In the course of daily life we solve problems often enough that there is a special term to characterize the activity and the right to expect a scientific theory to explain its dynamics. The classical view in psychology is that to solve a problem a subject must frame it by creating an internal representation of the problem’s structure, usually called a problem space. This space is an internally generable representation that is mathematically identical to a graph structure (...) with nodes and links. The nodes can be annotated with useful information, and the whole representation can be distributed over internal and external structures such as symbolic notations on paper or diagrams. If the representation is distributed across internal and external structures the subject must be able to keep track of activity in the distributed structure. Problem solving proceeds as the subject works from an initial state in mentally supported space, actively constructing possible solution paths, evaluating them and heuristically choosing the best. Control of this exploratory process is not well understood, as it is not always systematic, but various heuristic search algorithms have been proposed and some experimental support has been provided for them. (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 complex cognition (...) and emotion in the CPS context is discussed. The question if CPS requires complex cognition is answered with a tentative “yes.”. (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)

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 (...) class='Hi'>solving in the background. In this paper, we return the focus to content issues and address the important features that define complex problems. (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 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)

Recent research on human problem solving has largely focused on laboratory tasks that do not demand from the subject much prior, task‐related information. This study seeks to extend the theory of human problem solving to semantically richer domains that are characteristic of professional problem solving. We discuss the behavior of a single subject solving problems in chemical engineering thermodynamics. We use as a protocol‐encoding device a computer program called SAPA which also doubles as (...) a theory of the subject's problem‐solving behavior. The subject made extensive use of means‐ends analysis, similar to that observed in semantically less rich domains, supplemented by recognition mechanisms for accessing information in semantic memory. (shrink)

This paper provides a principled and elegant solution to the Gettier problem. The key move is to draw a general metaphysical distinction and conscript it for epistemological purposes. Section 1 introduces the Gettier problem. Sections 2–5 discuss instructively wrong or incomplete previous proposals. Section 6 presents my solution and explains its virtues. Section 7 answers the most common objection.

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)

The question that is the subject of this article is not intended to be a sociological or statistical question about the practice of today’s mathematicians, but a philosophical question about the nature of mathematics, and specifically the method of mathematics. Since antiquity, saying that mathematics is problem solving has been an expression of the view that the method of mathematics is the analytic method, while saying that mathematics is theorem proving has been an expression of the view that (...) the method of mathematics is the axiomatic method. In this article it is argued that these two views of the mathematical method are really opposed. In order to answer the question whether mathematics is problem solving or theorem proving, the article retraces the Greek origins of the question and Hilbert’s answer. Then it argues that, by Gödel’s incompleteness results and other reasons, only the view that mathematics is problem solving is tenable. (shrink)

In the course of daily life we solve problems often enough that there is a special term to characterize the activity and the right to expect a scientific theory to explain its dynamics. The classical view in psychology is that to solve a problem a subject must frame it by creating an internal representation of the problem‘s structure, usually called a problem space. This space is an internally generable representation that is mathematically identical to a graph structure (...) with nodes and links. The nodes can be annotated with useful information, and the whole representation can be distributed over internal and external structures such as symbolic notations on paper or diagrams. If the representation is distributed across internal and external structures the subject must be able to keep track of activity in the distributed structure. Problem solving proceeds as the subject works from an initial state in this mentally supported space, actively construction possible solution paths, evaluating them and heuristically choosing the best. Control of this exploratory process is not well understood, as it is not always systematic, but various heuristic search algorithms have been proposed and some experimental support has been provided for them. (shrink)

Creativity is commonly seen as beyond the scope of rationality. In the present paper, it is argued that available insights in epistemology and available results in logic enable us to incorporate creativity within an independently sensible view on human rationality.

