A historical example is considered which conflicts with Laudan's Problem Solving Model [1981]. In the period 1840–85 chemists preferred a theory with 3 major conceptual problems (the Liebig Theory of Acids) to Lavoisier's which had only one major conceptual problem (why are the halogen hydrides acids?). The overall conceptual merits of Lavoisier's scheme have been revived in the modern Lux-Flood classification of Acids. Larry Laudan [1977], [1981] proposed a problem solving model of scientific rationality which (...) not only applied to global theories but, if one takes the final paragraph of his [1977] seriously, also applies to sub theories, auxiliary hypotheses and sub auxiliary hypotheses all the way down the line. (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)

This article proposes a unified framework for understanding creative problem solving, namely, the explicit–implicit interaction theory. This new theory of creative problem solving constitutes an attempt at providing a more unified explanation of relevant phenomena (in part by reinterpreting/integrating various fragmentary existing theories of incubation and insight). The explicit–implicit interaction theory relies mainly on 5 basic principles, namely, (a) the coexistence of and the difference between explicit and implicit knowledge, (b) the simultaneous involvement of implicit and (...) explicit processes in most tasks, (c) the redundant representation of explicit and implicit knowledge, (d) the integration of the results of explicit and implicit processing, and (e) the iterative (and possibly bidirectional) processing. A computational implementation of the theory is developed based on the CLARION cognitive architecture and applied to the simulation of relevant human data. This work represents an initial step in the development of process-based theories of creativity encompassing incubation, insight, and various other related.. (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)

Hamblin distinguished between formal and descriptive dialectic. Formal normative models of deliberation dialogue have been strongly emphasized as argumentation frameworks in computer science. But making such models of deliberation applicable to real natural language examples has reached a point where the descriptive aspect needs more interdisciplinary work. The new formal and computational models of deliberation dialogue that are being built in computer science seem to be closely related to some already existing and very well established computing technologies (...) such as problem solving and decision making, but whether or how dialectical argumentation can be helpful to support these systems remains an open question. The aim of this paper is to examine some real examples of argumentation that seem to hover on the borderlines between deliberation, problem solving and decision making. (shrink)

In my paper I focus on the growth of knowledge in finance from an heuristic viewpoint and I propose the analysis of two different knowledge-advancing strategies usually adopted at the frontier of knowledge, i.e. problem-solving and model-building. I show how these two strategies, even though both effective in the short-run, nonetheless provide descriptions of the target object and which are different in their descriptive and knowledge-advancing depth. In order to do so, I propose a case study borrowed from (...) the modelling activities in the Libor market. (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)

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)

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.

The nature of creative thinking is complex and multifaceted, often involving cognitive processes and dispositions modulated by implicit cultural belief systems and ways of thinking. In this article, we build on existing research on the relations of creative thinking and culture, and explore how specific cultural resources can be harnessed to foster creative problem-solving in education. We first review the recent changes in our understanding of creative thinking, from an exclusive focus on cognitive processes to a more inclusive (...) view of creative problem-solving as socially negotiated and culturally modulated, carrying important cultural functions. We then introduce a pedagogical model, QEOSA, to illustrate how cultural resources, particularly culture-specific ways of thinking about the world, can be harnessed to foster creative thinking in education, and what developmental and pedagogical considerations are involved to make it effective. We finally conclude this article by indicating the value of this line of work that integrates psychological, cultural, developmental, and educational principles in fostering the development of a creative mind-set with relevant knowledge, skills, dispositions, and values. (shrink)

According to the restructuring hypothesis, insight problem solving typically progresses through consecutive stages of search, impasse, insight, and search again for someone, who solves the task. The order of these stages was determined through self-reports of problem solvers and has never been verified behaviorally. We asked whether individual analysis of problem solving attempts of participants revealed the same order of problem solving stages as defined by the theory and whether their subjective feelings corresponded (...) to the problem solving stages they were in. Our participants tried to solve the Five-Square problem in an online task, while we recorded the time and trajectory of their stick movements. After the task they were asked about their feelings related to insight and some of them also had the possibility of reporting impasse while working on the task. We found that the majority of participants did not follow the classic four-stage model of insight, but had more complex sequences of problem solving stages, with search and impasse recurring several times. This means that the classic four-stage model is not sufficient to describe variability on the individual level. We revised the classic model and we provide a new model that can generate all sequences found. Solvers reported insight more often than non-solvers and non-solvers reported impasse more often than solvers, as expected; but participants did not report impasse more often during behaviorally defined impasse stages than during other stages. This shows that impasse reports might be unreliable indicators of impasse. Our study highlights the importance of individual analysis of problem solving behavior to verify insight theory. (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.

