Computer-simulated scenarios have been part of psychological research on problem solving for more than 40 years. The shift in emphasis from simple toy problems to complex, more real-life oriented problems has been accompanied by discussions about the best ways to assess the process of solving complex problems. Psychometric issues such as reliable assessments and addressing correlations with other instruments have been in the foreground of these discussions and have left the content validity of complex (...) problem solving in the background. In this paper, we return the focus to content issues and address the important features that define complex problems. (shrink)

Complex problem solving (CPS) emerged in the last 30 years in Europe as a new part of the psychology of thinking and problem solving. This paper introduces into the field and provides a personal view. Also, related concepts like macrocognition or operative intelligence will be explained in this context. Two examples for the assessment of CPS, Tailorshop and MicroDYN, are presented to illustrate the concept by means of their measurement devices. Also, the relation of (...) class='Hi'>complex cognition and emotion in the CPS context is discussed. The question if CPS requires complex cognition is answered with a tentative “yes.”. (shrink)

Complex problem solving (CPS) and related topics such as dynamic decision-making (DDM) and complex dynamic control (CDC) represent multifaceted psychological phenomena. In a broad sense, CPS encompasses learning, decision-making, and acting in complex and dynamic situations. Moreover, solutions to problems that people face in such situations are often generated in teams or groups. In turn, this adds another layer of complexity to the situation itself because of the emerging issues that arise from the social dynamics (...) of group interactions. This framing of CPS means that it is not a single construct that can be measured by using a particular type of CPS task (e.g. minimal complex system tests), which is a view taken by the psychometric community. The proposed approach taken here is that because CPS is multifaceted, multiple approaches need to be taken to fully capture and understand what it is and how the different cognitive processes associated with it complement each other. (shrink)

In this paper we propose the multiple complex systems approach for assessing domain-general complex problem-solving skills and its processes knowledge acquisition and knowledge application. After defining the construct and the formal frameworks for describing complex problems, we emphasise some of the measurement issues inherent in assessing CPS skills with single tasks. With examples of the MicroDYN test and the MicroFIN test, we show how to adequately score problem-solving skills by using multiple tasks. We (...) discuss implications for problem-solving research and the assessment of CPS skills in general. (shrink)

This book explains the importance to acquire complex problem-solving in today’s job environment. The book describes how to use five problem-centered methods to design training for real-world complex problem-solving skills. The book briefly describes the five methods in the context of the complex problem-solving skills - Problem-based learning (PBL), Project-based learning, Scenario-based learning (SBL), Case-based learning method (CBL), and Simulation-based learning. The book also specifies six research-based guidelines, and how (...) training experts can design a training curriculum that ensures acquiring and accelerating complex problem-solving skills in any complex domain. (shrink)

Research in the fields of complex problem solving (CPS) and dynamic decision making using microworlds has been mainly conducted in Western industrialized countries. This study analyzes the CPS process by investigating thinking‐aloud protocols in five countries. Participants were 511 students from Brazil, Germany, India, the Philippines, and the United States who worked on two microworlds. On the basis of cultural‐psychological theories, specific cross‐national differences in CPS strategies were hypothesized. Following theories of situatedness of cognition, hypotheses about the (...) specific frequency of problem‐solving strategies in the two microworlds were developed. Results of the verbal protocols showed (a) modification of the theoretical CPS model, (b) task dependence of CPS strategies, and (c) cross‐national differences in CPS strategies. Participants’ CPS processes were particularly influenced by country‐specific problem‐solving strategies. (shrink)

Complex problem solving can be interpreted as the number of psychological mechanisms that allow us to reach our targets in difficult situations, that can be classified as complex, dynamic, non-transparent, interconnected, and multilayered, and also polytelic. The previous results demonstrated associations between the personality dimensions neuroticism, conscientiousness, and extraversion and problem-solving performance. However, there are no studies dealing with personality disorders in connection with CPS skills. Therefore, the current study examines a clinical sample consisting (...) of people with personality and/or depressive disorders. As we have data for all the potential personality disorders and also data from each patient regarding to potential depression, we meet the whole range from healthy to impaired for each personality disorder and for depression. We make use of a unique operationalization: CPS was surveyed in a simulation game, making use of the microworld approach. This study was designed to investigate the hypothesis that personality traits are related to CPS performance. Results show that schizotypal, histrionic, dependent, and depressive persons are less likely to successfully solve problems, while persons having the additional behavioral characteristics of resilience, action orientation, and motivation for creation are more likely to successfully solve complex problems. (shrink)

