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  1. Anomalous Evidence, Confidence Change, and Theory Change.Joshua A. Hemmerich, Kellie Van Voorhis & Jennifer Wiley - 2016 - Cognitive Science 40 (6):1534-1560.
    A novel experimental paradigm that measured theory change and confidence in participants' theories was used in three experiments to test the effects of anomalous evidence. Experiment 1 varied the amount of anomalous evidence to see if “dose size” made incremental changes in confidence toward theory change. Experiment 2 varied whether anomalous evidence was convergent or replicating. Experiment 3 varied whether participants were provided with an alternative theory that explained the anomalous evidence. All experiments showed that participants' confidence changes were commensurate (...)
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  • Précis of The creative mind: Myths and mechanisms.Margaret A. Boden - 1994 - Behavioral and Brain Sciences 17 (3):519-531.
    What is creativity? One new idea may be creative, whereas another is merely new: What's the difference? And how is creativity possible? These questions about human creativity can be answered, at least in outline, using computational concepts. There are two broad types of creativity, improbabilist and impossibilist. Improbabilist creativity involves novel combinations of familiar ideas. A deeper type involves METCS: the mapping, exploration, and transformation of conceptual spaces. It is impossibilist, in that ideas may be generated which – with respect (...)
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  • Integration and Reuse in Cognitive Skill Acquisition.Dario D. Salvucci - 2013 - Cognitive Science 37 (5):829-860.
    Previous accounts of cognitive skill acquisition have demonstrated how procedural knowledge can be obtained and transformed over time into skilled task performance. This article focuses on a complementary aspect of skill acquisition, namely the integration and reuse of previously known component skills. The article posits that, in addition to mechanisms that proceduralize knowledge into more efficient forms, skill acquisition requires tight integration of newly acquired knowledge and previously learned knowledge. Skill acquisition also benefits from reuse of existing knowledge across disparate (...)
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  • A model of knowledge activation and insight in problem solving.Matthew A. Cronin - 2004 - Complexity 9 (5):17-24.
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  • How Artificial Intelligence Can Help Us Understand Human Creativity.Fernand Gobet & Giovanni Sala - 2019 - Frontiers in Psychology 10.
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  • Lady Lovelace had it right: Computers originate nothing.Selmer Bringsjord - 1994 - Behavioral and Brain Sciences 17 (3):532-533.
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  • The birth of an idea.Liane M. Gabora - 1994 - Behavioral and Brain Sciences 17 (3):543-543.
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  • Can computers be creative, or even disappointed?Robert J. Sternberg - 1994 - Behavioral and Brain Sciences 17 (3):553-554.
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  • The Generality/Specificity of Expertise in Scientific Reasoning.Christian D. Schunn & John R. Anderson - 1999 - Cognitive Science 23 (3):337-370.
    Previous research on scientific reasoning has shown that it involves a diverse set of skills. Yet, little is known about generality or domain specificity of those skills, an important issue in theories of expertise and in attempts to automate scientific reasoning skills. We present a study designed to test what kinds of skills psychologists actually use in designing and interpreting experiments and contrast expertise within a particular research area with general expertise at designing and interpreting experiments. The results suggest that (...)
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  • Collaborative Discovery in a Scientific Domain.Takeshi Okada & Herbert A. Simon - 1997 - Cognitive Science 21 (2):109-146.
    This study compares Pairs of subjects with Single subjects in a task of discovering scientific laws with the aid of experiments. Subjects solved a molecular genetics task in a computer micro‐world (Dunbar, 1993). Pairs were more successful in discovery than Singles and participated more actively in explanatory activities (i.e., entertaining hypotheses and considering alternative ideas and justifications). Explanatory activities were effective for discovery only when the subjects also conducted crucial experiments. Explanatory activities were facilitated when paired subjects made requests of (...)
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  • Analogy programs and creativity.Bruce D. Burns - 1994 - Behavioral and Brain Sciences 17 (3):535-535.
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  • Creativity: Metarules and emergent systems.Jonathan Rowe - 1994 - Behavioral and Brain Sciences 17 (3):550-551.
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  • Creativity: A framework for research.Margaret A. Boden - 1994 - Behavioral and Brain Sciences 17 (3):558-570.
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  • Individual differences, developmental changes, and social context.Dean Keith Simonton - 1994 - Behavioral and Brain Sciences 17 (3):552-553.
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  • On doing the impossible.Robert L. Campbell - 1994 - Behavioral and Brain Sciences 17 (3):535-537.
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  • Computation: Part of the problem of creativity.Merlin Donald - 1994 - Behavioral and Brain Sciences 17 (3):537-538.
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  • How Do Creative Experts Practice New Skills? Exploratory Practice in Breakdancers.Daichi Shimizu & Takeshi Okada - 2018 - Cognitive Science 42 (7):2364-2396.
    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, (...)
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  • Art for art's sake.Alan Garnham - 1994 - Behavioral and Brain Sciences 17 (3):543-544.
    This piece is a commentary on a precis of Maggie Boden's book "The creative mind" published in Behavioral and Brain Sciences.
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  • Attention metaphors: How metaphors guide the cognitive psychology of attention.Diego Fernandez-Duque & Mark L. Johnson - 1999 - Cognitive Science 23 (1):83-116.
