What powered Einstein’s discoveries? Was it asking naïve questions, stubbornly? Was it a mischievous urge to break rules? Was it the destructive power of operational thinking? It was none of these. Rather, Einstein made his discoveries through lengthy, mundane investigations, pursued with tenacity and discipline. We have been led to think otherwise in part through Einstein’s brilliance at recounting in beguilingly simple terms a few brief moments of transcendent insight; and in part through our need to find a simple trick (...) underlying his achievements. These ideas are illustrated with the examples of Einstein’s 1905 discoveries of special relativity and the light quantum. (shrink)

_ Source: _Volume 94, Issue 3, pp 391 - 409 The author outlines a provisional phenomenology of problem solving. He begins by reviewing the history of problem-solving psychology, focusing on the Gestalt approach, which emphasizes the influence of prior knowledge and the occurrence of sudden insights. He then describes problem solving as a process unfolding in a field of consciousness against a background of unconscious knowledge, which encodes action patterns, schemata, and affordances. A global feeling of wrongness or tension is (...) resolved by a series of field transitions, which are guided by peripheral experiences of coherence or “rightness.” The author treats the distinction between reproductive thought and productive thought as a difference in field structure. With reproductive thoughts and actions we perform operations to solve a problem in a semi-automatic sequence. In productive thought, by contrast, a kind of parallel search occurs. This may explain the otherwise obscure phenomenology of struggling to break an impasse. (shrink)

Individual creativity is standardly treated as an ‘internalist’ process occurring solely in the head. An alternative, more interactionist view is presented here, where working with objects, media and other external things is seen as a fundamental component of creative thought. The value of chance interaction and chance cueing — practices widely used in the creative arts — is explored briefly in an account of the creative method of choreographer Wayne McGregor and then more narrowly in an experimental study that compared (...) performance on a Scrabble-like word discovery problem. Subjects were presented with seven letters and given two minutes to call out three-to-seven-letter English words. There were three conditions: The tiles were fixed in place, subjects were free to move the tiles manually or the tiles could be randomly shuffled. Results showed that random shuffling was best, with manual movement second. Three reasons are provided: Shuffling is faster and cheaper than mentally thinking of candidates; randomizing strings covers the search space better than a deterministic method based on past successes; and randomizing is equivalent to adding diversity to a team, which is known empirically to lead to more creative solutions. (shrink)

How do people make deductions? The orthodox view in psychology is that they use formal rules of inference like those of a “natural deduction” system.Deductionargues that their logical competence depends, not on formal rules, but on mental models. They construct models of the situation described by the premises, using their linguistic knowledge and their general knowledge. They try to formulate a conclusion based on these models that maintains semantic information, that expresses it parsimoniously, and that makes explicit something not directly (...) stated by any premise. They then test the validity of the conclusion by searching for alternative models that might refute the conclusion. The theory also resolves long-standing puzzles about reasoning, including how nonmonotonic reasoning occurs in daily life. The book reports experiments on all the main domains of deduction, including inferences based on prepositional connectives such as “if” and “or,” inferences based on relations such as “in the same place as,” inferences based on quantifiers such as “none,” “any,” and “only,” and metalogical inferences based on assertions about the true and the false. Where the two theories make opposite predictions, the results confirm the model theory and run counter to the formal rule theories. Without exception, all of the experiments corroborate the two main predictions of the model theory: inferences requiring only one model are easier than those requiring multiple models, and erroneous conclusions are usually the result of constructing only one of the possible models of the premises. (shrink)

The appropriate methodology for psychological research depends on whether one is studying mental algorithms or their implementation. Mental algorithms are abstract specifications of the steps taken by procedures that run in the mind. Implementational issues concern the speed and reliability of these procedures. The algorithmic level can be explored only by studying across-task variation. This contrasts with psychology's dominant methodology of looking for within-task generalities, which is appropriate only for studying implementational issues.The implementation-algorithm distinction is related to a number of (...) other “levels” considered in cognitive science. Its realization in Anderson's ACT theory of cognition is discussed. Research at the algorithmic level is more promising because it is hard to make further fundamental scientific progress at the implementational level with the methodologies available. Protocol data, which are appropriate only for algorithm-level theories, provide a richer source than data at the implementational level. Research at the algorithmic level will also yield more insight into fundamental properties of human knowledge because it is the level at which significant learning transitions are defined.The best way to study the algorithmic level is to look for differential learning outcomes in pedagogical experiments that manipulate instructional experience. This provides control and prediction in realistically complex learning situations. The intelligent tutoring paradigm provides a particularly fruitful way to implement such experiments.The implications of this analysis for the issue of modularity of mind, the status of language, research on human/computer interaction, and connectionist models are also examined. (shrink)

According to a simple form of consequentialism, we should base decisions on our judgments about their consequences for achieving our goals. Our goals give us reason to endorse consequentialism as a standard of decision making. Alternative standards invariably lead to consequences that are less good in this sense. Yet some people knowingly follow decision rules that violate consequentialism. For example, they prefer harmful omissions to less harmful acts, they favor the status quo over alternatives they would otherwise judge to be (...) belter, they provide third-party compensation on the basis of the cause of an injury rather than the benefit from the compensation, they ignore deterrent effects in decisions about punishment, and they resist coercive reforms they judge to be beneficial. I suggest that nonconsequentialist principles arise from overgeneralizing rules that are consistent with consequentialism in a limited set of cases. Commitment to such rules is detached from their original purposes. The existence of such nonconsequentialist decision biases has implications for philosophical and experimental methodology, the relation between psychology and public policy, and education. (shrink)

