This paper reports a psychological study of human categorization that looked at the procedures used by expert scientists when dealing with puzzling items. Five professional botanists were asked to specify a category from a set of positive and negative instances. The target category in the study was defined by a feature that was unusual, hence situations of uncertainty and puzzlement were generated. Subjects were asked to think aloud while solving the tasks, and their verbal reports were analyzed. A number of (...) problem solving strategies were identified, and subsequently integrated in a model of knowledge‐guided inductive categorization. Our model proposes that expert knowledge influences the subjects' reasoning in more complex ways than suggested by earlier investigations of scientific reasoning. As in previous studies, domain knowledge influenced our subjects' hypothesis generation and testing; but, additionally, it played a central role when subjects revised their hypotheses. (shrink)

In multicausal abductive tasks a person must explain some findings by assembling a composite hypothesis that consists of one or more elementary hypotheses. If there are n elementary hypotheses, there can be up to 2n composite hypotheses. To constrain the search for hypotheses to explain a new observation, people sometimes use their current explanation—the previous evidence and their present composite hypothesis of that evidence; however, it is unclear when and how the current explanation is used. In addition, although a person's (...) current explanation can narrow the search for a hypothesis, it can also blind the problem solver to alternative, possibly better, explanations. This paper describes a model of multicausal abductive reasoning that makes two predictions regarding the use of the current explanation. The first prediction is that the current explanation is not used to explain new evidence if there is a simple (i.e., nondisjunctive, concrete) hypothesis to account for that evidence. The second prediction is that the current explanation is used when attempting to discriminate among several alternative hypotheses for new evidence. These hypotheses were tested in three experiments. The results are consistent with the second prediction: the current explanation is used when discriminating among alternative hypotheses. However, the first prediction—that the current explanation is not used when a simple hypothesis can account for new data—received only limited support. Participants used the current explanation to constrain their interpretation of new data in 46.5% of all trials. This suggests that context‐independent strategies compete with context‐dependent ones—an interpretation that is consistent with recent work on strategy selection during problem solving. (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)

Theories of skill acquisition have made radically different predictions about the role of general problem‐solving methods in acquiring rules that promote effective transfer to new problems. Under one view, methods that focus on reaching specific goals, such as means‐ends analysis, are assumed to provide the basis for efficient knowledge compilation (Anderson, 1987), whereas under an alternative view such methods are believed to disrupt rule induction (Sweller, 1988). We suggest that the role of general methods in learning varies with both the (...) specificity of the problem solver's goal and the systematicity of the strategies used for testing hypotheses about rules. In the absence of a specific goal people are more likely to use a rule‐induction learning strategy, whereas provision of a specific goal fosters use of difference reduction, which tends to be a non‐rule‐induction strategy. We performed two experiments to investigate the impact of goal specificity and systematicity of rule‐induction strategies in learning and transfer within a complex dynamic system. The results of Experiment 1 indicated that during free exploration of a problem space, greater learning occurred if participants adopted more systematic strategies for rule induction, and that participants come to favor such strategies. Experiment 2 revealed that participants who were provided with a specific goal performed well on the initial problem but were impaired on a transfer test using a similar problem with a different goal. Instruction on a systematic rule‐induction strategy facilitated solution for both the initial and transfer problems, but participants' use of this strategy declined if they had a specific goal. Our results support Sweller's (1988) proposal that general problemsolving methods applied to a specific goal foster acquisition of knowledge about an isolated solution path but do not provide an effective way of learning the overall structure of a problem space. We interpret these results in terms of dualspace theories of search through problem space. (shrink)

We propose another positive illusion that fits with McKay & Dennett's (M&D's) criteria for adaptive misbeliefs. This illusion is pervasive in adult reasoning but we focus on its prevalence in children's developing theories. It is a strongly held conviction arising from normal functioning of the doxastic system that confers adaptive advantage on the individual.