In this paper, we bring together research on complex problem solving with that on motivational psychology about goal setting. Complex problems require motivational effort because of their inherent difficulties. Goal Setting Theory has shown with simple tasks that high, specific performance goals lead to better performance outcome than do-your-best goals. However, in complex tasks, learning goals have proven more effective than performance goals. Based on the Zurich Resource Model, so-called motto-goals should activate a person’s resources (...) through positive affect. It was found that motto-goals are effective with unpleasant duties. Therefore, we tested the hypothesis that motto-goals outperform learning and performance goals in the case of complex problems. A total of N = 123 subject participated in the experiment. In dependence of their goal condition, subjects developed a personal motto, learning, or performance goal. This goal was adapted for the computer-simulated complex scenario Tailorshop, where subjects worked as managers in a small fictional company. Other than expected, there was no main effect of goal condition for the management performance. An unexpected gender effect revealed better performance for men than women, pointing to a potential stereotype threat. As hypothesized, motto goals led to higher positive and lower negative affect than the other two goal types. Even though positive affect decreased and negative affect increased in all three groups during Tailorshop completion, participants with motto goals reported the lowest rates of negative affect. Exploratory analyses investigated the role of affect in complex problem solving via mediational analyses and the influence of goal type on perceived goal attainment. (shrink)

In the last 20 years, a stream of research emerged under the label of „complex problem solving“ (CPS). This research was intended to describe the way people deal with complex, dynamic, and intransparent situations. Complex computer-simulated scenarios were as stimulus material in psychological experiments. This line of research lead to subtle insights into the way how people deal with complexity and uncertainty. Besides these knowledge-rich, realistic, intransparent, complex, dynamic scenarios with many variables, a second (...) line of research used more simple, knowledge-lean scenarios with a low number of variables („minimal complex systems“, MCS) that have been proposed recently in problem-solving research for the purpose of educational assessment. In both cases, the idea behind the use of microworlds is to increase validity of problem solving tasks by presenting interactive environments that can be explored and controlled by participants while pursuing certain action goals. The main argument presented here is: both types of systems - CPS and MCS – can only be dealt with successfully if causal dependencies between input and output variables are identified and used for system control. System knowledge is necessary for control and intervention. But CPS and MCS differ in their way of how causal dependencies are identified and how the mental model is constructed; therefore, they cannot be compared directly to each other with respect to the cognitive processes that are necessary for solving the tasks. Knowledge-poor MCS tasks address only a small fraction of the cognitive processes and structures needed for knowledge-rich CPS situations. (shrink)

The Role of Motivation in Complex Problem SolvingPrevious research on Complex Problem Solving (CPS) has primarily focused on cognitive factors as outlined below. The current paper discusses the role of motivation during CPS and argues that motivation, emotion, and cognition interact and cannot be studied in an isolated manner. Motivation is the process that determines the energization and direction of behavior (Heckhausen, 1991).Three motivation theories and their relation to CPS are examined: McClelland’s achievement motivation, Maslow’s (...) hierarchy of needs, and Dörner’s needs as outlined in PSI-theory. We chose these three theories for several reasons. First, space forces us to be selective. Second, the three theories are among the most prominent motivational theories. Finally, they are need theories postulating several motivations and not just one. A thinking-aloud protocol is provided to illustrate the role of motivational and cognitive dynamics in CPS. Problems are part of all the domains of human life. The field of CPS investigates problems that are complex, dynamic, and non-transparent (Dörner, 1996). Complex problems consist of many interactively interrelated variables. Dynamic ones change and develop further over time, regardless of whether the involved people take action. And non-transparent problems have many aspects of the problem situation that are unclear or unknown to the involved people. CPS researchers focus exactly on such kinds of problems. Under a narro... (shrink)

