Skip to main content Accessibility help

We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.

Close cookie message
×
Hostname: page-component-7479d7b7d-68ccn Total loading time: 0 Render date: 2024-07-12T22:29:32.722Z Has data issue: false hasContentIssue false

9 - Complex Problem Solving and Intelligence: Empirical Relation and Causal Direction

Published online by Cambridge University Press:  23 November 2009

By
Dorit Wenke ,
Peter A. Frensch  and
Joachim Funke
Edited by
Robert J. Sternberg  and
Jean E. Pretz
Robert J. Sternberg
Affiliation:
Yale University, Connecticut
Jean E. Pretz
Affiliation:
Yale University, Connecticut
Get access

Summary

INTRODUCTION

The breadth of human problem solving is truly striking. On the one hand, human problem solving makes possible the most wondrous achievements, such as “an 800-seat airliner with wings that blend smoothly into the fuselage instead of protruding from its sides that is scheduled to be in the air by 2006” (AP news from February 9, 2001). Yet, on the other hand, errors in problem solving can lead to catastrophic and near-catastrophic disasters, such as, for instance, the nuclear reactor accident at Three Mile Island, Pennsylvania, in 1979. Whatever “problem solving” is, and scientists disagree vehemently on the proper meaning of the term, there can be little doubt that it has shaped human culture to an extent that is almost unrivaled by any other human ability.

From the inception of the concept of “intelligence,” the ability to solve problems has featured prominently in virtually every definition of human intelligence (e.g., Sternberg & Berg, 1986). In addition, intelligence has often been viewed as one of the best predictors of problem-solving ability (e.g., Putz-Osterloh, 1981; Putz-Osterloh & Lüer, 1981). Thus, whatever the causal relation between the two concepts, prevailing theoretical positions strongly suggest that intelligence and problem solving are related. In this chapter we concentrate on complex rather than on simple problem solving. Our main goal is to review the extent to which the ability to solve complex problems is indeed tied, empirically, to intelligence and to discuss which causal direction holds between the two concepts.

Type
Chapter
Information
Cognition and Intelligence
Identifying the Mechanisms of the Mind
 , pp. 160 - 187
Publisher: Cambridge University Press
Print publication year: 2004

