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 (...) to the particular conceptual space concerned – could not have been generated before. The more clearly conceptual spaces can be defined, the better we can identify creative ideas. Defining conceptual spaces is done by musicologists, literary critics, and historians of art and science. Humanist studies, rich in intuitive subtleties, can be complemented by the comparative rigour of a computational approach. Computational modelling can help to define a space, and to show how it may be mapped, explored, and transformed. Impossibilist creativity can be thought of in “classical” Al terms, whereas connectionism illuminates improbabilist creativity. Most Al models of creativity can only explore spaces, not transform them, because they have no self-reflexive maps enabling them to change their own rules. A few, however, can do so. A scientific understanding of creativity does not destroy our wonder at it, nor does it make creative ideas predictable. Demystification does not imply dehumanization. (shrink)

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)

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 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 (...) with the amount of anomalous evidence presented, and that larger decreases in confidence predicted theory changes. Convergent evidence and the presentation of an alternative theory led to larger confidence change. Convergent evidence also caused more theory changes. Even when people do not change theories, factors pertinent to the evidence and alternative theories decrease their confidence in their current theory and move them incrementally closer to theory change. (shrink)

This piece is a commentary on a precis of Maggie Boden's book "The creative mind" published in Behavioral and Brain Sciences.

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 (...) each other for explanation and focused on them. The study extends from individual to collaborative discovery activities the importance to the discovery process of setting goals to find hypotheses and evidence (Dunbar, 1993) and to construct explanations of phenomena and processes encountered in examples (Chi, Bassok, Lewis, & Glaser, 1989). (shrink)

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 (...) of attention. (4) The debate between supramodal and pre‐motor theories of attention replays the dichotomy between the Spotlight and the Vision metaphors of attention. Our analysis reveals the central role of metaphor in scientific theory and research on attention, exposes hidden assumptions behind various research strategies, and shows the need for flexibility in the use of current metaphors. (shrink)

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. (...) The discussion on epistemology of science presents ideas from the emerging field of philosophy of chemistry to highlight the much neglected area of epistemology in chemical education. Domain-specificity is exemplified in the context of chemical laws, in particular the Periodic Law. The applications of the discussion for chemical education are explored in relation to argumentation, itself an epistemologically grounded discourse pattern in science. The overall implications include the need for reconceptualization of the nature of teaching and learning in chemistry to include more particular epistemological aspects of chemistry. (shrink)

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 (...) is related to students’ learning of science in the classroom and involves: facilitating the study of subject knowledge, increasing the interest in learning science, supporting the conduct of scientific inquiry, meeting the needs of public examinations, and fulfilling the requirement of learning science. The second type goes beyond learning science and includes developing thinking skills, cultivating scientific ethics in students, and supporting the participation in public decisions on socioscientific issues. Although rich relationships were perceived by these teachers between NOS instruction and students’ learning of science, few values were stated from broad social and cultural perspectives. Suggestions are made about developing teachers’ views of the values of teaching NOS so as to influence their intention of teaching it. (shrink)

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 (...) psychologists use many domain‐general skills in their experimentation and that bright and motivated Carnegie Mellon undergraduates are missing many of these skills. We believe that these results have important implications for psychological and artificial intelligence models of expertise, as well as educational implications in the domain of science instruction. (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)

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 (...) task domains, relying on indexicals to reference and share necessary information across knowledge components. To demonstrate these ideas, the article proposes a computational model of skill acquisition from instructions focused on integration and reuse, and applies this model to account for behavior across seven task domains. (shrink)