Despite the accumulation of substantial cognitive science research relevant to education, there remains confusion and controversy in the application of research to educational practice. In support of a more systematic approach, we describe the Knowledge-Learning-Instruction (KLI) framework. KLI promotes the emergence of instructional principles of high potential for generality, while explicitly identifying constraints of and opportunities for detailed analysis of the knowledge students may acquire in courses. Drawing on research across domains of science, math, and language learning, we illustrate the (...) analyses of knowledge, learning, and instructional events that the KLI framework affords. We present a set of three coordinated taxonomies of knowledge, learning, and instruction. For example, we identify three broad classes of learning events (LEs): (a) memory and fluency processes, (b) induction and refinement processes, and (c) understanding and sense-making processes, and we show how these can lead to different knowledge changes and constraints on optimal instructional choices. (shrink)

The present study discusses findings that replicate and extend the original work of Burns and Vollmeyer (2002), which showed that performance in problem solving tasks was more accurate when people were engaged in a non-specific goal than in a specific goal. The main innovation here was to examine the goal specificity effect under both observation-based and conventional action-based learning conditions. The findings show that goal specificity affects the accuracy of problem solving in the same way, both when the learning stage (...) of the task is observationbased and when it is action-based. Additionally, the findings show that, when instructions do not promote goal specificity, observation-based problem solving is as effective as action-based problem solving. (shrink)

We focus on Karmiloff-Smith's Representational redescription model, arguing that it poses some problems concerning the architecture of a redescribing system. To discuss the topic, we consider the implicit/explicit dichotomy and the relations between natur al language and the language of thought. We argue that the model regards how knowledge is employed rather than how it is represented in the system.

We use evidence from cognitive psychology and the history of science to examine the issue of the theory-ladenness of perceptual observation. This evidence shows that perception is theory-laden, but that it is only strongly theory-laden when the perceptual evidence is ambiguous or degraded, or when it requires a difficult perceptual judgment. We argue that debates about the theory-ladenness issue have focused too narrowly on the issue of perceptual experience, and that a full account of the scientific process requires an examination (...) of theory-ladenness in attention, perception, data interpretation, data production, memory, and scientific communication. We conclude that the evidence for theory-ladenness does not lead to a relativist account of scientific knowledge. (shrink)

Why does one need creativity? On a personal level, improvisation with available resources is needed for online coping with unforeseen environmental stimuli when existing knowledge and apparent action strategies do not work. On a cultural level, the exploitation of existing cultural means and norms for the deliberate production of novel and valuable artifacts is a basis for cultural and technological development and extension of human action possibilities across various domains. It is less clear, however, how creativity develops and how exactly (...) one arrives at generating new action possibilities and producing multiple alternative action strategies using familiar objects. In this theoretical paper, we first consider existing accounts of the creative process in the Alternative Uses Task and then present an alternative interpretation, drawing on sociocultural views and an embodied cognition approach. We explore similarities between the psychological processes underlying the generation of new uses in the Alternative Uses Task and children’s pretend play. We discuss possible cognitive mechanisms and speculate how the generation of new action possibilities for common objects in pretend play can be related to adults’ ability to generate new action strategies associated with object use. Implications for creativity development in humans and embodied artificial agents are discussed. (shrink)

In this interdisciplinary article, we investigate the relationship between creativity and the immune system; the creative features of the immune system and how the immune system and its role in regulating homeostasis might be related to creative cognition. We argue that within a multivariate approach of creativity, the immune system is a contributing factor. New directions for research are also discussed. When astronauts and cosmonauts venture into the new and extreme environment of outer space, their immune system needs to instantly (...) adapt and find new answers to survive biologically and psychologically. Many astronauts report interest in creative activities and therefore represent an interesting group to investigate creativity in relation with the immune system. Little is known regarding how the immune system interacts with and supports creative cognition and behavior, if an individual’s immune system, interacting with cognition, adapts more originally to a new environment compared to another’s; in other words, if there is creativity in the domain of the immune system, and the creative properties and functions of the immune system itself. (shrink)

