FACTOID # 8: Bookworms: Vermont has the highest number of high school teachers per capita and third highest number of librarians per capita.
 
 Home   Encyclopedia   Statistics   States A-Z   Flags   Maps   FAQ   About 
   
 
WHAT'S NEW
RELATED ARTICLES
People who viewed "Problem solving" also viewed:
 

SEARCH ALL

FACTS & STATISTICS    Advanced view

Search encyclopedia, statistics and forums:

 

 

(* = Graphable)

 

 


Encyclopedia > Problem solving

Problem solving forms part of thinking. Considered the most complex of all intellectual functions, problem solving has been defined as higher-order cognitive process that requires the modulation and control of more routine or fundamental skills (Goldstein & Levin, 1987). It occurs if an organism or an artificial intelligence system does not know how to proceed from a given state to a desired goal state. It is part of the larger problem process that includes problem finding and problem shaping. Personification of thought (Greek Εννοια) in Celsus Library in Ephesos, Turkey Thought or thinking is a mental process which allows beings to model the world, and so to deal with it effectively according to their goals, plans, ends and desires. ... Intelligence is a property of mind that encompasses many related mental abilities, such as the capacities to reason, plan, solve problems, think abstractly, comprehend ideas and language, and learn. ... Cognitive The scientific study of how people obtain, retrieve, store and manipulate information. ... A crab is an example of an organism. ... Hondas humanoid robot AI redirects here. ... System (from the Latin (systēma), and this from the Greek (sustēma)) is an assemblage of entity/objects, real or abstract, comprising a whole with each and every component/element interacting or related to at least one other component/element. ... Look up Problem in Wiktionary, the free dictionary. ... Problem finding means problem discovery. ... Problem shaping means revising a question so that the solution process can begin or continue. ...

Contents

Overview

The nature of human problem solving has been studied by psychologists over the past hundred years. There are several methods of studying problem solving, including; introspection, behaviorism, simulation and computer modeling, and experiment. A psychologist is a scientist and/or clinician who studies psychology, the systematic investigation of the human mind, including behavior and cognition. ... This article is about the psychological process of introspecting. ... Behaviorism is an approach to psychology based on the proposition that behaviour can be studied and explained scientifically without recourse to internal mental states. ... Wooden mechanical horse simulator during WWI. A simulation is an imitation of some real thing, state of affairs, or process. ... A computer simulation or a computer model is a computer program which attempts to simulate an abstract model of a particular system. ... In the scientific method, an experiment (Latin: ex-+-periri, of (or from) trying), is a set of actions and observations, performed in the context of solving a particular problem or question, to support or falsify a hypothesis or research concerning phenomena. ...


Beginning with the early experimental work of the Gestaltists in Germany (e.g. Duncker, 1935), and continuing through the 1960s and early 1970s, research on problem solving typically conducted relatively simple, laboratory tasks (e.g. Duncker's "X-ray" problem; Ewert & Lambert's 1932 "disk" problem, later known as Tower of Hanoi) that appeared novel to participants (e.g. Mayer, 1992). Various reasons account for the choice of simple novel tasks: they had clearly defined optimal solutions, they were solvable within a relatively short time frame, researchers could trace participants' problem-solving steps, and so on. The researchers made the underlying assumption, of course, that simple tasks such as the Tower of Hanoi captured the main properties of "real world" problems, and that the cognitive processes underlying participants' attempts to solve simple problems were representative of the processes engaged in when solving "real world" problems. Thus researchers used simple problems for reasons of convenience, and thought generalizations to more complex problems would become possible. Perhaps the best-known and most impressive example of this line of research remains the work by Newell and Simon (1972). Gestalt psychology (also Gestalt theory of the Berlin School) is a theory of mind and brain that proposes that the operational principle of the brain is holistic, parallel, and analog, with self-organizing tendencies. ... A model set of the Towers of Hanoi The Tower of Hanoi or Towers of Hanoi is a mathematical game or puzzle. ...


