Thomas C. Ormerod

Does Incubation Enhance Problem Solving? A Meta-Analytic Review

A meta-analytic review of empirical studies that have investigated incubation effects on problem solving is reported. Although some researchers have reported increased solution rates after an incubation period (i.e., a period of time in which a problem is set aside prior to further attempts to solve), others have failed to find effects. The analysis examined the contributions of moderators such as problem type, presence of solution-relevant or misleading cues, and lengths of preparation and incubation periods to incubation effect sizes. The authors identified a positive incubation effect, with divergent thinking tasks benefiting more than linguistic and visual insight tasks from incubation. Longer preparation periods gave a greater incubation effect, whereas filling an incubation period with high cognitive demand tasks gave a smaller incubation effect. Surprisingly, low cognitive demand tasks yielded a stronger incubation effect than did rest during an incubation period when solving linguistic insight problems. The existence of multiple types of incubation effect provides evidence for differential invocation of knowledge-based vs. strategic solution processes across different classes of problem, and it suggests that the conditions under which incubation can be used as a practical technique for enhancing problem solving must be designed with care.

Information processing and insight : A process model of performance on the nine-dot and related problems

The 9-dot problem is widely regarded as a difficult insight problem. The authors present a detailed information-processing model to explain its difficulty, based on maximization and progress-monitoring heuristics with lookahead. In Experiments 1 and 2, the model predicted performance for the 9-dot and related problems. Experiment 3 supported an extension of the model that accounts for insightful moves. Experiments 4 and 5 provided a critical test of model predictions versus those of previous accounts. On the basis of these findings, the authors claim that insight problem solving can be modeled within a means-ends analysis framework. Maximization and progress-monitoring heuristics are the source of problem difficulty, but also create the conditions necessary for insightful moves to be sought. Furthermore, they promote the discovery and retention of promising states that meet the progress-monitoring criterion and attenuate the problem space.

Human performance on the traveling salesman problem

Two experiments on performance on the traveling salesman problem (TSP) are reported. The TSP consists of finding the shortest path through a set of points, returning to the origin. It appears to be an intransigent mathematical problem, and heuristics have been developed to find approximate solutions. The first experiment used 10-point, the second, 20-point problems. The experiments tested the hypothesis that complexity of TSPs is a function of number of nonboundary points, not total number of points. Both experiments supported the hypothesis. The experiments provided information on the quality of subjects’ solutions. Their solutions clustered close to the best known solutions, were an order of magnitude better than solutions produced by three well-known heuristics, and on average fell beyond the 99.9th percentile in the distribution of random solutions. The solution process appeared to be perceptually based.

Putting ethnography to work: the case for a cognitive ethnography of design

The methods of ethnography and cognitive psychology are frequently set in opposition to each other. Whilst such a view may be appropriate in defining pure, or prototypical, classes of each activity, the value and necessity of such a distinction is broken down when researchers are goal-directed to study complex work domains in order to foster technological change. In this paper, we outline a rapprochement of these methods, which we term cognitive ethnography. The value of qualifying ethnography in this way is to emphasize systematically the differences between ethnography as a radial category and the kinds of legitimate method used to study work practices which are often referred to as ethnographic, but which in practice differ in important ways from prototypical ethnographic studies. Features of cognitive ethnography such as observational specificity, verifiability and purposivenes challenge many of the tenets of a pure ethnographic method, yet they are essential for studies that are undertaken to inform technological change. We illustrate our arguments with reference to a project to develop a tool for supporting design re-use in innovative design environments.

Structured and opportunistic processing in design: a critical discussion

We present a critical discussion of research into the nature of design expertise, in particular evaluating claims that opportunism is a major influence on the behaviour of expert designers. We argue that the notion of opportunism has been under-constrained, and as a consequence the existence of opportunism in expert design has been exaggerated. Much of what has been described as opportunistic design behaviour appears to reflect a mix of breadth-first and depth-first modes of solution development. Whilst acknowledging that opportunities can arise in the design process (e.g. serendipitous solution discovery), such events might equally confirm structured behaviour as cause unstructured behaviour. We argue that the default mode for truly expert designers is typically a top-clown and breadth-first approach, since longer-term considerations of cost-effectiveness are more important for expert designers than short-term considerations of cognitive cost. However, there are situations (e.g. when faced with a highly unfamiliar design task) where it is cost-effective for experts to pursue a depth-first mode of solution development. The implications of our analysis for the development of methods and tools to support the design process are also discussed.