Analogical reasoning by comparison is considered a special case of inductive reasoning, which is fundamental to the scientific method. By reasoning analogically, learners can abstract the underlying commonalities of several entities, thereby ignoring single objects’ superficial features. We tested whether different task environments designed to trigger analogical reasoning by comparison would support preschoolers’ induction of the concept of material kind to predict and explain objects’ floating or sinking as a central aspect of scientific reasoning. Specifically, in two experiments, we investigated (...) whether the number of presented objects (one versus two standards), consisting of a specific material and the labeling of objects with the respective material name, would benefit preschoolers’ material-based inferences. For each item set used in both experiments, we asked the children ( N = 59 in Experiment 1, N = 99 in Experiment 2) to predict an object’s floating or sinking by matching it to the standards and to verbally explain their selections. As expected, we found a significant effect for the number of standards in both experiments on the prediction task, suggesting that children successfully induced the relevance of material kind by comparison. However, labels did not increase the effect of the standards. In Experiment 2, we found that the children could transfer their conceptual knowledge on material kind but that transfer performance did not differ among the task environments. Our findings suggest that tasks inviting analogical reasoning by comparison with two standards are useful for promoting young children’s scientific reasoning. (shrink)

Prior evidence has shown that children’s understanding of balance proceeds through stages. Children go from a stage where they lack a consistent theory ( No Theory ), to becoming Center Theorists at around age 6 (believing that all objects balance in their geometric center), to Mass Theorists at around age 8, when they begin to consider the distribution of objects’ mass. In this study we adapted prior testing paradigms to examine 5-year-olds’ understanding of balance and compared children’s learning about balance (...) from evidence presented through primary sources (a guided activity) or secondary sources (picture books). Most of the research on young children’s understanding of balance has been conducted using a single object, weighted either proportionally (symmetrical object) or disproportionally (asymmetrical object). In this study, instead of using a single object, 5-year-olds ( N = 102) were shown 4 pairs of objects, two with the same weight and two with different weight. Children were told to place the objects on a beam where they thought they would balance. We found evidence for an intermediate level of understanding. Transition Theorists represent children who have two distinct theories, one for balancing same weight objects, and one for balancing different weight objects, but one of these theories is incorrect. Following the assessment of children’s understanding, we compared their learning about balance from evidence that was either presented through primary sources (a guided activity) or secondary sources (picture books). Children learn equally well from both sources of evidence. Findings are discussed in terms of theoretical and practical implications. (shrink)

Locked and unlocked strategies are at the center of this article, as ways of shedding new light on the cognitive aspects of deep learning machines. The character and the role of these cognitive strategies, which are occurring both in humans and in computational machines, is indeed strictly related to the generation of cognitive outputs, which range from weak to strong level of knowledge creativity. I maintain that these differences lead to important consequences when we analyze computational AI programs, such as (...) AlphaGo, which aim at performing various kinds of abductive hypothetical reasoning. In these cases, the programs are characterized by _locked_ abductive strategies: they deal with weak (even if sometimes amazing) kinds of hypothetical creative reasoning, because they are limited in what I call eco-cognitive openness, which instead qualifies human cognizers who are performing higher kinds of abductive creative reasoning, where cognitive strategies are instead _unlocked_. (shrink)

Constructing an intuitive theory from data confronts learners with a “chicken‐and‐egg” problem: The laws can only be expressed in terms of the theory's core concepts, but these concepts are only meaningful in terms of the role they play in the theory's laws; how can a learner discover appropriate concepts and laws simultaneously, knowing neither to begin with? We explore how children can solve this chicken‐and‐egg problem in the domain of magnetism, drawing on perspectives from computational modeling and behavioral experiments. We (...) present 4‐ and 5‐year‐olds with two different simplified magnet‐learning tasks. Children appropriately constrain their beliefs to two hypotheses following ambiguous but informative evidence. Following a critical intervention, they learn the correct theory. In the second study, children infer the correct number of categories given no information about the possible causal laws. Children's hypotheses in these tasks are explained as rational inferences within a Bayesian computational framework. (shrink)