The assumption that positive affect leads to a better performance in simple cognitive tasks has become well established. We address the question whether positive and negative emotions differentially influence performance in complex problem-solving in the same way. Emotions were induced by positive or negative feedback in 74 participants who had to manage a computer-simulated complex problem-solving scenario. Results show that overall scenario performance is not affected, but positive and negative emotions elicit distinguishable problem- (...) class='Hi'>solving strategies: Participants with negative emotions are more focused on the seeking and use of information. We discuss methodological requirements for investigating emotion influences in complex and dynamic cognitive tasks. (shrink)

The assumption that positive affect leads to a better performance in simple cognitive tasks has become well established. We address the question whether positive and negative emotions differentially influence performance in complex problem-solving in the same way. Emotions were induced by positive or negative feedback in 74 participants who had to manage a computer-simulated complex problem-solving scenario. Results show that overall scenario performance is not affected, but positive and negative emotions elicit distinguishable problem- (...) class='Hi'>solving strategies: Participants with negative emotions are more focused on the seeking and use of information. We discuss methodological requirements for investigating emotion influences in complex and dynamic cognitive tasks. (shrink)

Multiple goals balancing is an important but not yet fully validated dimension of complex problem solving (CPS). The present study used process data to explore how solvers clarify goals, set priorities, and balance conflicting goals. We extracted behavioral indicators of goal pursuit from the log data of 3,201 students on the third subtask of the “Ticket” task in the PISA 2012 CPS test. Cluster analysis was used to identify 10 groups that varied in goal pursuit behavior. Logistics (...) and least-squares regression analysis were used to explore how goal pursuit affected task scores and CPS proficiency. The results showed that competent solvers clarified goals and weighed priorities more effectively. They also made trade-offs between conflicting goals. The importance of theoretically-driven log data analysis and coping strategies in the face of multiple goals conflict scenarios was discussed. (shrink)

The assumption that positive affect leads to a better performance in simple cognitive tasks has become well established. We address the question whether positive and negative emotions differentially influence performance in complex problem-solving in the same way. Emotions were induced by positive or negative feedback in 74 participants who had to manage a computer-simulated complex problem-solving scenario. Results show that overall scenario performance is not affected, but positive and negative emotions elicit distinguishable problem- (...) class='Hi'>solving strategies: Participants with negative emotions are more focused on the seeking and use of information. We discuss methodological requirements for investigating emotion influences in complex and dynamic cognitive tasks. (shrink)

This paper reflects on Dietrich Dörner's observation that participants in complex dynamic control tasks exhibit a "tendency to economize", that is, they tend to minimize cognitive effort. I interpret this observation in terms of a dual processing approach and explore if the reluctance to adopt Type 2 processing could be rooted in biological energy saving. There is evidence that the energy available for the cortex at any point in time is quite limited. Therefore, effortful thinking comes at the cost (...) of neglecting other cortical functions. The proposed dual processing approach to complex problem solving is explored in an experiment where we varied cognitive load by means of a secondary task in order to make Type 1 or Type 2 processing more likely. Results show that cognitive load had no effect on target achievement. Even in the single task condition, many participants prefer Type 1 processing, confirming Dörner's observation. (shrink)

Worst case complexity analyses of algorithms are sometimes held to be less informative about the real difficulty of computation than are expected complexity analyses. We show that the two most common representations of problem solving in cognitive science each admit aigorithms that have constant expected complexity, and for one of these representations we obtain constant expected complexity bounds under a variety of probability measures.

Following Marr’s famous three-level distinction between explanations in cognitive science, it is often accepted that focus on modeling cognitive tasks should be on the computational level rather than the algorithmic level. When it comes to mathematical problem solving, this approach suggests that the complexity of the task of solving a problem can be characterized by the computational complexity of that problem. In this paper, I argue that human cognizers use heuristic and didactic tools and thus (...) engage in cognitive processes that make their problem solving algorithms computationally suboptimal, in contrast with the optimal algorithms studied in the computational approach. Therefore, in order to accurately model the human cognitive tasks involved in mathematical problem solving, we need to expand our methodology to also include aspects relevant to the algorithmic level. This allows us to study algorithms that are cognitively optimal for human problem solvers. Since problem solving methods are not universal, I propose that they should be studied in the framework of enculturation, which can explain the expected cultural variance in the humanly optimal algorithms. While mathematical problem solving is used as the case study, the considerations in this paper concern modeling of cognitive tasks in general. (shrink)