The present paper will summarise the methodology, the scientific outcomes, and the potential for generalisation of the model of a project that studied cohabitation between human inhabitants and liminal species (in the present case, corvids) in Tartu, Estonia, from October 2021 to July 2023, with a comparative field study in Paris, France. It will present the context and goals of using a semiotic model to map interspecific cohabitation, expose what kind of data can be used to feed the model in (...) a relevant way and how it was done in the case of this project. This paper will present how the model diagnosed issues in cohabitation, both from material nuisances and cultural aspects, insisting on the concept of “hostile minority” that emerged from the study. It will discuss the importance of problem-solving in interspecific cohabitation, what the model suggested regarding this aspect, how this tool can be generalised to a large variety of cases and why it should be used this way. (shrink)

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)

As one of the important 21st-century skills, collaborative problem solving (CPS) has caught much attention in the assessment area. Two initiative approaches have been created: the human-to-human and human-to-agent modes. Between the two modes, the human-to-human interaction is much closer to the real-world situation and its process stream data can reveal more detailed information about the cognitive processes. In order to measure CPS ability effectively by this mode, how to extract indicators from the data and model it is (...) crucial, while the existing methods all have some disadvantages. In the present study, we proposed a new paradigm for extracting indicators and modeling the dyad data in the human-to-human mode. Specifically, both individual and group indicators were extracted from the data stream, which served as evidence for demonstrating CPS skills. In addition, a within-item multidimensional Rasch model was used to fit the dyad data. To test the validity of the paradigm, we developed five tasks following the asymmetric mechanism and integrated them into an online testing platform. Four hundred thirty-four students from China participated in the assessment and the online platform recorded their crucial actions with time stamps. The new paradigm was used to deal with the generated process stream data. Results showed that the model fitted well. The item parameter estimates and fitting indexes were acceptable, and students were well differentiated. In general, the new paradigm of extracting indicators and modeling the dyad data is feasible for improving the human-to-human assessment of CPS. Finally, the limitations of the current study and further research directions are discussed. (shrink)

Logic-based approaches to legal problem solving model the rule-governed nature of legal argumentation, justification, and other legal discourse but suffer from two key obstacles: the absence of efficient, scalable techniques for creating authoritative representations of legal texts as logical expressions; and the difficulty of evaluating legal terms and concepts in terms of the language of ordinary discourse. Data-centric techniques can be used to finesse the challenges of formalizing legal rules and matching legal predicates with the language of ordinary (...) parlance by exploiting knowledge latent in legal corpora. However, these techniques typically are opaque and unable to support the rule-governed discourse needed for persuasive argumentation and justification. This paper distinguishes representative legal tasks to which each approach appears to be particularly well suited and proposes a hybrid model that exploits the complementarity of each. (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)

Insight problem solving was investigated with the matchstick algebra problems developed by Knoblich, Ohlsson, Haider, and Rhenius (1999). These problems are false equations expressed with Roman numerals that can be made true bymoving one matchstick. In a first group participants examined a static two-dimensional representation of the false algebraic expression and told the experimenter which matchstick should be moved. In a second group, participants interacted with a three-dimensional representation of the false equation. Success rates in the static group (...) for different problem types replicated the pattern of data reported in Knoblich et al. (1999). However, participants in the interactive group were significantly more likely to achieve insight. Problem-solving success in the static group was best predicted by performance on a test of numeracy, whereas in the interactive group it was best predicted by performance on a test of visuo-spatial reasoning. Implications for process models of problem solving are discussed. (shrink)

