienced managers invest more in response to consumer pressure but less in response to community pressure. Practical and theoretical implications of these findings in green management are explored. (shrink)

A productive way to think about imagistic mental models of physical systems is as though they were sources of quasi‐empirical evidence. People depict or imagine events at those points in time when they would experiment with the world if possible. Moreover, just as they would do when observing the world, people induce patterns of behavior from the results depicted in their imaginations. These resulting patterns of behavior can then be cast into symbolic rules to simplify thinking about future problems and (...) to reveal higher order relationships. Using simple gear problems, three experiments explored the occasions of use for, and the inductive transitions between, depictive models and number‐based rules. The first two experiments used the convergent evidence of problem‐solving latencies, hand motions, referential language and error data to document the initial use of a model, the induction of rules from the modeling results, and the fallback to a model when a rule fails. The third experiment explored the intermediate representations that facilitate the induction of rules from depictive models. The strengths and weaknesses of depictive modeling and more analytic systems of reasoning are delineated to motivate the reasons for these transitions. (shrink)

Research on expert‐novice differences has mainly focused on how experts solve familiar problems. We know far less about the skills and knowledge used by experts when they are confronted with novel problems within their area of expertise. This article discusses a study in which verbal protocols were taken from subjects of various expertise designing an experiment in an area with which they were unfamiliar. The results showed that even when domain knowledge is lacking, experts solve a novel problem within their (...) area of expertise by dividing the problem into a number of subproblems that are solved in a specified order. The lack of domain knowledge is compensated for by using abstract knowledge structures and domain‐specific heuristic strategies. However, the quality of their solutions is considerably lower than the quality attained by experts who were familiar with the type of problem to be solved. The results suggest that when experts are confronted with novel problems as compared with familiar problems, their form of reasoning remains intact, but the content of their reasoning suffers due to lack of domain knowledge. (shrink)

This study explores the way that belief systems, interactions with social or experimental environments, and skills at the “control” level in decision‐making shape people's behavior as they solve problems. It is argued that problem‐solvers' beliefs (not necessarily consciously held) about what is useful in mathematics may determine the set of “cognitive resources” at their disposal as they do mathematics. Such beliefs may, for example, render inaccessible to them large bodies of information that are stored in long‐term memory and that are (...) easily retrieved in other circumstances. In other cases, individuals' reactions to an experimental setting (fear of failure, or the desire to “look mathematical” while being videotaped) may induce behavior that is almost pathological—and at the same time, so consistent that it can be modeled. In general, such “environmental” factors establish the context within which individuals access and utilize the information potentially at their disposal.Protocols illustrating these points are presented and discussed. A model based on an axiomatization of students' beliefs about plane geometry is outlined, and is shown to correspond closely to their problem‐solving performance. A framework is offered for analyzing problem‐solving performance at three qualitatively different levels: access to cognitive resources stored in LTM, executive or control decision‐making, and belief systems. (shrink)

Understanding how situational features of assessment tasks impact reasoning is important for many educational pursuits, notably the selection of curricular examples to illustrate phenomena, the design of formative and summative assessment items, and determination of whether instruction has fostered the development of abstract schemas divorced from particular instances. The goal of our study was to employ an experimental research design to quantify the degree to which situational features impact inferences about participants’ understanding of Mendelian genetics. Two participant samples from different (...) educational levels and cultural backgrounds were used to test for context effects. A multi-matrix test design was employed, and item packets differing in situational features were randomly distributed to participants in the two samples. Rasch analyses of participant scores from both samples produced good item fit, person reliability, and item reliability and indicated that the university sample displayed stronger performance on the items compared to the high school sample. We found, surprisingly, that in both samples, no significant differences in performance occurred among the animal, plant, and human item contexts, or between the fictitious and “real” item contexts. In the university sample, we were also able to test for differences in performance between genders, among ethnic groups, and by prior biology coursework. None of these factors had a meaningful impact upon performance or context effects. Thus some, but not all, types of genetics problem solving or item formats are impacted by situational features. (shrink)

Previous neural network models of concept learning were mainly implemented with supervised learning schemes. However, studies of human conceptual memory have shown that concepts may be learned without a teacher who provides the category name to associate with exemplars. A modular neural network architecture that realizes concept acquisition through two functionally distinct operations, categorizing and naming, is proposed as an alternative. An unsupervised algorithm realizes the categorizing module by constructing representations of categories compatible with prototype theory. The naming module associates (...) category names to the output of the categorizing module in a supervised mode. In such a modular architecture, the interface between the modules can be conceived of as an “information relay” that encodes, constrains, and propagates important information. Five experiments were conducted to analyze the relationships among internal conceptual codes and simple conceptual and lexical development. The first two experiments show a prototype effect and illustrate some basic characteristics of the system. The third experiment presents a bottom‐up model of the narrowing down of children's early lexical categories that honors mutual exclusivity. The fourth experiment introduces top‐down constraints on conceptual coding. The fifth experiment exhibits how hierarchical relationships between concepts are learned by the architecture, and also demonstrates how a spectrum of conceptual expertise may gradually emerge as a consequence of experiencing more with certain categories than with others. (shrink)