Integrative systems biology is an emerging field that attempts to integrate computation, applied mathematics, engineering concepts and methods, and biological experimentation in order to model large-scale complex biochemical networks. The field is thus an important contemporary instance of an interdisciplinary approach to solving complex problems. Interdisciplinary science is a recent topic in the philosophy of science. Determining what is philosophically important and distinct about interdisciplinary practices requires detailed accounts of problem-solving practices that attempt to understand (...) how specific practices address the challenges and constraints of interdisciplinary research in different contexts. In this paper we draw from our 5-year empirical ethnographic study of two systems biology labs and their collaborations with experimental biologists to analyze a significant problem-solving approach in ISB, which we call adaptive problem solving. ISB lacks much of the methodological and theoretical resources usually found in disciplines in the natural sciences, such as methodological frameworks that prescribe reliable model-building processes. Researchers in our labs compensate for the lack of these and for the complexity of their problems by using a range of heuristics and experimenting with multiple methods and concepts from the background fields available to them. Using these resources researchers search out good techniques and practices for transforming intractable problems into potentially solvable ones. The relative freedom lab directors grant their researchers to explore methodological options and find good practices that suit their problems is not only a response to the complex interdisciplinary nature of the specific problem, but also provides the field itself with an opportunity to discover more general methodological approaches and develop theories of biological systems. Such developments in turn can help to establish the field as an identifiably distinct and successful approach to understanding biological systems. (shrink)

Multiple theories of problem-solving hypothesize that there are distinct qualitative phases exhibited during effective problem-solving. However, limited research has attempted to identify when transitions between phases occur. We integrate theory on collaborative problem-solving with dynamical systems theory suggesting that when a system is undergoing a phase transition it should exhibit a peak in entropy and that entropy levels should also relate to team performance. Communications from 40 teams that collaborated on a complex (...) class='Hi'>problem were coded for occurrence of problem-solving processes. We applied a sliding window entropy technique to each team's communications and specified criteria for identifying data points that qualify as peaks and determining which peaks were robust. We used multilevel modeling, and provide a qualitative example, to evaluate whether phases exhibit distinct distributions of communication processes. We also tested whether there was a relationship between entropy values at transition points and CPS performance. We found that a proportion of entropy peaks was robust and that the relative occurrence of communication codes varied significantly across phases. Peaks in entropy thus corresponded to qualitative shifts in teams’ CPS communications, providing empirical evidence that teams exhibit phase transitions during CPS. Also, lower average levels of entropy at the phase transition points predicted better CPS performance. We specify future directions to improve understanding of phase transitions during CPS, and collaborative cognition, more broadly. (shrink)

The aim of this paper is to describe the way in which argumentative patterns come into being in plenary debate over legislative issues in the European Parliament. What kind of argumentative patterns are to be expected within this macro context? It is shown that the argumentative patterns that come into being in legislative debate in the European Parliament depend for the most part on the problem-solving argumentation that is put forward in the opening speech by the rapporteur of (...) the parliamentary committee report. This argumentation can be pragmatic problem-solving argumentation or complex problem-solving argumentation. The most important prototypical argumentative patterns are investigated in the argumentation put forward by the Members of parliament. This investigation is based on an inventory of the arguments that can in principle be used to support or attack the initial problem-solving argumentation put forward by the rapporteur. (shrink)