A general model of problem‐solving processes based on misconception elimination is presented to simulate both impasses and solving processes. The model operates on goal‐related rules and a set of constraint rules in the form of “if (state or goal), do not (Action)” for the explicit constraints in the instructions and the implicit constraints that come from misconceptions of legal moves. When impasses occur, a constraint elimination mechanism is applied. Because successive eliminations of implicit constraints enlarge the (...) class='Hi'>problem space and have an effect on planning, the model integrates “plan‐based” and “constraint‐based” approaches to problem‐solving behavior.Simulating individual protocols of Tower of Hanoi situations shows that the model, which has a proper set of constraints, predicts a single move with no alternative on about 61% of the movements and that protocols are quite successfully simulated movement by movement. Finally, it is shown that many features of previous models are embedded in the constraint elimination model. (shrink)

This paper begins with an analysis of global problems shaping education, particularly as they impact upon learning and life chances. In addressing these problems a range of philosophical positions and controversies are considered, including: traditional romantic and institutional views of schooling; and more recent maximalist, neo-liberal, emancipatory and post-modern-perspectives of lifelong learning. In this paper we argue that these do not represent 'the last word' on the provision of learning and the enhancement of life chances and instead we put forward (...) an alternative view based upon the notion of adopting an inclusive problem-solving approach, which we believe may be better suited to offering solutions to the various global problems that have been identified or that are still emerging. We believe that such an approach addresses and expands the individual, social, economic and political features of education and conduces to the improvement and expansion of learning and life chances. (shrink)

Problem Solving Technologies provides a user friendly understanding of technological objects including what they are and how the function in our lives.

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)

Philosophical pragmatism provides a theory and practical guidance for engaged philosophy. The movement to apply philosophy to real-world problems gained traction in the 1970s and has become an important area of philosophical inquiry. Applied philosophy draws connections between philosophical principles and real-life problems. This has been a valuable methodology for many purposes, and it especially serves the purposes of philosophers. Unfortunately, it often starts from existing frameworks or principles that are recognized by philosophers but does not start from real-life problems (...) as they are experienced by people. Indeed, sometimes people observe miscommunication and disconnections but are not clear what the source of the problem is. Identifying the nature of a social problem from the perspective of the people who deal with it is a large part of what is required to then analyze the problem philosophically. This requires communicating directly with practitioners, policymakers, and researchers in the field at issue. Paul Thompson’s engaged philosophical approach to agricultural ethics demonstrates the diversity of philosophical activities that are required to accomplish this goal, and it is rooted in pragmatism. Engaged philosophy is more expansive than applied philosophy because it serves many functions and the frameworks produced are emergent rather than prescribed. Engaged philosophy offers an implicit critique of contemporary norms of applied philosophical practice, and it opens up creative opportunities for philosophers to engage in real-life problem solving. This essay traces Paul Thompson’s strategies for engaged philosophy and their relation to pragmatism. (shrink)

Insight problem solving is thought to underpin creative thought as it incorporates both divergent (generating multiple ideas and solutions) and convergent (arriving at the optimal solution) thinking approaches. The current literature on schizotypy and creativity is mixed and requires clarification. An alternate approach was employed by designing an exploratory web-based study using only correlates of schizotypal traits (paranoia, dissociation, cognitive failures, fantasy proneness, and unusual sleep experiences) and examining which (if any) predicted optimal performance on an insight (...) class='Hi'>problem-solving task. One hundred and twenty-one participants were recruited online from the general population and completed the number reduction task. The discovery of the hidden rule (HR) was used as a measure of insight. Multivariate logistic regression analyses highlighted persecutory ideation to best predict the discovery of the HR (OR = 1.05; 95% CI 1.01–1.10, p = 0.017), with a one-point increase in persecutory ideas corresponding to the participant being 5% more likely to discover the HR. This result suggests that persecutory ideation, above other schizotypy correlates, may be involved in insight problem solving. (shrink)

Anders, Rudi To solve a problem such as wars between nations and civil wars it is necessary to discover what causes the problem.

