The Einstellung effect occurs when the first idea that comes to mind, triggered by familiar features of a problem, prevents a better solution being found. It has been shown to affect both people facing novel problems and experts within their field of expertise. We show that it works by influencing mechanisms that determine what information is attended to. Having found one solution, expert chess players reported that they were looking for a better one. But their eye movements showed that they (...) continued to look at features of the problem related to the solution they had already thought of. The mechanism which allows the first schema activated by familiar aspects of a problem to control the subsequent direction of attention may contribute to a wide range of biases both in everyday and expert thought - from confirmation bias in hypothesis testing to the tendency of scientists to ignore results that do not fit their favoured theories. (shrink)

In a famous study of expert problem solving, de Groot (1946/1978) examined how chess players found the best move. He reported that there was little difference in the way that the best players (Grand Masters) and very good players (Candidate Masters) searched the board. Although this result has been regularly cited in studies of expertise, it is frequently misquoted. It is often claimed that de Groot found no difference in the way that experts and novices investigate a problem. Comparison of (...) expert and novice chess players on de Groot's problem shows that there are clear differences in their search patterns. We discuss the troublesome theoretical and practical consequences of incorrectly reporting de Groot's findings. (shrink)

A study is reported which focused on the problem-solving strategies employed by expert electronics engineers pursuing a real-world task: integrated-circuit design. Verbal protocol data were analysed so as to reveal aspects of the organisation and sequencing of ongoing design activity. These analyses indicated that the designers were implementing a highly systematic solution-development strategy which deviated only a small degree from a normatively optimal top-down and breadth-first method. Although some of the observed deviation could be described as opportunistic in nature, much (...) of it reflected the rapid depth-first exploration of tentative solution ideas. We argue that switches from a predominantly breadth-first mode of problem solving to depth-first or opportunistic modes may be an important aspect of the expert's strategic knowledge about how to conduct the design process effectively when faced with difficulties, uncertainties, and design impasses. (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)

There is a crucial debate concerning the nature of chess chunks: One current possibility states that chunks are built by encoding particular combinations of pieces-on-squares (POSs), and that chunks are formed mostly by “close” pieces (in a “Euclidean” sense). A complementary hypothesis is that chunks are encoded by abstract, semantic information. This article extends recent experiments and shows that chess players are able to perceive strong similarity between very different positions if the pieces retain the same abstract roles in both (...) of them. This casts doubt on the idea that POS information is the key information encoded in chess chunks, and this article proposes, instead, that the key encoding involves the abstract roles that pieces (and sets of pieces) play—a theoretical standpoint in line with the research program in semantics that places analogy at the core of cognition. (shrink)

The well-known game of chess has traditionally been modeled in artificial intelligence studies by search engines with advanced pruning techniques. The models were thus centered on an inference engine manipulating passive symbols in the form of tokens. It is beyond doubt, however, that human players do not carry out such processes. Instead, chess masters instead carry out perceptual processes, carefully categorizing the chunks perceived in a position and gradually building complex dynamic structures to represent the subtle pressures embedded in the (...) positions. In this paper we will consider two hypotheses concerning the underlying subcognitive processes and architecture. In the first hypothesis, a multiple-leveled chess representational structure is presented, which includes distance graphs (with varying levels of quality) between pieces, piece mobilities, and abstract roles. These representational schemes seem to account for numerous characteristics of human player’s psychology. The second hypothesis concerns the extension of the architecture proposed in the Copycat project as central for modeling the emergent intuitive perception of a chess position. We provide a synthesis on how the postulated architecture models chess intuition as an emergent mixture of simultaneous distance estimations, chunk perceptions, abstract role awareness, and intention activations. This is an alternative model to the traditional AI approaches, focusing on the philosophy of active symbols. (shrink)

The acquisition of expertise in formal problem solving has been assumed to involve either a shift from backwards to forwards inference, or a shift from unguided to guided forwards inference. In a longitudinal study, the acquisition of formal problem-solving expertise was investigated. Participants were tested as novices before undertaking controlled practice in the problem domain which involved transformation rule problems , and were finally tested as experts. The direction of inference in problem solutions was found to be inadequate to describe (...) the strategic differences between novices and experts. Therefore, a new solution coding system was applied, based on atomic components of problem solution. Analysis of novice and expert solutions revealed no systematic strategy in the novice stage solutions were confused and contained unproductive steps and backtracking. Several strategies were found in the expert solutions, but they did not agree with previously reported results. It was therefore proposed that the acquisition of expertise does not involve a change from one specific solution strategy to another, but rather the development of an efficient strategy, which can differ between participants. (shrink)

In a famous study of expert problem solving, de Groot (1946/1978) examined how chess players found the best move. He reported that there was little difference in the way that the best players (Grand Masters) and very good players (Candidate Masters) searched the board. Although this result has been regularly cited in studies of expertise, it is frequently misquoted. It is often claimed that de Groot found no difference in the way that experts and novices investigate a problem. Comparison of (...) expert and novice chess players on de Groot's problem shows that there are clear differences in their search patterns. We discuss the troublesome theoretical and practical consequences of incorrectly reporting de Groot's findings. (shrink)

Understanding how look-ahead search and pattern recognition interact is one of the important research questions in the study of expert problem solving. This paper examines the implications of the template theory Gobet & Simon, 1996a , a recent theory of expert memory, on the theory of problem solving in chess. Templates are chunks Chase & Simon, 1973 that have evolved into more complex data structures and that possess slots allowing values to be encoded rapidly. Templates may facilitate search in three (...) ways: a by allowing information to be stored into LTM rapidly; b by allowing a search in the template space in addition to a search in the move space; and c by compensating loss in the minds eye due to interference and decay. A computer model implementing the main ideas of the theory is presented, and simulations of its search behaviour are discussed. The template theory accounts for the slight skill difference in average depth of search found in chess players, as well as for other empirical data. (shrink)

This is Part I of a two-part reflection by Robert Ennis on his involvement in the critical thinking movement. Part I deals with how he got started in the movement and with the development of his influential definition of critical thinking and his conception of what critical thinking involves. Part II of the reflection will appear in the next issue of INQUIRY, Vol. 26, No. 2 (Summer 2011), and it will cover topics concerned with assessing critical thinking, teaching critical thinking, (...) and what the future may hold. (shrink)

This is the second part of a two-part reflection by Robert Ennis on his involvement in, and the progress of, the critical thinking movement. It provides a summary of Part I (Ennis 2011), including his definition/conception of critical thinking, the definition being “reasonable reflective thinking focused on deciding what to believe or do.” It then examines the assessment and the teaching of critical thinking (including incorporation in a curriculum), and makes suggestions regarding the future of critical thinking. He urges that (...) now is the time to make a major effort in promoting critical thinking. Later may be too late. He also suggests a number of things to do. An Appendix, which provides a detailed elaboration of the nature of critical thinking, is at the end of Part I, but summaries are provided here. (shrink)