A problem is a situation in which an agent seeks to attain a given goal without knowing how to achieve it. Human problem solving is typically studied as a search in a problem space composed of states (information about the environment) and operators (to move between states). A problem such as playing a game of chess has possible states, and a traveling salesperson problem with as little as 82 cities already has more than different (...) tours (similar to chess). Biological neurons are slower than the digital switches in computers. An exhaustive search of the problem space exceeds the capacity of current computers for most interesting problems, and it is fairly clear that humans cannot in their lifetime exhaustively search even small fractions of these problem spaces. Yet, humans play chess and solve logistical problems of similar complexity on a daily basis. Even for simple problems humans do not typically engage in exploring even a small fraction of the problem space. This begs the question: How do humans solve problems on a daily basis in a fast and efficient way? Recent work suggests that humans build a problem representation and solve the represented problem—not the problem that is out there. The problem representation that is built and the process used to solve it are constrained by limits of cognitive capacity and a cost–benefit analysis discounting effort and reward. In this article, we argue that better understanding the way humans represent and solve problems using heuristics can help inform how simpler algorithms and representations can be used in artificial intelligence to lower computational complexity, reduce computation time, and facilitate real-time computation in complex problem solving. (shrink)

Over a 20-year period, the United States has developed a consensus of legal opinion concerning living wills and other advance directives. At the heart of this consensus are two interconnected principles. First, the state should minimally interfere with the wishes of patients and surrogates and the decisions of physicians about foregoing life-sustaining treatments. Second, state interference is permissible for the sake of protecting a compelling state interest. The overwhelming majority of states with advance directive laws have attained this balance of (...) minimal interference and compelling state interest in developing their laws. (shrink)

Experimental research by social and cognitive psychologists has established that cooperative groups solve a wide range of problems better than individuals. Cooperative problem solving groups of scientific researchers, auditors, financial analysts, air crash investigators, and forensic art experts are increasingly important in our complex and interdependent society. This comprehensive textbook--the first of its kind in decades--presents important theories and experimental research about group problem solving. The book focuses on tasks that have demonstrably correct solutions within (...) mathematical, logical, scientific, or verbal systems, including algebra problems, analogies, vocabulary, and logical reasoning problems.The book explores basic concepts in group problem solving, social combination models, group memory, group ability and world knowledge tasks, rule induction problems, letters-to-numbers problems, evidence for positive group-to-individual transfer, and social choice theory. The conclusion proposes ten generalizations that are supported by the theory and research on group problem solving. Group Problem Solving is an essential resource for decision-making research in social and cognitive psychology, but also extremely relevant to multidisciplinary and multicultural problem-solving teams in organizational behavior, business administration, management, and behavioral economics. (shrink)

This article reports a study carried out in order to measure how semantic factors affect reductions in the difficulty of the Chinese Ring Puzzle (CRP) that involves removing five objects according to a recursive rule. We hypothesised that semantics would guide inferences about action decision making. The study involved a comparison of problem solving for two semantic isomorphic variants of the CRP ( fish and fleas ) with problem solving for the puzzle's classic variant (the Balls (...) and Boxes problem; Kotovsky learning involves generalising the relations within a coherent, interconnected whole that makes up the puzzle's rules. It seems that semantics make it easier for the puzzle's elements to be grouped together within coherent, meaningful wholes, which reduces relational complexity and facilitates problem solving. (shrink)

Any part of the world can be viewed and modelled in terms of its chosen qualitative and/or quantitative properties, OR its structure. The former approach has been used by nearly the whole of ‘human intellectual endeavor’, i.e conventional science of physics, the arts etc. Development of the latter or the ‘systemic view’ is the subject matter of the current work. The Purpose of Change is Problem Solving suggests that the ‘structural view’ is empirical, pervasive throughout experience and as (...) such results in a single domain as opposed to conventional science which consists of many domains like mechanics, electricity etc. Thus, a unique approach is required which is based on ‘general principles of systems’ translated into operational form by the symbolism of processed natural language called ‘linguistic modelling of scenarios’ which can carry mathematics and uncertainties. To model scenarios with complex structure, a description or story in natural language is expressed in terms of homogenous language of one – and two – place sentences, the ‘elementary constituents’ of which complex structures can be constructed [like a variety of buildings from bricks]. To correspond to the single domain, based on the logic of causation, a single scheme of ‘Management/producers – Product – User/consumer’ is proposed which is immediately applicable to structuring scenarios and guides their detailed linguistic modelling or design. The approach, subject to debate, can have significant impact on society and education, especially that of engineering which lacks a ‘comprehensive theory of structure’ of problematic scenarios. (shrink)