How do people use information from others to solve complex problems? Prior work has addressed this question by placing people in social learning situations where the problems they were asked to solve required varying degrees of exploration. This past work uncovered important interactions between groups' connectivity and the problem's complexity: the advantage of less connected networks over more connected networks increased as exploration was increasingly required for optimally solving the problem at hand. We propose the Social Interpolation (...) Model (SIM), an agent‐based model to explore the cognitive mechanisms that can underlie exploratory behavior in groups. Through results from simulation experiments, we conclude that “exploration” may not be a single cognitive property, but rather the emergent result of three distinct behavioral and cognitive mechanisms, namely, (a) breadth of generalization, (b) quality of prior expectation, and (c) relative valuation of self‐obtained information. We formalize these mechanisms in the SIM, and explore their effects on group dynamics and success at solving different kinds of problems. Our main finding is that broad generalization and high quality of prior expectation facilitate successful search in environments where exploration is important, and hinder successful search in environments where exploitation alone is sufficient. (shrink)

Criticisms of patent laws for technological innovations in the United States reveal a multifaceted milieu of problems centered around the protection of short-term economic gain and individual property rights. In this article, we consider this a conflict between current patent laws and the innovation capabilities of organizations. We propose a solution that enables the company to assure its long-term survival in the face of these restrictions. This presumes that the firm will at least maintain its innovation capacities while preserving the (...) company's ethical values and those of its social environment. We offer a theoretical model that is designed to help managers and policymakers reorient their governance strategies for managing the innovation process, using the “ethics of responsibility,” which establishes the link to individual moral values at the beginning of a governance process as well as the consequences of a decision. Our integrated causal model of ethical innovation for patents is presented and implications for global organizations and possible solutions for patent law process failure are offered. (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)

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)

Real world problem-solving (RWPS) is what we do every day. It requires flexibility, resilience, resourcefulness, and a certain degree of creativity. A crucial feature of RWPS is that it involves continuous interaction with the environment during the problem-solving process. In this process, the environment can be seen as not only a source of inspiration for new ideas but also as a tool to facilitate creative thinking. The cognitive neuroscience literature in creativity and problem-solving is (...) extensive, but it has largely focused on neural networks that are active when subjects are not focused on the outside world, i.e., not using their environment. In this paper, I attempt to combine the relevant literature on creativity and problem-solving with the scattered and nascent work in perceptually-driven learning from the environment. I present my synthesis as a potential new theory for real world problem-solving and map out its hypothesized neural basis. I outline some testable predictions made by the model and provide some considerations and ideas for experimental paradigms that could be used to evaluate the model more thoroughly. (shrink)

According to the diversity-beats-ability theorem, groups of diverse problem solvers can outperform groups of high-ability problem solvers. We argue that the model introduced by Lu Hong and Scott Page is inadequate for exploring the trade-off between diversity and ability. This is because the model employs an impoverished implementation of the problem-solving task. We present a new version of the model which captures the role of ‘ability’ in a meaningful way, and use it to explore the trade-offs (...) between diversity and ability in scientific problem solving. (shrink)

Problem solving is a crucial higher-order thinking ability of humans. Humans’ ability to solve problems is a critical higher-order thinking ability. Mathematical problem solving, analogical problem solving, complex problem solving, situated problem solving, and so on are all examples of problem solving. Furthermore, distinct types of research analysis, models, and theories are based on the mechanisms and elements involved in diverse problem-solving types. The conventional approach (...) to understanding human problem solving is a representation-laden description, which is similar to most cognitive explanations of psychological processes. On the other hand, the paper goes beyond representational theories and models to investigate nonrepresentational and situated aspects of human problem solving. Problem solving is a crucial higher-order thinking ability of humans. The paper is a rudimentary attempt to present a nonrepresentational, Affordance-Situation-Attunement (ASA) framework of human problem solving. The aim is to invoke ASA as an alternative framework, in contrast with the dominant representational explanation of human problem solving. The aim is not to disparage the representational theories and models of problem solving but to contribute a nonrepresentational working framework and elements for highlighting the situated nature of human problem solving. (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)