History

However, beginning in the 1970s, researchers became increasingly convinced that empirical findings and theoretical concepts derived from simple laboratory tasks did not necessarily generalize to more complex, real-life problems. Even worse, it appeared that the processes underlying creative problem solving in different domains differed from each other (Sternberg, 1995). These realizations have led to rather different responses in North America and in Europe. la merda c est koi ca Empirical is an adjective often used in conjunction with science, both the natural and social sciences, which means an observation or experiment based upon experience that is capable of being verified or disproved. ...


Headline text

USA and Canada

In North America, initiated by the work of Herbert Simon on learning by doing in semantically rich domains (e.g. Anzai & Simon, 1979; Bhaskar & Simon, 1977), researchers began to investigate problem solving separately in different natural knowledge domains - such as physics, writing, or chess playing - thus relinquishing their attempts to extract a global theory of problem solving (e.g. Sternberg & Frensch, 1991). Instead, these researchers have frequently focused on the development of problem solving within a certain domain, that is on the development of expertise (e.g. Anderson, Boyle & Reiser, 1985; Chase & Simon, 1973; Chi, Feltovich & Glaser, 1981). Herbert Alexander Simon (June 15, 1916 – February 9, 2001) was an American political scientist whose research ranged across the fields of cognitive psychology, computer science, public administration, economics, management, and philosophy of science and a professor, most notably, at Carnegie Mellon University. ... In general, semantics (from the Greek semantikos, or significant meaning, derived from sema, sign) is the study of meaning, in some sense of that term. ... Expertise is the property of a person (that is, expert) or of a system which delivers a desired result such as pertinent information or skill. ...


Areas that have attracted rather intensive attention in North America include such diverse fields as:

  • Reading (Stanovich & Cunningham, 1991)
  • Writing (Bryson, Bereiter, Scardamalia & Joram, 1991)
  • Calculation (Sokol & McCloskey, 1991)
  • Political decision making (Voss, Wolfe, Lawrence & Engle, 1991)
  • Managerial problem solving (Wagner, 1991)
  • Lawyers' reasoning (Amsel, Langer & Loutzenhiser, 1991)
  • Mechanical problem solving (Hegarty, 1991)
  • Problem solving in electronics (Lesgold & Lajoie, 1991)
  • Computer skills (Kay, 1991)
  • Game playing (Frensch & Sternberg, 1991)
  • Personal problem solving (Heppner & Krauskopf, 1987)
  • Mathematical problem solving (Polya, 1945; Schoenfeld, 1985)
  • Social problem solving (D'Zurilla & Goldfreid, 1971; D'Zurilla & Nezu, 1982)

Europe

In Europe, two main approaches have surfaced, one initiated by Donald Broadbent (1977; see Berry & Broadbent, 1995) in the United Kingdom and the other one by Dietrich Dörner (1975, 1985; see Dörner & Wearing, 1995) in Germany. The two approaches have in common an emphasis on relatively complex, semantically rich, computerized laboratory tasks, constructed to resemble real-life problems. The approaches differ somewhat in their theoretical goals and methodology, however. The tradition initiated by Broadbent emphasizes the distinction between cognitive problem-solving processes that operate under awareness versus outside of awareness, and typically employs mathematically well-defined computerized systems. The tradition initiated by Dörner, on the other hand, has an interest in the interplay of the cognitive, motivational, and social components of problem solving, and utilizes very complex computerized scenarios that contain up to 2,000 highly interconnected variables (e.g., Dörner, Kreuzig, Reither & Stäudel's 1983 LOHHAUSEN project; Ringelband, Misiak & Kluwe, 1990). Buchner (1995) describes the two traditions in detail. Donald E. Broadbent (Birmingham, 1926-1993) was an influential fucktard British experimental psychologist. ... Prof. ...


To sum up, researchers' realization that problem-solving processes differ across knowledge domains and across levels of expertise (e.g. Sternberg, 1995) and that, consequently, findings obtained in the laboratory cannot necessarily generalize to problem-solving situations outside the laboratory, has during the past two decades led to an emphasis on real-world problem solving. This emphasis has been expressed quite differently in North America and Europe, however. Whereas North American research has typically concentrated on studying problem solving in separate, natural knowledge domains, much of the European research has focused on novel, complex problems, and has been performed with computerized scenarios (see Funke, 1991, for an overview).