This paper presents an analysis of emotional and affectively toned discourse in biomedical engineering researchers’ accounts of their problem solving practices. Drawing from our interviews with scientists in two laboratories, we examine three classes of expression: explicit, figurative and metaphorical, and attributions of emotion to objects and artifacts important to laboratory practice. We consider the overall function of expressions in the particular problem solving contexts described. We argue that affective processes are engaged in problem (...) class='Hi'>solving, not as simply tacked onto reasoning but as integral to it. The examples we present illustrate the close relation of emotion to problem solving and experimentation; they also implicate social and cultural dimensions of emotion expression. The analysis underscores a need to consider emotional expression to be intimately and importantly tied to the cognitive achievements and social negotiations of laboratory practices. (shrink)

The current study describes the implementation of an online Future Problem Solving program in the field of Health education and set out to explore its contribution to students' eHealth Literacy identity, by using two levels of teacher guidance: minimal vs. frequent. FPS was employed in two groups of Health students. In the research group, frequent weekly guidance was provided to the students centered on the enhancement of eHealth Literacy skills, whereas in the control group minimal guidance was offered (...) by the lecturer. Data for the analysis were gathered from 113 Israeli undergraduate students of a Management of Health Service Organizations program, of whom 62 comprised the research group. Data were gathered twice, pre- and post-program implementation from both groups. Findings showed significant differences between the tests only for the research group, with increased levels of eHealth Literacy skills detected between the tests. The perception of the FPS program as meaningful contributed to students' perceived eHealth Literacy skills only in the research group whereas non-significant results were shown for the control group. This study mainly shows that the enhancement of skills in online educational environments requires frequent and personalized guidance. Faculty must recognize the role of the instructor as a facilitator of learning and design successful scaffolding strategies to nurture students' lifelong learning skills during distance learning. (shrink)

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)

In adversarial problem solving (APS), one must anticipate, understand and counteract the actions of an opponent. Military strategy, business, and game playing all require an agent to construct a model of an opponent that includes the opponent's model of the agent. The cognitive mechanisms required for such modeling include deduction, analogy, inductive generalization, and the formation and evaluation of explanatory hypotheses. Explanatory coherence theory captures part of what is involved in APS, particularly in cases involving deception.

In the movie The Gold Rush Charlie Chaplin and his friend are stranded in a log cabin in the middle of winter while a blizzard rages. The cabin is isolated, and they have a very big problem – there is nothing to eat. They pace around wondering what to do. Charlie's friend starts to see Charlie as a chicken, and he tries to kill him. He chases Charlie around the cabin many times. Eventually they hit upon the idea of (...) boiling an old boot and eating it for dinner. With great delicacy they sit at the table and eat the boot as if it were a gourmet meal. They solved the problem of having nothing to eat. While their solution to the problem did not result in a culinary feast, this example reveals two crucial features of problem solving. First, a problem exists when a goal must be achieved and the solution is not immediately obvious. Second, problem solving often involves attempting different ways to solve the problem. Put more formally, a problem has four components. First, there is an initial state. This is the person's state of knowledge at the start of a problem. Second, there is the goal state: the goal that the person wishes to achieve. Third are the actions or operations that the problem‐solver can use to get to the goal state. Fourth is the task environment that the solver is working in. The task environment consists of the features of the physical environment that can either directly or indirectly constrain or suggest different ways of solving a problem. I will sketch out the main currents of thinking in research in this area, beginning by reviewing the history of research on problem solving and then focusing on a number of important issues in problem‐solving research. Finally, I will give an overview of some recent developments. (shrink)

This study investigated how problem solvers get into and out of a state of impasse while solving difficult problems. 47 participants had to decipher the secret method behind 33 magic tricks while r...