Novice designers produced a sequence of sketches while inventing a logo for a novel brand of soft drink. The sketches were scored for the presence of specific objects, their local features and global composition. Self‐assessment scores for each sketch and art critics' scores for the end products were collected. It was investigated whether the design evolves in an essentially random fashion or according to an overall heuristic. The results indicated a macrostructure in the evolution of the design, characterized by two (...) stages. For the majority of participants, the first stage is marked by the introduction and modification of novel objects and their local and global aspects; the second stage is characterized by changes in their global composition. The minority that showed the better designs has a different strategy, in which most global changes were made in the beginning. Although participants did not consciously apply these strategies, their self‐assessment scores reflect the stages of the process. (shrink)

The ArgumentIn this paper I present and argue for a model of conceptual development in science and apply it to the transition from classical to modern physics associated with Einstein. The model claims a continuous and rational transition between incompatible subsequent conceptual systems in mathematical science and explains its mechanism. The model was developed in a study of the transition from preclassical to classical mechanics. I argue for a strong structural analogy between the transition from preclassical to classical mechanics on (...) the one hand and from classical to modern physics on the other. The first transition is briefly sketched here by reference to Galileo and his disciples; in the second transition Planck and Lorentz on the one hand and Einstein on the other play the respective roles.A detailed and documented reconstruction of the transition from preclassical to classical mechanics on the basis of this model has already been published and is only briefly referred to in the paper. The transition from classical to modern physics is portrayed here much more extensively—though of course merely in broad brush strokes. Einstein–s role in this transition is reconstructed in the light of a conceptualization of his scientific knowledge as an active structure of thought, shaped by his intellectual experience. In this way, the development of his individual thinking is shown to be part of the overall process of conceptual transformation from classical to modern physics. The reconstruction sketched in this paper is to be considered as a proposal to be substantiated, reformed, and improved by future detailed studies. (shrink)

The object of this paper is to show why recent research in the psychology of deductive and probabilistic reasoning does not have.

In this dissertation, I provide an interpretation and defense of Merleau-Ponty's thesis of the primacy of perception, namely, the thesis that all knowledge is founded in perceptual experience. I take as an interpretative and argumentative key Merleau-Ponty's phenomenological conception of motivation. Whereas epistemology has traditionally accepted a dichotomy between reason and natural causality, I show that this dichotomy is not exhaustive of the forms of epistemic grounding. There is a third type of grounding, the one characteristic of the grounding relations (...) found in perception: motivation. I argue that introducing motivation as a form of epistemic grounding allows us to see how Merleau-Ponty's thesis of the primacy of perception avoids both rationalism and empiricism. Whereas empiricism has argued that all the content of our knowledge is grounded in causal interactions between the world and our senses, and rationalism has held that experience does not suffice as a reason for knowledge, thinking of the relation between experience and knowledge in terms of motivation accommodates the best insights of rationalism and empiricism. Motivation allows us to see how knowledge can be grounded in experience without the content of knowledge being reducible to that of experience. (shrink)

The ArgumentScientific tools—measurement and calculation instruments, techniques of inference—straddle the line between the context of discovery and the context of justification. In discovery, new scientific tools suggest new theoretical metaphors and concepts; and in justification, these tool-derived theoretical metaphors and concepts are morelikely to be accepted by the scientific community if the tools are already entrenched in scientific practice.Techniques of statistical inference and hypothesis testing entered American psychology first as tools in the 1940s and 1950s and then as cognitive theories (...) in the 1960s and 1970s. Not only did psychologists resists statistical metaphors of mind prior to the institutionalization of inference techniques in their own practice; the cognitive theories they ultimately developed about “the mind as intuitive statistician” still bear the telltale marks of the practical laboratory context in which the tool was used. (shrink)

Many scholars note that the Analects, and Confucian philosophy more generally, hold a conception of knowing that more closely approximates ‘knowing-how’ than ‘knowing-that’. However, I argue that this description is not sufficiently sensitive to the concerns of the early Confucians and their focus on self-cultivation. I propose that a particular conception of knowing—knowing to act in the moment—is better suited to capturing the Analects’ emphasis on exemplary lives in actual contexts. These investigations might also contribute to discussions on know-how in (...) epistemology in western philosophy. (shrink)

If I lose my key in Canada, for instance, and I search for it in the United Kingdom, how long will I take to find it? This paper argues that problems in education are caused by non-professional teachers who are employed when trained teachers move in search of promotion friendly activities or financially rewarding duties. This shift of focus means that policy makers in education act without adequate professional guidance. The problems in education, therefore, result from demands made on mainstream (...) education based on misconceptions about what education can offer. It is argued that the implementation of e-learning in education faces the risk of developing on the basis of unproven theories. This scenario increasingly sees the replacement of formal education activities in institutions of learning with non-formal and informal education practices. Given that the contents and influences of non-formal and informal education are not under the control of the teacher, the experiences that learners bring to education settings are increasingly difficult to manage. The paper proposes that by integrating e-learning in teacher education and rewarding 'good teaching', there is a potential for a successful e-learning revolution in education. (shrink)