Characteristics of difficult problems

As elucidated by Dietrich Dörner and later expanded upon by Joachim Funke, difficult problems have some typical characteristics that can be summarized as follows: Prof. ...

  • Intransparency (lack of clarity of the situation)
    • commencement opacity
    • continuation opacity
  • Polytely (multiple goals)
    • inexpressiveness
    • opposition
    • transience
  • Complexity (large numbers of items, interrelations, and decisions)
    • enumerability
    • connectivity (hierarchy relation, communication relation, allocation relation)
    • heterogeneity
  • Dynamics (time considerations)
    • temporal constraints
    • temporal sensitivity
    • phase effects
    • dynamic unpredictability

The resolution of difficult problems requires a direct attack on each of these characteristics that are encountered. For the Computer Science term, see Computational complexity theory. ... Connectivity is the property of a device such as a PC, peripheral, PDA, mobile phone, robot, home appliance, or car that enables it to be connected, generally to a PC or another device without the need of a PC - autonomously. ... A heterogeneous compound, mixture, or other such object is one that consists of many different items. ... The word dynamics can refer to: in physics, a branch of mechanics; see dynamics (mechanics). ... Predictability refers to the degree that a correct prediction of a systems state can be made either qualitatively or quantitatively. ...


Some problem-solving techniques

  1. Hill-climbing strategy, (or - rephrased - gradient descent/ascent, difference reduction) - attempting at every step to move closer to the goal situation. The problem with this approach is that many challenges require that you seem to move away from the goal state in order to clearly see the solution.
  2. Means-end analysis, more effective than hill-climbing, requires the setting of subgoals based on the process of getting from the initial state to the goal state when solving a problem.
  3. Working backwards
  4. Trial-and-error
  5. Brainstorming
  6. Morphological box
  7. Method of focal objects
  8. Lateral thinking
  9. George Pólya's techniques in How to Solve It
  10. Research: study what others have written about the problem (and related problems). Maybe there's already a solution?
  11. Assumption reversal (write down your assumptions about the problem, and then reverse them all)
  12. Analogy: has a similar problem (possibly in a different field) been solved before?
  13. Hypothesis testing: assuming a possible explanation to the problem and trying to prove the assumption.
  14. Constraint examination: are you assuming a constraint which doesn't really exist?
  15. Take more time: time pressure can cause one to think in circles (the brain, unhelpfully, tends to be "pulled" towards a particular solution, or aspect of the problem)
  16. Incubation: input the details of a problem into your mind, then stop focusing on it. The subconscious mind will continue to work on the problem, and the solution might just "pop up" while you are doing something else
  17. Build (or write) one or more abstract models of the problem
  18. Try to prove that the problem cannot be solved. Where the proof breaks down can be your starting point for resolving it
  19. Get help from friends or online problem solving community (e.g. 3form)
  20. Root Cause Analysis
  21. Wind Tunnel: based on Socratic Method whereby you outrun your logical constraints to reach for new insights to a problem. Developed by Win Wenger.
  22. Rory O'Connor's Inner Vision Deck that combines Socratic Method with methaphorical thinking and assumption breaking.