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Amthauer, R., Brocke, B., Liepmann, D., & Beauducel, A. (1973). Intelligence Structure Test (IST 70). Göttingen: Hogrefe
Anderson, J. R., Boyle, C. B., & Reiser, B. J. (1985). Intelligent tutoring systems. Science, 228, 456–462CrossRefGoogle ScholarPubMed
Anderson, M. (1998). Individual differences in intelligence. In K. Kirsner, C. Speelman, M. Maybery, A. O'Brien-Malone, M. Anderson, & C. MacLeod (Eds.), Implicit and explicit processes (pp. 171–185). Mahwah, NJ: Erlbaum
Anzai, K., & Simon, H. A. (1979). The theory of learning by doing. Psychological Review, 86, 124–140CrossRefGoogle ScholarPubMed
Beckmann. (1995). Lernen und komplexes Problemlösen. Ein Beitrag zur Validierung von Lerntests [Learning and problem solving. A contribution to validate learning potential tests]. Bonn: Holos
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. 3–25). Hillsdale, NJ: Erlbaum
Berry, D. C., & Broadbent, D. E. (1984). On the relationship between task performance and associated verbalizable knowledge. Quarterly Journal of Experimental Psychology, 36A, 209–231CrossRefGoogle Scholar
Berry, D. C., & Broadbent, D. E. (1987). The combination of explicit and implicit learning processes in task control. Psychological research, 49, 7–15CrossRefGoogle Scholar
Berry, D. C., & Broadbent, D. E. (1988). Interactive tasks and the implicit–explicit distinction. British Journal of Psychology, 79, 251–272CrossRefGoogle Scholar
Berry, D. C., & Broadbent, D. E. (1995). Implicit learning in the control of complex systems. In P. A. Frensch & J. Funke (Eds.), Complex problem solving. The European perspective (pp. 3–25). Hillsdale, NJ: Erlbaum
Bhaskar, R., & Simon, H. A. (1977). Problem solving in semantically rich domains: An example from engineering thermodynamics. Cognitive Science, 1, 193–215CrossRefGoogle Scholar
Broadbent, D. E. (1977). Levels, hierarchies, and the locus of control. Quarterly Journal of Experimental Psychology, 29, 181–201CrossRefGoogle Scholar
Buchner, A. (1995). Basic topics and approaches to the study of complex problem solving. In P. A. Frensch & J. Funke (Eds.), Complex problem solving. The European perspective (pp. 27–63). Hillsdale, NJ: Erlbaum
Buchner, A. (1999). Komplexes Problemlösen vor dem Hintergrund der Theorie finiter Automaten [Complex problem solving viewed from the theory of finite state automata]. Psychologische Rundschau, 50, 206–212CrossRefGoogle Scholar
Buchner, A., Funke, J., & Berry, D. (1995). Negative correlations between control performance and verbalizable knowledge: Indicators for implicit learning in process control tasks? Quarterly Journal of Experimental Psychology, 48A, 166–187CrossRefGoogle Scholar
Cattell, R. B., & Weiss, R. H. (1980). Culture Fair Intelligence Test, Scale 3 (CFT3). Göttingen: Hogrefe
Ceci, S. J., & Liker, J. K. (1986a). A day at the races: A study of IQ, expertise, and cognitive complexity. Journal of Experimental Psychology: General, 115, 255–266CrossRefGoogle Scholar
Ceci, S. J., & Liker, J. K. (1986b). Academic and nonacademic intelligence: An experimental separation. In R. J. Sternberg & R. K. Wagner (Eds.), Practical intelligence (pp. 119–142). Cambridge, UK: Cambridge University Press
Ceci, S. J., & Liker, J. K. (1988). Stalking the IQ–expertise relation: When critics go fishing. Journal of Experimental Psychology: General, 117, 96–100CrossRefGoogle Scholar
Ceci, S. J., & Ruiz, A. (1992). The role of general ability in cognitive complexity: A case study of expertise. In R. R. Hoffmann (Ed.), The psychology of expertise: Cognitive research and empirical AI (pp. 218–230). New York: SpringerCrossRef
Ceci, S. J., & Ruiz, A. (1993). Transfer, abstractness, and intelligence. In D. K. Detterman & R. J. Sternberg (Eds.), Transfer on trial: Intelligence, cognition, and instruction (pp. 168–191). Norwood, NJ: Ablex
Chase, W. G., & Simon, H. A. (1973). Perception in chess. Cognitive Psychology, 4, 55–81CrossRefGoogle Scholar
Chi, M. T. H., Feltovich, P. J., & Glaser, R. (1981). Categorization and representation of physics problems by experts and novices. Cognitive Science, 5, 121–152CrossRefGoogle Scholar
Detterman, D. K., & Spry, K. M. (1988). Is it smart to play the horses? Comment on “A day at the races: A study of IQ, expertise, and cognitive complexity” (Ceci & Liker, 1986). Journal of Experimental Psychology: General, 117, 91–95CrossRefGoogle Scholar
Dienes, Z., & Fahey, R. (1995). The role of specific instances in controlling a dynamic system. Journal of Experimental Psychology: Learning, Memory, & Cognition, 21, 848–862Google Scholar
Dienes, Z., & Fahey, R. (1998). The role of implicit memory in controlling a dynamic system. Quarterly Journal of Experimental Psychology, 51A, 593–614CrossRefGoogle Scholar