A paradigm instructs in how to do research successfully. Analytic philosophy of science, currently dominant, models paradigmatic rational science as a system of logical inferences. It is, however, an abundantly inadequate paradigm. This paper presents an alternative paradigm: science as an organized collection of problem solving processes. This position is backed, on the one side, by a cognitive model of problem solving process applicable to all problem solving circumstances and, on the other, by (...) a non-formal conception of rationality that provides a wider enriched notion of rational research process than is available to the analytic paradigm. The result is a very different way of looking at science and of doing history and philosophy of science. The position is developed sufficiently to display its nature and merits. (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)

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 this article, the pragma-dialectical model of a critical discussion is demonstrated to provide a useful instrument for discovering causes of an unsatisfactory development of problem-solving discussions. First a sketch is given of the development of a problem-solving discussion which, in the opinion of the participants themselves, developed in an unsatisfactory fashion. Then it is argued that this development can be traced back to flaws in the execution of the stages of a critical discussion.

This article proposes a theoretical framework for external representation based problem solving. The Tic‐Tac‐Toe and its isomorphs are used to illustrate the procedures of the framework as a methodology and test the predictions of the framework as a functional model. Experimental results show that the behavior in the Tic‐Tac‐Toe is determined by the directly available information in external and internal representations in terms of perceptual and cognitive biases, regardless of whether the biases are consistent with, inconsistent with, or (...) irrelevant to the task. It is shown that external representations are not merely inputs and stimuli to the internal mind and that they have much more important functions than mere memory aids. A representational determinism is suggested—the form of a representation determines what information can be perceived, what processes can be activated, and what structures can be discovered from the specific representation. (shrink)

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)

Understanding arithmetic word problems involves a complex interaction of text comprehension and mathematical processes. This article presents a computer simulation designed to capture the working memory demands required in “bottomup” comprehension of arithmetic word problems. The simulation's sentence‐level parser and text integration component reflect the importance of processing the problem from its original natural language presentation. Children's probability of solution was analyzed in exploratory regression analyses as a function of the simulation's sentence‐level and text integration processes. Working memory variables (...) measuring the combined effects of concepts to remember and text integration inferences account for a significant proportion of variance in children's solution probabilities across the first four grade levels (K‐3). Consistent with previous results from others, which highlighted the significance of small changes in problem wording, the simulation offers a process‐oriented perspective as to why natural language presentation constrains the comprehension of mathematical relationships. (shrink)

The present volume intends an incursion into some key techniques of social work practice. Using arguments of social epistemology, the author introduces an overview of the case work and brings to attention important aspects of social work counselling. The reader is challenged to explore methodological aspects of counselling and is encouraged to practice the use of NLP techniques during the nondirective interview, which is able to lead to a change focused on the strengths of the client. Putting into relation the (...) main occupations used in assistance-work creates the complex context of inter and multidisciplinary approach of social work practice, recognizing the border aspect of the discipline. The whole approach proposed by the author is filtered by the ethical character of social intervention directed towards the promotion of individual rights and having as central concept the quality of life. This is not viewed as an abstract concept, but as a source of operational indicators relevant to individual existence. To validate social work as applied science, the author brings into focus epistemological arguments adapted to the requirements and demands of this field. (shrink)

Considerable evidence indicates that domain specific knowledge in the form of schemas is the primary factor distinguishing experts from novices in problem‐solving skill. Evidence that conventional problem‐solving activity is not effective in schema acquisition is also accumulating. It is suggested that a major reason for the ineffectiveness of problem solving as a learning device, is that the cognitive processes required by the two activities overlap insufficiently, and that conventional problem solving in the (...) form of means‐ends analysis requires a relatively large amount of cognitive processing capacity which is consequently unavailable for schema acquisition. A computational model and experimental evidence provide support for this contention. Theoretical and practical implications are discussed. (shrink)

We discuss the relation of the Theory of Event Coding (TEC) to a computational model of expert perception, CHREST, based on the chunking theory. TEC's status as a verbal theory leaves several questions unanswerable, such as the precise nature of internal representations used, or the degree of learning required to obtain a particular level of competence: CHREST may help answer such questions.

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)

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)