These are also known as creativity techniques. Also, please see the thinking article. Gradient descent is an optimization algorithm that approaches a local minimum of a function by taking steps proportional to the negative of the gradient (or the approximate gradient) of the function at the current point. ... Trial and error (also known in computer science literature as generate and test and as guess and check when solving equations in elementary algebra) is a method of problem solving for obtaining knowledge, both propositional knowledge and know-how. ... Look up brainstorming in Wiktionary, the free dictionary. ... Morphological analysis was designed for multi-dimensional, non-quantifiable problems where causal modeling and simulation do not function well or at all. ... The technique of focal object for problem solving involves synthesizing the seemingly non-matching characteristics of different objects into something new. ... Lateral thinking is a term coined by Edward de Bono, a Maltese psychologist, physician, and writer, although it may have been an idea whose time was ready; the notion of lateral truth is discussed by Robert M. Pirsig in Zen and the Art of Motorcycle Maintenance from the same era... George Pólya (December 13, 1887 – September 7, 1985, in Hungarian Pólya György) was a Hungarian mathematician. ... George Pólyas 1945 book How to Solve It (ISBN 0691080976) is a small volume describing methods of problem-solving. ... Research is often described as an active, diligent, and systematic process of inquiry aimed at discovering, interpreting, and revising facts. ... Analogy is either the cognitive process of transferring or giving information from a particular subject (the analogue or source) to another particular subject (the target), or a linguistic expression corresponding to such a process. ... One may be faced with the problem of making a definite decision with respect to an uncertain hypothesis which is known only through its observable consequences. ... In evolutionary computation, a human-based genetic algorithm (HBGA) is a genetic algorithm that allows humans to contribute their innovative solutions to the evolutionary process. ... Root cause analysis (RCA) is a term used to denote a class of problem solving methods aimed at identifying the root causes of problems or events. ... Socratic Method (or method of elenchos or Socratic debate) is a dialectic method of inquiry, largely applied to the examination of key moral concepts and first described by Plato in the Socratic Dialogues. ... To meet Wikipedias quality standards, this article or section may require cleanup. ... Socratic Method (or method of elenchos or Socratic debate) is a dialectic method of inquiry, largely applied to the examination of key moral concepts and first described by Plato in the Socratic Dialogues. ... Creativity techniques are heuristic methods to facilitate creativity in a person or a group of people. ... Thought or thinking is a mental process which allows beings to model the world, and so to deal with it effectively according to their goals, plans, ends and desires. ...


See also

Abduction, or abductive reasoning, is the process of reasoning to the best explanations. ... Analogy is either the cognitive process of transferring or giving information from a particular subject (the analogue or source) to another particular subject (the target), or a linguistic expression corresponding to such a process. ... Hondas humanoid robot AI redirects here. ... Look up brainstorming in Wiktionary, the free dictionary. ... Look up Common sense in Wiktionary, the free dictionary. ... Commonsense reasoning is the branch of Artificial intelligence concerned with replicating human thinking. ... Creative Problem Solving begins when knowledge and simply thinking about a problem fails. ... Cyc is an artificial intelligence project that attempts to assemble a comprehensive ontology and database of everyday common sense knowledge, with the goal of enabling AI applications to perform human-like reasoning. ... To meet Wikipedias quality standards, this article or section may require cleanup. ... Educational psychology is the study of how humans learn in educational settings, the effectiveness of educational interventions, the psychology of teaching, and the social psychology of schools as organizations. ... The executive system is a theorised cognitive system in psychology that controls and manages other cognitive processes. ... General Problem Solver (GPS) was a computer program created in 1957 by Herbert Simon and Allen Newell to build a universal problem solver machine. ... Induction or inductive reasoning, sometimes called inductive logic, is the process of reasoning in which the premises of an argument are believed to support the conclusion but do not ensure it. ... Intelligence amplification (IA) refers to the process of enhancing human intelligence through the use of technology. ... Wikipedia does not yet have an article with this exact name. ... Kepner-Tregoe Inc. ... Alan M. Lesgold is an educational psychologist who has made notable contributions to the cognitive science of learning and its application to instructional technology. ... Allen Newell (March 19, 1927 - July 19, 1992) was a researcher in computer science and cognitive psychology at the RAND corporation and at Carnegie-Mellon’s School of Computer Science. ... Herbert Alexander Simon (June 15, 1916 – February 9, 2001) was an American political scientist whose research ranged across the fields of cognitive psychology, computer science, public administration, economics, management, and philosophy of science and a professor, most notably, at Carnegie Mellon University. ... Soar (also known as SOAR) is a symbolic cognitive architecture, created by John Laird, Allen Newell, and Paul Rosenbloom at Carnegie Mellon University. ... TRIZ (pronounced [triz]) is a Russian acronym for Teoriya Resheniya Izobretatelskikh Zadatch (Теория решения изобретательских задач), a Theory of solving inventive problems or Theory of inventive problems solving (TIPS)(less known as Theory of Solving Inventors Problems), developed by Genrich Altshuller and his colleagues since 1946. ... Troubleshooting is a form of problem solving. ... The concept of wicked problems was originally proposed by H. J. Rittel (a pioneering theorist of design and planning, and late professor at the University of California, Berkeley) and M. Webber in a seminal treatise for social planning. ...

