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

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)

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)

A new approach to Hume's problem of induction that justifies the optimality of induction at the level of meta-induction. Hume's problem of justifying induction has been among epistemology's greatest challenges for centuries. In this book, Gerhard Schurz proposes a new approach to Hume's problem. Acknowledging the force of Hume's arguments against the possibility of a noncircular justification of the reliability of induction, Schurz demonstrates instead the possibility of a noncircular justification of the optimality of induction, or, more (...) precisely, of meta-induction (the application of induction to competing prediction models). Drawing on discoveries in computational learning theory, Schurz demonstrates that a regret-based learning strategy, attractivity-weighted meta-induction, is predictively optimal in all possible worlds among all prediction methods accessible to the epistemic agent. Moreover, the a priori justification of meta-induction generates a noncircular a posteriori justification of object induction. Taken together, these two results provide a noncircular solution to Hume's problem. Schurz discusses the philosophical debate on the problem of induction, addressing all major attempts at a solution to Hume's problem and describing their shortcomings; presents a series of theorems, accompanied by a description of computer simulations illustrating the content of these theorems (with proofs presented in a mathematical appendix); and defends, refines, and applies core insights regarding the optimality of meta-induction, explaining applications in neighboring disciplines including forecasting sciences, cognitive science, social epistemology, and generalized evolution theory. Finally, Schurz generalizes the method of optimality-based justification to a new strategy of justification in epistemology, arguing that optimality justifications can avoid the problems of justificatory circularity and regress. (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 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)

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)

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)

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)

The goals ofthis paper are to identify (in Section II) some general features of problem solving strategies in science, to discuss (in Section III) how Chomsky has employed two particularly popular discovery strategies in science, and to show (in Section IV) how these strategies inform Chomskyan linguistics. In Section IV I will discuss (1) how their employment in linguistics manifests features of scientific problem solving outlined in Section Il and (2) how an analysis in terms of (...) those features suggests a natural account for many controversial aspects 0fChomsky’s methods. I will specifically examine how this analysis bears on Chomsky’s claims concerning competence theories’ centrality in psychology and their psychological reality. Although no methodological considerations bar Chomsky from tinkering with our notion ofpsychology, competence theories mus! eventually offer some fruitful empirical connections with psycholinguistics and that part of mainstream cognitive psychology concerned with language study tojustify that tinkering. After twenty years of research such connections have proven rare enough to raise important doubts about thejustification ofChomsl·:y’s claims for the place of competence theory in cognitive psychology {and for the psychological reality of the mechanism it describes). Although I will argue (contra man) tf C}iom.rk_y’s critics) that his methods are unexceptionable, still [contra Chomsky) his theories have not proven sufficiently robust empirically to justify his strong claims concerning their position in cognitive psychology. (shrink)

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)

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)

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.

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)

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)

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)

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)

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)

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.

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...

In a study examining the effects of time of day on problem solving, participants solved insight and analytic problems at their optimal or non-optimal time of day. Given the presumed differences in the cognitive processes involved in solving these two types of problems, it was expected that the reduced inhibitory control associated with non-optimal times of the day would differentially impact performance on the two types of problems. In accordance with this expectation, results showed consistently greater insight (...) problem solving performance during non-optimal times of day compared to optimal times of day but no consistent time of day effects on analytic problem solving. The findings indicate that tasks involving creativity might benefit from a non-optimal time of day. (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.

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)

Behavior that solves a problem is distinguished by the fact that it changes another part of the solver's behavior and is strengthened when it does so. Problem solving typically involves the construction of discriminative stimuli. Verbal responses produce especially useful stimuli, because they affect other people. As a culture formulates maxims, laws, grammar, and science, its members behave more effectively without direct or prolonged contact with the contingencies thus formulated. The culture solves problems for its members, and (...) does so by transmitting the verbal discriminative stimuli called rules. Induction, deduction, and the construction of models are ways of producing rules. Behavior that solves a problem may result from direct shaping by contingencies or from rules constructed either by the problem solver or by others. Because different controlling variables are involved, contingency-shaped behavior is never exactly like rule-governed behavior. The distinction must take account of a system which establishes certain contingencies of reinforcement, such as some part of the natural environment, a piece of equipment, or a verbal community; the behavior shaped and maintained by these contingencies; rules, derived from the contingencies, which specify discriminative stimuli, responses, and consequences, and the behavior occasioned by the rules. (shrink)

'Never before has there been so many and such dreadful weapons in so many irresponsible hands.' - Karl Popper, from the Preface All Life is Problem Solving is a stimulating and provocative selection of Popper's writings on his main preoccupations during the last twenty-five years of his life. This collection illuminates Popper's process of working out key formulations in his theory of science, and indicates his view of the state of the world at the end of the Cold (...) War and after the collapse of communism. (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)

_'Never before has there been so many and such dreadful weapons in so many irresponsible hands.'__ - Karl Popper, from the Preface_ _All Life is Problem Solving_ is a stimulating and provocative selection of Popper's writings on his main preoccupations during the last twenty-five years of his life. This collection illuminates Popper's process of working out key formulations in his theory of science, and indicates his view of the state of the world at the end of the Cold War (...) and after the collapse of communism. (shrink)

Intelligent mental representations of physical, cognitive and social environments allow humans to navigate enormous search spaces, whose sizes vastly exceed the number of neurons in the human brain. This allows us to solve a wide range of problems, such as the Traveling Salesperson Problem, insight problems, as well as mathematics and physics problems. As an area of research, problem solving has steadily grown over time. Researchers in Artificial Intelligence have been formulating theories of problem solving (...) for the last 70 years. Psychologists, on the other hand, have focused their efforts on documenting the observed behavior of subjects solving problems. This book represents the first effort to merge the behavioral results of human subjects with formal models of the causative cognitive mechanisms. The first coursebook to deal exclusively with the topic, it provides a main text for elective courses and a supplementary text for courses such as cognitive psychology and neuroscience. (shrink)

This paper reports on a study that was conducted on the effects of training students in specific strategic and meta-cognitive questioning strategies on the development of reasoning, problem-solving, and learning during cooperative inquiry-based science activities. The study was conducted in 18 sixth grade classrooms and involved 35 groups of students in three conditions: the cognitive questioning condition; the Philosophy for Children condition; and the comparison condition. The students were videotaped as they worked on a specific inquiry-science task once (...) each term for two consecutive school terms. The results show that the students in all conditions demonstrated more helping discourses or discourses known to mediate learning than any other of the discourse categories. This outcome is encouraging because it is the helping discourses where students provide explanations, elaborations, and reasons that promote follow-up learning. (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)

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)

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)

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)

The general thesis that science is essentially a problem-solving activity is extended to the development of new fields. Their development represents a research strategy for generating and solving new unsolved problems and solving existing ones in related fields. The pattern of growth of new fields is guided by the central problems within the field and applicable problems in other fields. Proponents of existing research traditions welcome work in new fields, if they believe it will increase the (...) problem-solving effectiveness of their tradition. Correspondingly, researchers in new fields will graft their work onto established traditions, if they believe it will augment the problem-solving effectiveness of their work. The above claims are defended through using the development of paleomagnetism as a case study. (shrink)