Previous neural network models of concept learning were mainly implemented with supervised learning schemes. However, studies of human conceptual memory have shown that concepts may be learned without a teacher who provides the category name to associate with exemplars. A modular neural network architecture that realizes concept acquisition through two functionally distinct operations, categorizing and naming, is proposed as an alternative. An unsupervised algorithm realizes the categorizing module by constructing representations of categories compatible with prototype theory. The naming module associates (...) category names to the output of the categorizing module in a supervised mode. In such a modular architecture, the interface between the modules can be conceived of as an “information relay” that encodes, constrains, and propagates important information. Five experiments were conducted to analyze the relationships among internal conceptual codes and simple conceptual and lexical development. The first two experiments show a prototype effect and illustrate some basic characteristics of the system. The third experiment presents a bottom‐up model of the narrowing down of children's early lexical categories that honors mutual exclusivity. The fourth experiment introduces top‐down constraints on conceptual coding. The fifth experiment exhibits how hierarchical relationships between concepts are learned by the architecture, and also demonstrates how a spectrum of conceptual expertise may gradually emerge as a consequence of experiencing more with certain categories than with others. (shrink)

What is ‘counterintuitive’? There is general agreement that it refers to a violation of previously held knowledge, but the precise definition seems to vary with every author and study. The aim of this paper is to deconstruct the notion of ‘counterintuitive’ and provide a more philosophically rigorous definition congruent with the history of psychology, recent experimental work in ‘minimally counterintuitive’ concepts, the science vs. religion debate, and the developmental and evolutionary background of human beings. We conclude that previous definitions of (...) counterintuitiveness have been flawed and did not resolve the conflict between a believer’s conception of the supernatural entity (an atypical “real kind”) and the non-believer’s conception (empty name/fictional). Furthermore, too much emphasis has been placed on the universality and (presumed) innateness of intuitive concepts (and hence the criteria for what is counterintuitive)—and far too little attention paid to learning and expertise. We argue that many putatively universal concepts are not innate, but mostly learned and defeasible—part of a religious believer’s repertoire of expert knowledge. Nonetheless, the results from empirical studies about the memorability of counterintuitive concepts have been convincing and it is difficult to improve on existing designs and methodologies. However, future studies in counterintuitive concepts need to embed their work in research about context effects, typicality, the psychology of learning and expertise (for example, the formation of expert templates and range defaults), with more attention to the sources of knowledge (direct and indirect knowledge) and a better idea of what ‘default’ knowledge really is. (shrink)

Research into expertise is relatively common in cognitive science concerning expertise existing across many domains. However, much less research has examined how experts within the same domain assess the performance of their peer experts. We report the results of a modified think-aloud study conducted with 18 pilots . Pairs of same-ranked pilots were asked to rate the performance of a captain flying in a critical pre-recorded simulator scenario. Findings reveal considerable variance within performance categories, differences in the process used as (...) evidence in support of a performance rating, different numbers and types of facts identified, and differences in how specific performance events affect choice of performance category and gravity of performance assessment. Such variance is consistent with low inter-rater reliability. Because raters exhibited good, albeit imprecise, reasons and facts, a fuzzy mathematical model of performance rating was developed. The model provides good agreement with observed variations. (shrink)

We investigated the understanding of causal systems categories—categories defined by common causal structure rather than by common domain content—among college students. We asked students who were either novices or experts in the physical sciences to sort descriptions of real-world phenomena that varied in their causal structure (e.g., negative feedback vs. causal chain) and in their content domain (e.g., economics vs. biology). Our hypothesis was that there would be a shift from domain-based sorting to causal sorting with increasing expertise in the (...) relevant domains. This prediction was borne out: The novice groups sorted primarily by domain and the expert group sorted by causal category. These results suggest that science training facilitates insight about causal structures. (shrink)

This article presents a cognitive map proposed to be associated with understanding of the “system concept,” one component of the physics principle of Newton's second low. A definition of the concept is followed by the results of a problem‐solving experiment designed to investigate whether or not good problem solvers possess cognitive structures similar to the one proposed. Think‐aloud protocols were collected as subjects solved a series of physics problems involving Newton's second law. Coding schemes were used to analyze these protocols (...) and to develop a quantitative index intended to reflect the extent to which subjects possessed certain components of the proposed structure. This index proved a highly significant predictor of performance on Newton's second law transfer problems contained in a written exam. In contrast, performance on a set of familiar problems in the same written exam was not a good predictor of performance on transfer problems. These results indicate that cognitive structures that connect the equation ΣF = ma and the concept of choosing appropriate systems are at least part of what constitutes understanding of the principle of Newton's second law. Implications for physics education and problem‐solving research are presented. (shrink)