External links

References

  • Amsel, E., Langer, R., & Loutzenhiser, L. (1991). Do lawyers reason differently from psychologists? A comparative design for studying expertise. In R. J. Sternberg & P. A. Frensch (Eds.), Complex problem solving: Principles and mechanisms (pp. 223-250). Hillsdale, NJ: Lawrence Erlbaum Associates.
  • Anderson, J. R., Boyle, C. B., & Reiser, B. J. (1985). Intelligent tutoring systems. Science, 228, 456-462.
  • Anzai, K., & Simon, H. A. (1979). The theory of learning by doing. Psychological Review, 86, 124-140.
  • Beckmann, J. F., & Guthke, J. (1995). Complex problem solving, intelligence, and learning ability. In P. A. Frensch & J. Funke (Eds.), Complex problem solving: The European Perspective (pp. 177-200). Hillsdale, NJ: Lawrence Erlbaum Associates.
  • Berry, D. C., & Broadbent, D. E. (1995). Implicit learning in the control of complex systems: A reconsideration of some of the earlier claims. In P.A. Frensch & J. Funke (Eds.), Complex problem solving: The European Perspective (pp. 131-150). Hillsdale, NJ: Lawrence Erlbaum Associates.
  • Bhaskar, R., & Simon, H. A. (1977). Problem solving in semantically rich domains: An example from engineering thermodynamics. Cognitive Science, 1, 193-215.
  • Brehmer, B. (1995). Feedback delays in dynamic decision making. In P. A. Frensch & J. Funke (Eds.), Complex problem solving: The European Perspective (pp. 103-130). Hillsdale, NJ: Lawrence Erlbaum Associates.
  • Brehmer, B., & Dörner, D. (1993). Experiments with computer-simulated microworlds: Escaping both the narrow straits of the laboratory and the deep blue sea of the field study. Computers in Human Behavior, 9, 171-184.
  • Broadbent, D. E. (1977). Levels, hierarchies, and the locus of control. Quarterly Journal of Experimental Psychology, 29, 181-201.
  • Bryson, M., Bereiter, C., Scardamalia, M., & Joram, E. (1991). Going beyond the problem as given: Problem solving in expert and novice writers. In R. J. Sternberg & P. A. Frensch (Eds.), Complex problem solving: Principles and mechanisms (pp. 61-84). Hillsdale, NJ: Lawrence Erlbaum Associates.
  • Buchner, A. (1995). Theories of complex problem solving. In P. A. Frensch & J. Funke (Eds.), Complex problem solving: The European Perspective (pp. 27-63). Hillsdale, NJ: Lawrence Erlbaum Associates.
  • Buchner, A., Funke, J., & Berry, D. C. (1995). Negative correlations between control performance and verbalizable knowledge: Indicators for implicit learning in process control tasks? Quarterly Journal of Experimental Psychology, 48A, 166-187.
  • Chase, W. G., & Simon, H. A. (1973). Perception in chess. Cognitive Psychology, 4, 55-81.
  • Chi, M. T. H., Feltovich, P. J., & Glaser, R. (1981). Categorization and representation of physics problems by experts and novices. Cognitive Science, 5, 121-152.
  • Dörner, D. (1975). Wie Menschen eine Welt verbessern wollten [How people wanted to improve the world]. Bild der Wissenschaft, 12, 48-53.
  • Dörner, D. (1985). Verhalten, Denken und Emotionen [Behavior, thinking, and emotions]. In L. H. Eckensberger & E. D. Lantermann (Eds.), Emotion und Reflexivität (pp. 157-181). München, Germany: Urban & Schwarzenberg.
  • Dörner, D. (1992). Über die Philosophie der Verwendung von Mikrowelten oder "Computerszenarios" in der psychologischen Forschung [On the proper use of microworlds or "computer scenarios" in psychological research]. In H. Gundlach (Ed.), Psychologische Forschung und Methode: Das Versprechen des Experiments. Festschrift für Werner Traxel (pp. 53-87). Passau, Germany: Passavia-Universitäts-Verlag.