Problem-solving Strategies and Expertise in Engineering Design.

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 experts strategic knowledge about how to conduct the design process effectively when faced with difficulties, uncertainties, and design impasses.

What makes an insight problem? The roles of heuristics, goal conception and solution recoding in knowledge-lean problems.

Four experiments investigated transformation problems with insight characteristics. In Experiment 1, performance on a version of the 6-coin problem that had a concrete and visualizable solution followed a hill-climbing heuristic. Experiment 2 demonstrated that the difficulty of a version of the problem that potentially required insight for solution stems from the same hill-climbing heuristic, which creates an implicit conceptual block. Experiment 3 confirmed that the difficulty of the potential insight solution is conceptual, not procedural. Experiment 4 demonstrated the same principles of move selection on the 6-coin problem and the 10-coin (triangle) problem. It is argued that hill-climbing heuristics provide a common framework for understanding transformation and insight problem solving. Postsolution receding may account for part of the phenomenology of insight.

Naturalistic decision making and macrocognition

This book presents the latest work in the area of naturalistic decision making (NDM) and its extension into the area of macrocognition. It contains 18 chapters relating research centered on the study of expertise in naturalistic settings, written by international experts in NDM and cognitive systems engineering. The objective of the book is to present the reader with exciting new developments in this field of research, which is characterized by its application-oriented focus. The work addresses only real-world problems and issues. For instance, how do multi-national teams collaborate effectively? How can surgeons best be supported by technology? How do detectives make sense of complex criminal cases? In all instances the studies have been carried out on experts within their respective domains. The traditional field of NDM is extended in this work by focusing on macrocognitive functions other than decision making, namely sense-making, coordination and planning. This has broadened the scope of the field. The book also contains a theoretical discussion of the macro-micro distinction. Naturalistic Decision Making and Macrocognition will be relevant to graduate students, researchers and professionals (including professionals and researchers in business, industry and government) who are interested in decision making, expertise, training methods and system design. The material may be used in two ways: theoretically, to advance understanding of the field of naturalistic decision making; and practically, to gain insight into how experts in various domains solve particular problems, understand and deal with issues and collaborate with others.

A model of human performance on the traveling salesperson problem

A computational model is proposed of how humans solve the traveling salesperson problem (TSP). Tests of the model are reported, using human performance measures from a variety of 10-, 20-, 40-, and 60-node problems, a single 48-node problem, and a single 100-node problem. The model provided a range of solutions that approximated the range of human solutions and conformed closely to quantitative and qualitative characteristics of human performance. The minimum path lengths of subjects and model deviated by average absolute values of 0.0%, 0.9%, 2.4%, 1.4%, 3.5%, and 0.02% for the 10-, 20-, 40-, 48-, 60-, and 100-node problems, respectively. Because the model produces a range of solutions, rather than a single solution, it may find better solutions than some conventional heuristic algorithms for solving TSPs, and comparative results are reported that support this suggestion.

Applying ethnography in the analysis and support of expertise in engineering design

Whilst many contemporary studies of design have claimed to be using ethnographic methods, the techniques which have been employed often diverge from the characteristics of pure ethnography as used in traditional anthropological and sociological research. We argue that this is entirely appropriate for applied ethnography that is conducted in pursuit of explicit design goals. In this paper, we explore the relationship between pure and applied ethnography, and their use in cognitive and social research. We also discuss how the outcomes of applied ethnography can be applied to i) the design of a computer-based design support tool and ii) the development of controlled experimental studies that retain sufficient ecological validity to capture realistic design expertise. We additionally argue that objectivity in empirical studies of design can be obtained only by triangulating observations across methodologies that embrace both ethnographic and laboratory-based traditions.