In the context of office work, learning to handle an Enterprise Resource Planning system is important as implementation costs for such systems and associated expectations are high. However, these expectations are often not met because the users are not trained adequately. Electronic Performance Support Systems are designed to support employees’ ERP-related problem-solving and informal learning. EPSS are supposed to enhance employees’ performance and informal workplace learning through task-specific and granular help in task performance and problem-solving. However, (...) there is little empirical research on EPSS. Two survey studies addressed this research gap. In the first study, 301 people working in Human Resource -related positions and functions evaluated the learning potential of EPSS as well as potential advantages and obstacles concerning the implementation and use of EPSS. Though other measures are currently assessed as more important for learning, HR employees expect a strong increase in the significance of EPSS for employee learning. In the second study, 652 users of ERP software completed a questionnaire on characteristics of their daily work tasks, team characteristics, individual dispositions, their coping with ERP-related problems, and characteristics of EPSS. Findings indicate that the most frequently available and used approach when dealing with an ERP-related problem is consulting colleagues. Three EPSS types can be distinguished by their increasing integration into the user interface and their context-sensitivity. While external and extrinsic EPSS are available to many users, intrinsic EPSS are less common but are used intensively if available. EPSS availability is identified to be a strong positive predictor of frequency of EPSS use, while agreeableness as well as the task complexity and information-processing requirements show small negative effects. Moreover, more intensive ERP users use EPSS more frequently. In general, ERP users value, features such as context-sensitivity, an integration of the EPSS into the ERP system’s user interface, the option to save one’s own notes, and information displayed in an extra window. It is expected that EPSS will play an important role in workplace learning in the future, along with other measures. (shrink)

This book explores solving the problem of complexity for science in the 21st century.

Sign-theoretical concepts have been used in research into the nature of living systems, not only by biologists, semioticians, and philosophers, but also by scientists who analyze organisms from the perspective of Decision Theory. Decision Theory (DT) describes both the external behavior and the internal information-processing of any kind of agent in terms of problem solving. Such “problem solving” is considered a complex process of: (1) defining a goal in an environment, (2) selecting the means to (...) reach the defined goal, and (3) controlling the effects of said selected means on the environment. The hypothesis that problem-solving agents are, first, physical entities and, second, sign-using systems is one of the most influential ideas in Decision Theory. This idea has been developed under the name of the ‘Physical Symbol System Hypothesis’ (PSSH) since the 1950s, particularly by two American scientists, Allen Newell and Herbert A. Simon, who did interdisciplinary research in cognitive science, artificial intelligence, economics, and decision theory. This paper first gives a short overview of the basic semiotic theory that underlies Newell’s and Simon’s work, and then offers some ideas on a specifically biosemiotic use of the Physical SymbolSystem Hypothesis. (shrink)

This book offers a uniquely constructive set of tools for engaging complex and controversial ethical problems. Covering such practical methods as diversifying options, lateral thinking, reframing problems, approaching conflicts as creative opportunities, and many others, it shows how to find "room to move" inside even the most challenging ethical problems, and thereby discover new and productive ways to deal with them. The book features numerous exercises and applications that consider a wide range of familiar ethical issues--including the moral status (...) of animals, the death penalty, poverty, drug use, and many others--and ends with some of the toughest: abortion, assisted suicide, and environmental ethics. An ideal supplement for any general ethics course, Creative Problem-Solving in Ethics can also be used in more specific "applied" courses like bioethics, business ethics, and social ethics, as well as in critical thinking courses that emphasize ethics. In addition, it provides a concise and engaging introduction to creative thinking for workshop participants and general readers. From the very beginning of the book, readers will discover that creative thinking can offer imaginative and promising alternatives to seemingly intractable ethical dilemmas. (shrink)

Complex systems are used, studied and instantiated in science, with what con-sequences? To be clear and systematic in response it is necessary to distin-guish the consequences, for science, of science using and studying complex systems, for philosophy of science, of science using and studying complex systems, for philosophy of science, of philosophy of science modelling sci-ence as a complex system. Each of these is explored in turn, especially. While has been least studied, it will be shown (...) how modelling science as a complex process may change our conception of science and thereby query what a philosophy of science adequate to this complexity might look like. (shrink)