  • Dörner, D., Kreuzig, H. W., Reither, F., & Stäudel, T. (Eds.). (1983). Lohhausen. Vom Umgang mit Unbestimmtheit und Komplexität [Lohhausen. On dealing with uncertainty and complexity]. Bern, Switzerland: Hans Huber.
  • Dörner, D., & Wearing, A. (1995). Complex problem solving: Toward a (computer-simulated) theory. In P. A. Frensch & J. Funke (Eds.), Complex problem solving: The European Perspective (pp. 65-99). Hillsdale, NJ: Lawrence Erlbaum Associates.
  • Duncker, K. (1935). Zur Psychologie des produktiven Denkens [The psychology of productive thinking]. Berlin: Julius Springer.
  • Ewert, P. H., & Lambert, J. F. (1932). Part II: The effect of verbal instructions upon the formation of a concept. Journal of General Psychology, 6, 400-411.
  • Eyferth, K., Schömann, M., & Widowski, D. (1986). Der Umgang von Psychologen mit Komplexität [On how psychologists deal with complexity]. Sprache & Kognition, 5, 11-26.
  • Frensch, P. A., & Funke, J. (Eds.). (1995). Complex problem solving: The European Perspective. Hillsdale, NJ: Lawrence Erlbaum Associates.
  • Frensch, P. A., & Sternberg, R. J. (1991). Skill-related differences in game playing. In R. J. Sternberg & P. A. Frensch (Eds.), Complex problem solving: Principles and mechanisms (pp. 343-381). Hillsdale, NJ: Lawrence Erlbaum Associates.
  • Funke, J. (1991). Solving complex problems: Human identification and control of complex systems. In R. J. Sternberg & P. A. Frensch (Eds.), Complex problem solving: Principles and mechanisms (pp. 185-222). Hillsdale, NJ: Lawrence Erlbaum Associates.
  • Funke, J. (1993). Microworlds based on linear equation systems: A new approach to complex problem solving and experimental results. In G. Strube & K.-F. Wender (Eds.), The cognitive psychology of knowledge (pp. 313-330). Amsterdam: Elsevier Science Publishers.
  • Funke, J. (1995). Experimental research on complex problem solving. In P. A. Frensch & J. Funke (Eds.), Complex problem solving: The European Perspective (pp. 243-268). Hillsdale, NJ: Lawrence Erlbaum Associates.
  • Funke, U. (1995). Complex problem solving in personnel selection and training. In P. A. Frensch & J. Funke (Eds.), Complex problem solving: The European Perspective (pp. 219-240). Hillsdale, NJ: Lawrence Erlbaum Associates.
  • Goldstein F. C., & Levin H. S. (1987). Disorders of reasoning and problem-solving ability. In M. Meier, A. Benton, & L. Diller (Eds.), Neuropsychological rehabilitation. London: Taylor & Francis Group.
  • Groner, M., Groner, R., & Bischof, W. F. (1983). Approaches to heuristics: A historical review. In R. Groner, M. Groner, & W. F. Bischof (Eds.), Methods of heuristics (pp. 1-18). Hillsdale, NJ: Lawrence Erlbaum Associates.
  • Hayes, J. (1980). The complete problem solver. Philadelphia: The Franklin Institute Press.
  • Hegarty, M. (1991). Knowledge and processes in mechanical problem solving. In R. J. Sternberg & P. A. Frensch (Eds.), Complex problem solving: Principles and mechanisms (pp. 253-285). Hillsdale, NJ: Lawrence Erlbaum Associates.
  • Heppner, P. P., & Krauskopf, C. J. (1987). An information-processing approach to personal problem solving. The Counseling Psychologist, 15, 371-447.
  • Huber, O. (1995). Complex problem solving as multi stage decision making. In P. A. Frensch & J. Funke (Eds.), Complex problem solving: The European Perspective (pp. 151-173). Hillsdale, NJ: Lawrence Erlbaum Associates.
  • Hübner, R. (1989). Methoden zur Analyse und Konstruktion von Aufgaben zur kognitiven Steuerung dynamischer Systeme [Methods for the analysis and construction of dynamic system control tasks]. Zeitschrift für Experimentelle und Angewandte Psychologie, 36, 221-238.