How do expert performers practice as they develop creatively? This study investigated the processes involved in the practice of new skills by expert breakdancers. A great deal of evidence supports the theory of “deliberate practice” (Ericsson, Krampe, & Tesch‐Römer, 1993,Psychological Review, 100,363) in skill acquisition; however, expert creative performers may emphasize other forms of practice for skill development. Four case studies collected through fieldwork and laboratory observation were analyzed to evaluate expert dancers’ practice processes as they developed proficiency in new, (...) specific skills. We focused on three aspects of learning: the degree of skill acquisition, the content of skills included in practice, and dancers’ stated purposes for practicing. The results showed that dancers’ practice improved skills (as suggested by deliberate practice) and engaged the exploration of new, original skills, along with coordinating skills within performance. In their practice, these dance experts went beyond deliberative practice to highly exploratory processes for skill development. (shrink)

A model is proposed to explain how emotional and cognitive processes drive epistemic activities within individual scientists. In this account, emotion–cognition interactions produce cyclical phases of accommodative and assimilative epistemic activities, called thought experiments and empirical experiments, respectively. During thought experiments, scientists ruminate over troubling anomalies in order to generate the theoretical ingredients necessary for constructing new conjectures. During empirical experiments, scientists explore exciting conjectures in order to cover the empirical ground necessary to discover new anomalies. Critically, epistemic activities are (...) accompanied and sustained by positive and negative emotional moods. The main virtue of the model is its specification of a coupled feedback mechanism that explains the dynamics and the temporal dependencies between empirical and theoretical activities underlying scientific discovery. (shrink)

In 1983, Dr. J. Robin Warren and Dr. Barry Marshall reported finding a new kind of bacteria in the stomachs of people with gastritis. Warren and Marshall were soon led to the hypothesis that peptic ulcers are generally caused, not by excess acidity or stress, but by a bacterial infection. Initially, this hypothesis was viewed as preposterous, and it is still somewhat controversial. In 1994, however, a U. S. National Institutes of Health Consensus Development Panel concluded that infection appears to (...) play an important contributory role in the pathogenesis of peptic ulcers, and recommended that antibiotics be used in their treatment. Peptic ulcers are common, affecting up to 10% of the population, and evidence has mounted that many ulcers can be cured by eradicating the bacteria responsible for them. (shrink)

Human one‐to‐one tutoring has been shown to be a very effective form of instruction. Three contrasting hypotheses, a tutor‐centered one, a student‐centered one, and an interactive one could all potentially explain the effectiveness of tutoring. To test these hypotheses, analyses focused not only on the effectiveness of the tutors' moves, but also on the effectiveness of the students' construction on learning, as well as their interaction. The interaction hypothesis is further tested in the second study by manipulating the kind of (...) tutoring tactics tutors were permitted to use. In order to promote a more interactive style of dialogue, rather than a didactic style, tutors were suppressed from giving explanations and feedback. Instead, tutors were encouraged to prompt the students. Surprisingly, students learned just as effectively even when tutors were suppressed from giving explanations and feedback. Their learning in the interactive style of tutoring is attributed to construction from deeper and a greater amount of scaffolding episodes, as well as their greater effort to take control of their own learning by reading more. What they learned from reading was limited, however, by their reading abilities. (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)

Collecting information that one expects to be useful is a powerful way to facilitate learning. However, relatively little is known about how people decide which information is worth sampling over the course of learning. We describe several alternative models of how people might decide to collect a piece of information inspired by “active learning” research in machine learning. We additionally provide a theoretical analysis demonstrating the situations under which these models are empirically distinguishable, and we report a novel empirical study (...) that exploits these insights. Our model-based analysis of participants' information gathering decisions reveals that people prefer to select items which resolve uncertainty between two possibilities at a time rather than items that have high uncertainty across all relevant possibilities simultaneously. Rather than adhering to strictly normative or confirmatory conceptions of information search, people appear to prefer a “local” sampling strategy, which may reflect cognitive constraints on the process of information gathering. (shrink)