    The concept of attention is defined by multiple inconsistent metaphors that scientists use to identify relevant phenomena, frame hypotheses, construct experiments, and interpret data. (1) The Filter metaphor shapes debates about partial vs. complete filtering, early vs. late selection, and information filtering vs. enhancement. (2) The Spotlight metaphor raises the issue of space‐ vs. object‐based selection, and it guides research on the size, shape, and movement of the attentional focus. (3) The Spotlight‐in‐the‐Brain metaphor is frequently used to interpret imaging studies (...)
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  • Understanding students' practical epistemologies and their influence on learning through inquiry.William A. Sandoval - 2005 - Science Education 89 (4):634-656.
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  • Respecting the phenomenology of human creativity.Victor A. Shames & John F. Kihlstrom - 1994 - Behavioral and Brain Sciences 17 (3):551-552.
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  • The Impact of Goal Specificity on Strategy Use and the Acquisition of Problem Structure.Regina Vollmeyer, Bruce D. Burns & Keith J. Holyoak - 1996 - Cognitive Science 20 (1):75-100.
    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 (...)
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  • Goals, analogy, and the social constraints of scientific discovery.Kevin Dunbar & Lisa M. Baker - 1994 - Behavioral and Brain Sciences 17 (3):538-539.
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  • What about everyday creativity?Nick V. Flor - 1994 - Behavioral and Brain Sciences 17 (3):540-542.
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  • Creativity: Myths? Mechanisms.Michel Treisman - 1994 - Behavioral and Brain Sciences 17 (3):554-555.
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  • Creative thinking presupposes the capacity for thought.James H. Fetzer - 1994 - Behavioral and Brain Sciences 17 (3):539-540.
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  • Accommodating Surprise in Taxonomic Tasks: The Role of Expertise.Eugenio Alberdi, Derek H. Sleeman & Meg Korpi - 2000 - Cognitive Science 24 (1):53-91.
    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 (...)
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  • The empirical detection of creativity.Han L. J. van der Maas & Peter C. M. Molenaar - 1994 - Behavioral and Brain Sciences 17 (3):555-555.
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  • What is the difference between real creativity and mere novelty?Alan Bundy - 1994 - Behavioral and Brain Sciences 17 (3):533-534.
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  • Conscious thought processes and creativity.Maria F. Ippolito - 1994 - Behavioral and Brain Sciences 17 (3):546-547.
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  • The generative-rules definition of creativity.Joseph O'Rourke - 1994 - Behavioral and Brain Sciences 17 (3):547-547.
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  • Creativity is in the mind of the creator.Ashwin Ram, Eric Domeshek, Linda Wills, Nancy Nersessian & Janet Kolodner - 1994 - Behavioral and Brain Sciences 17 (3):549-549.
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  • Creativity, madness, and extra strong Al.K. W. M. Fulford - 1994 - Behavioral and Brain Sciences 17 (3):542-543.
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  • Breaking the law: Promoting domain-specificity in chemical education in the context of arguing about the periodic law. [REVIEW]Sibel Erduran - 2007 - Foundations of Chemistry 9 (3):247-263.
    In this paper, domain-specificity is presented as an understudied problem in chemical education. This argument is unpacked by drawing from two bodies of literature: learning of science and epistemology of science, both themes that have cognitive as well as philosophical undertones. The wider context is students’ engagement in scientific inquiry, an important goal for science education and one that has not been well executed in everyday classrooms. The focus on science learning illustrates the role of domain specificity in scientific reasoning. (...)
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  • Computational creativity: What place for literature?Jörgen Pind - 1994 - Behavioral and Brain Sciences 17 (3):547-548.
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  • Views from the Chalkface.Zhi Hong Wan & Siu Ling Wong - 2016 - Science & Education 25 (9-10):1089-1114.
    Although the goal of developing school students’ understanding of nature of science has long been advocated, there is still a lack of research that focuses on probing how science teachers, a kind of major stakeholder in NOS instruction, perceive the values of teaching NOS. Through semi-structured interviews, this study investigated the views of 15 Hong Kong in-service senior secondary science teachers about the values of teaching NOS. These values as perceived by the teachers fall into two types. The first type (...)
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  • (1 other version)Imagery and creativity.Klaus Rehkämper - 1994 - Behavioral and Brain Sciences 17 (3):550-550.
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  • Machine discoverers: Transforming the spaces they explore.Jan M. Zytkow - 1994 - Behavioral and Brain Sciences 17 (3):557-558.
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  • Epistemologically authentic inquiry in schools: A theoretical framework for evaluating inquiry tasks.Clark A. Chinn & Betina A. Malhotra - 2002 - Science Education 86 (2):175-218.
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  • The creative mind versus the creative computer.Robert W. Weisberg - 1994 - Behavioral and Brain Sciences 17 (3):555-557.
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  • The historical basis of scientific discovery.Gerd Grasshoff - 1994 - Behavioral and Brain Sciences 17 (3):545-546.
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  • Creativity theory: Detail and testability.K. J. Gilhooly - 1994 - Behavioral and Brain Sciences 17 (3):544-545.
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  • Creativity, combination, and cognition.Terry Dartnall - 1994 - Behavioral and Brain Sciences 17 (3):537-537.
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  • Can artificial intelligence explain age changes in literary creativity?Carolyn Adams-Price - 1994 - Behavioral and Brain Sciences 17 (3):532-532.
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