  • Hunt, E. (1991). Some comments on the study of complexity. In R. J. Sternberg, & P. A. Frensch (Eds.), Complex problem solving: Principles and mechanisms (pp. 383-395). Hillsdale, NJ: Lawrence Erlbaum Associates.
  • Hussy, W. (1985). Komplexes Problemlösen - Eine Sackgasse? [Complex problem solving - a dead end?]. Zeitschrift für Experimentelle und Angewandte Psychologie, 32, 55-77.
  • Kay, D. S. (1991). Computer interaction: Debugging the problems. In R. J. Sternberg & P. A. Frensch (Eds.), Complex problem solving: Principles and mechanisms (pp. 317-340). Hillsdale, NJ: Lawrence Erlbaum Associates.
  • Kluwe, R. H. (1993). Knowledge and performance in complex problem solving. In G. Strube & K.-F. Wender (Eds.), The cognitive psychology of knowledge (pp. 401-423). Amsterdam: Elsevier Science Publishers.
  • Kluwe, R. H. (1995). Single case studies and models of complex problem solving. In P. A. Frensch & J. Funke (Eds.), Complex problem solving: The European Perspective (pp. 269-291). Hillsdale, NJ: Lawrence Erlbaum Associates.
  • Kolb, S., Petzing, F., & Stumpf, S. (1992). Komplexes Problemlösen: Bestimmung der Problemlösegüte von Probanden mittels Verfahren des Operations Research ? ein interdisziplinärer Ansatz [Complex problem solving: determining the quality of human problem solving by operations research tools - an interdisciplinary approach]. Sprache & Kognition, 11, 115-128.
  • Krems, J. F. (1995). Cognitive flexibility and complex problem solving. In P. A. Frensch & J. Funke (Eds.), Complex problem solving: The European Perspective (pp. 201-218). Hillsdale, NJ: Lawrence Erlbaum Associates.
  • Lesgold, A., & Lajoie, S. (1991). Complex problem solving in electronics. In R. J. Sternberg & P. A. Frensch (Eds.), Complex problem solving: Principles and mechanisms (pp. 287-316). Hillsdale, NJ: Lawrence Erlbaum Associates.
  • Mayer, R. E. (1992). Thinking, problem solving, cognition. Second edition. New York: W. H. Freeman and Company.
  • Müller, H. (1993). Komplexes Problemlösen: Reliabilität und Wissen [Complex problem solving: Reliability and knowledge]. Bonn, Germany: Holos.
  • Newell, A., & Simon, H. A. (1972). Human problem solving. Englewood Cliffs, NJ: Prentice-Hall.
  • Paradies, M.W., & Unger, L. W. (2000). TapRooT - The System for Root Cause Analysis, Problem Investigation, and Proactive Improvement. Knoxville, TN: System Improvements.
  • Putz-Osterloh, W. (1993). Strategies for knowledge acquisition and transfer of knowledge in dynamic tasks. In G. Strube & K.-F. Wender (Eds.), The cognitive psychology of knowledge (pp. 331-350). Amsterdam: Elsevier Science Publishers.
  • Riefer, D.M., & Batchelder, W.H. (1988). Multinomial modeling and the measurement of cognitive processes. Psychological Review, 95, 318-339.
  • Ringelband, O. J., Misiak, C., & Kluwe, R. H. (1990). Mental models and strategies in the control of a complex system. In D. Ackermann, & M. J. Tauber (Eds.), Mental models and human-computer interaction (Vol. 1, pp. 151-164). Amsterdam: Elsevier Science Publishers.
  • Schaub, H. (1993). Modellierung der Handlungsorganisation. Bern, Switzerland: Hans Huber.
  • Sokol, S. M., & McCloskey, M. (1991). Cognitive mechanisms in calculation. In R. J. Sternberg & P. A. Frensch (Eds.), Complex problem solving: Principles and mechanisms (pp. 85-116). Hillsdale, NJ: Lawrence Erlbaum Associates.