Learning to solve a class of problems can be characterized as a search through a space of hypotheses about the rules for solving these problems. A series of four experiments studied how different learning conditions affected the search among hypotheses about the solution rule for a simple computational problem. Experiment 1 showed that a problem property such as computational difficulty of the rules biased the search process and so affected learning. Experiment 2 examined the impact of examples (...) as instructional tools and found that their effectiveness was determined by whether they uniquely pointed to the correct rule. Experiment 3 compared verbal directions with examples and found that both could guide search. The final experiment tried to improve learning by using more explicit verbal directions or by adding scaffolding to the example. While both manipulations improved learning, learning still took the form of a search through a hypothesis space of possible rules. We describe a model that embodies two assumptions: the instruction can bias the rules participants hypothesize rather than directly be encoded into a rule; participants do not have memory for past wrong hypotheses and are likely to retry them. These assumptions are realized in a Markov model that fits all the data by estimating two sets of probabilities. First, the learning condition induced one set of Start probabilities of trying various rules. Second, should this first hypothesis prove wrong, the learning condition induced a second set of Choice probabilities of considering various rules. These findings broaden our understanding of effective instruction and provide implications for instructional design. (shrink)

Objective: To identify problem solving strategies in general practice. Basic procedures: Three styles of scientific reasoning were defined and modelled on the medical environment. These models were tested in a simulated doctor-patient encounter.

To help consider why some groups solve problems successfully but others do not, this article introduces a framework for analyzing sequences of group members' actions. The dimensions of evaluation of the previous action , knowledge content , and invitational form organize twenty-seven individual actions, each with specific functions and conditions of use. Evaluations, repetitions and invitational forms link actions together to create coherent social interactions, and thereby serve as possible quantitative measures of collaboration quality. Specific individual action also helps constitute (...) specific social interactions. Six types of social interactions that occur during group problem-solving are organized by problem knowledge distribution and degree of cooperation . This framework's mutually exclusive categories and multi-function individual actions allow statistical analyses of many group interactions both in their entirety and infine detail. (shrink)

In this paper I study the activity of mathematical problem-solving in scientific practice, focussing on enquiries in mathematical social science. I identify three salient phases of mathematical problem-solving and adopt them as a reference frame to investigate aspects of applications that have not yet received extensive attention in the philosophical literature.

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)

According to Zagzebski, understanding something is justified by the exercise of cognitive skills and intellectual virtues the knower possesses. Zagzebski develops her view by suggesting that “understanding has internalist conditions for success”. Against this view, Grimm raises an objection: what justifies understanding is the reliability of the processes by which we come to understand, and we need not be aware of the outcome of all reliable processes. Understanding is no exception, so, given that understanding something results from reliable processes, we (...) need not always be aware of what we understand. I reply to Grimm’s objection; I argue that Zagzebski’s internalist requirement is best conceived as accessibility to conscious reflection. The accessibility condition is satisfied because understanding solves problems on the knower’s research agenda. And whenever problem-solving is non-trivial, the knower needs to reflect on what the best solving strategy is. (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)

Visual analogy is believed to be important in human problem solving. Yet, there are few computational models of visual analogy. In this paper, we present a preliminary computational model of visual analogy in problem solving. The model is instantiated in a computer program, called Galatea, which uses a language for representing and transferring visual information called Privlan. We describe how the computational model can account for a small slice of a cognitive-historical analysis of Maxwell’s reasoning about (...) electromagnetism. (shrink)

Rather than being random deviation, student errors can be a source of insight into the nature of student difficulties. This paper reports on (and offers pedagogical advice concerning) many common student errors in the construction of proofs, in the application of inference and replacement rules, and in the choice of proof strategies. In addition, a detailed description of the bottom-up strategy for “working backwards” is supplied, along with a discussion of the main difficulties students face when trying to solve proofs (...) in this fashion. Ultimately, it is argued that students can employ both top-down and bottom-up proofs strategies by making use of a graphic proof representation. (shrink)

This essay is part of a dossier on Cristina Lafont's book Democracy without Shortcuts.