Marr’s seminal distinction between computational, algorithmic, and implementational levels of analysis has inspired research in cognitive science for more than 30 years. According to a widely-used paradigm, the modelling of cognitive processes should mainly operate on the computational level and be targeted at the idealised competence, rather than the actual performance of cognisers in a specific domain. In this paper, we explore how this paradigm can be adopted and revised to understand mathematical problem solving. The computational-level approach applies (...) methods from computational complexity theory and focuses on optimal strategies for completing cognitive tasks. However, human cognitive capacities in mathematical problem solving are essentially characterised by processes that are computationally sub-optimal, because they initially add to the computational complexity of the solutions. Yet, these solutions can be optimal for human cognisers given the acquisition and enactment of mathematical practices. Here we present diagrams and the spatial manipulation of symbols as two examples of problem solving strategies that can be computationally sub-optimal but humanly optimal. These aspects need to be taken into account when analysing competence in mathematical problem solving. Empirically informed considerations on enculturation can help identify, explore, and model the cognitive processes involved in problem solving tasks. The enculturation account of mathematical problem solving strongly suggests that computational-level analyses need to be complemented by considerations on the algorithmic and implementational levels. The emerging research strategy can help develop algorithms that model what we call enculturated cognitive optimality in an empirically plausible and ecologically valid way. (shrink)

We investigate flexibility and problem solving in skilled action. We conducted a field study of mountain bike riding that required a learner rider to cope with major changes in technique and equipment. Our results indicate that relatively inexperienced individuals can be capable of fairly complex 'on-the-fly' problem solving which allows them to cope with new conditions. This problem solving is hard to explain for classical theories of skill because the adjustments are too large (...) to be achieved by automatic mechanisms and too complex and rapid to be achieved by cognitive processes as they are usually understood. A recent theory, Mesh, can explain these results because it posits that skill-specific cognitive abilities develop during skill learning and that control typically involves an interplay between cognitive and automatic mechanisms. Here we develop Mesh further, providing a detailed explanation for these problem solving abilities. We argue that causal representation, metacognitive awareness and other forms of performance awareness combine in the formulation and control of action strategies. We also argue that the structure of control present in this case is inconsistent with Bratman's model of intentions, and that, in the face of high uncertainty and risk, intentions can be much more labile than Bratman recognises. In addition, we found limitations and flaws in problem solving which illuminate the representations involved. Finally, we highlight the crucial role of social and cultural learning in the development of complex skills. (shrink)

Wicked Philosophy. Philosophy of Science and Vision Development for Complex Problems provides an overview of the philosophy of the natural sciences, the social sciences and the humanities, and explores how insights from these three domains can be integrated to help find solutions for the complex, 'wicked' problems we are currently facing. The core of a new science-based vision is complexity thinking, offering a meta-position for navigating alternative paradigms and making informed choices of resources for projects involving complex (...) problems. The book also brings design thinking into problem-solving and teaching, fostering construction of an integrative approach that bridges structure and action amplified by transdisciplinary engagement of stakeholders in society. Bron: Flaptekst, uitgeversinformatie. (shrink)

Solving complex socio-technical problems, this paper claims, involves diverse knowledges (cognitive diversity), competing interests (social diversity), and pragmatism. To explain this view, this paper first explores two different cases: Canadian pulp and paper mill pollution and siting nuclear reactors in seismically sensitive areas of California. Solving such socio-technically complex problems involves cognitive diversity as well as social diversity and pragmatism. Cognitive diversity requires one to not only recognize relevant knowledges but also to assess their validity. Finally, (...) it is suggested, integrating the resultant set of diverse relevant and valid knowledges determines the parameters of the solution space for the problem. (shrink)

Most psychological theories of problem solving have focused on modeling explicit processes that gradually bring the solver closer to the solution in a mostly explicit and deliberative way. This approach to problem solving is typically inefficient when the problem is too complex, ill-understood, or ambiguous. In such a case, a ‘creative’ approach to problem solving might be more appropriate. In the present paper, we propose a computational psychological model implementing the Explicit-Implicit Interaction (...) theory of creative problem solving that involves integrating the results of implicit and explicit processing. In this paper, the new model is used to simulate insight in creative problem solving and the overshadowing effect. (shrink)