  • Stanovich, K. E., & Cunningham, A. E. (1991). Reading as constrained reasoning. In R. J. Sternberg & P. A. Frensch (Eds.), Complex problem solving: Principles and mechanisms (pp. 3-60). Hillsdale, NJ: Lawrence Erlbaum Associates.
  • Sternberg, R. J. (1995). Conceptions of expertise in complex problem solving: A comparison of alternative conceptions. In P. A. Frensch & J. Funke (Eds.), Complex problem solving: The European Perspective (pp. 295-321). Hillsdale, NJ: Lawrence Erlbaum Associates.
  • Sternberg, R. J., & Frensch, P. A. (Eds.). (1991). Complex problem solving: Principles and mechanisms. Hillsdale, NJ: Lawrence Erlbaum Associates.
  • Strauß, B. (1993). Konfundierungen beim Komplexen Problemlösen. Zum Einfluß des Anteils der richtigen Lösungen (ArL) auf das Problemlöseverhalten in komplexen Situationen [Confoundations in complex problem solving. On the influence of the degree of correct solutions on problem solving in complex situations]. Bonn, Germany: Holos.
  • Strohschneider, S. (1991). Kein System von Systemen! Kommentar zu dem Aufsatz "Systemmerkmale als Determinanten des Umgangs mit dynamischen Systemen" von Joachim Funke [No system of systems! Reply to the paper "System features as determinants of behavior in dynamic task environments" by Joachim Funke]. Sprache & Kognition, 10, 109-113.
  • Van Lehn, K. (1989). Problem solving and cognitive skill acquisition. In M. I. Posner (Ed.), Foundations of cognitive science (pp. 527-579). Cambridge, MA: MIT Press.
  • Voss, J. F., Wolfe, C. R., Lawrence, J. A., & Engle, R. A. (1991). From representation to decision: An analysis of problem solving in international relations. In R. J. Sternberg & P. A. Frensch (Eds.), Complex problem solving: Principles and mechanisms (pp. 119-158). Hillsdale, NJ: Lawrence Erlbaum Associates.
  • Wagner, R. K. (1991). Managerial problem solving. In R. J. Sternberg & P. A. Frensch (Eds.), Complex problem solving: Principles and mechanisms (pp. 159-183). Hillsdale, NJ: Lawrence Erlbaum Associates.
  • Wisconsin Educational Media Association. (1993). "Information literacy: A position paper on information problem-solving." Madison, WI: WEMA Publications. (ED 376 817). (Portions adapted from Michigan State Board of Education's Position Paper on Information Processing Skills, 1992).

  Results from FactBites:
 
Mathematics Through Problem Solving (2275 words)
Problem solving is an important component of mathematics education because it is the single vehicle which seems to be able to achieve at school level all three of the values of mathematics listed at the outset of this article: functional, logical and aesthetic.
Cockcroft (1982) also advocated problem solving as a means of developing mathematical thinking as a tool for daily living, saying that problem-solving ability lies 'at the heart of mathematics' (p.73) because it is the means by which mathematics can be applied to a variety of unfamiliar situations.
One of the aims of teaching through problem solving is to encourage students to refine and build onto their own processes over a period of time as their experiences allow them to discard some ideas and become aware of further possibilities (Carpenter, 1989).
  More results at FactBites »

 
 

COMMENTARY     


Share your thoughts, questions and commentary here
Your name
Your comments

Want to know more?
Search encyclopedia, statistics and forums:

 


Press Releases |  Feeds | Contact
The Wikipedia article included on this page is licensed under the GFDL.
Images may be subject to relevant owners' copyright.
All other elements are (c) copyright NationMaster.com 2003-5. All Rights Reserved.
Usage implies agreement with terms, 1022, m