Dörner, D. (1975). Wie Menschen eine Welt verbessern wollten [How people wanted to improve a world]. Bild der Wissenschaft, 12, 48–53Google Scholar
Dörner, D. (1980). On the difficulty people have in dealing with complexity. Simulation & Games, 11, 87–106CrossRefGoogle Scholar
Dörner, D. (1986). Diagnostik der operativen Intelligenz [Assessment of operative intelligence]. Diagnostica, 32, 290–308Google Scholar
Dörner, D., & Kreuzig, H. W. (1983). Problemlösefähigkeit und Intelligenz [Problem solving and intelligence]. Psychologische Rundschau, 34, 185–192Google Scholar
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: Erlbaum
Dörner, D., Kreuzig, H. W., Reither, F., & Stäudel, T. (1983). Lohhausen. Vom Umgang mit Unbestimmtheit und Komplexität [Lohhausen. On dealing with uncertainty and complexity]. Bern, Switzerland: Hans Huber
Duncker, K. (1935/1974). Zur Psychologie des produktiven Denkens [On productive thinking]. Berlin: Julius Springer
Ellis, N. R., & Allison, P. (1988). Memory for frequency of occurrence in retarded and nonretarded persons. Intelligence, 12, 61–75CrossRefGoogle Scholar
Ellis, N. R., Katz, E., & Williams, J. E. (1987). Developmental aspects of memory for spatial location. Journal of Experimental Child Psychology, 44, 401–412CrossRefGoogle ScholarPubMed
Ewert, P. H., & Lambert, J. F. (1932). The effect of verbal instructions upon the formation of a concept. Journal of General Psychology, 6, 400–413CrossRefGoogle Scholar
Fletcher, J., Maybery, M. T., & Bennett, S. (2000). Implicit learning differences: A question of developmental level? Journal of Experimental Psychology: Learning, Memory, and Cognition, 26, 246–252Google ScholarPubMed
Frensch, P. A. (1998). One concept, multiple meanings. On how to define the concept of implicit learning. In M. A. Stadler & P. A. Frensch (Eds.), Handbook of implicit learning. Thousand Oaks: Sage
Frensch, P. A., & Funke, J. (1995). Definitions, traditions, and a general framework for understanding complex problem solving. In P. A. Frensch & J. Funke (Eds.), Complex problem solving. The European perspective (pp. 3–25). Hillsdale, NJ: Erlbaum
Frensch, P. A., & Rünger, D. (2003). Implicit learning. Current Directions in Psychological Science, 12, 13–18CrossRefGoogle Scholar
Funke, J. (1983). Einige Bermerkungen zu Problemen der Problemlöseforschung oder: Ist Testintelligenz doch ein Prädiktor [Some remarks on the problems of problem solving research or: Does test intelligence predict control performance?]. Diagnostica, 29, 283–302Google Scholar
Funke, J. (1984). Diagnose der westdeutschen Problemlöseforschung in Form einiger Thesen [Assessment of West German problem solving research]. Sprache & Kognition, 3, 159–172Google Scholar
Funke, J. (1991). Solving complex problems: Exploration and control of complex systems. In R. J. Sternberg & P. A. Frensch (Eds.), Complex problem solving: Principles and mechanisms (pp. 185–222). Hillsdale, NJ: Erlbaum
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: Erlbaum
Funke, J. (2001). Dynamic systems as tools for analysing human judgement. Thinking and Reasoning, 7, 69–89CrossRefGoogle Scholar
Geddes, B. W., & Stevenson, R. J. (1997). Explicit learning of a dynamic system with a non-salient pattern. Quarterly Journal of Experimental Psychology, 50A, 742–765CrossRefGoogle Scholar
Green, R. E., & Shanks, D. R. (1993). On the existence of independent explicit and implicit learning systems: An examination of some evidence. Memory & Cognition, 21, 304–317CrossRefGoogle ScholarPubMed
Greve, W. (2001). Traps and gaps in action explanation. Theoretical problems of a psychology of human action. Psychological Review, 108, 435–451CrossRefGoogle ScholarPubMed
Guthke, J., Jäger, C., & Schmidt, I. (1983). LTS: Learning Test Battery “Reasoning”. Berlin: Humboldt-Universität zu Berlin, Institut für Psychologie
Hayes, N. A., & Broadbent, D. E. (1988). Two modes of learning for interactive tasks. Cognition, 28, 249–276CrossRefGoogle ScholarPubMed
Hesse, F. W. (1982). Effekte des semantischen Kontexts auf die Bearbeitung komplexer Probleme [Effects of semantic context on problem solving]. Zeitschrift für Experimentelle und Angewandte Psychologie, 29, 62–91Google Scholar
Hörmann, J. J., & Thomas, M. (1989). Zum Zusammenhang zwischen Intelligenz und komplesem Problemlösen [On the relationship between intelligence and complex problem solving]. Sprache & Kognition, 8, 23–31Google Scholar
Howe, M. J. (1988). Intelligence as an explanation. British Journal of Psychology, 79, 349–360CrossRefGoogle Scholar
Howe, M. J. A. (1996). Concepts of ability. In I. Dennis & P. Tapsfield (Eds.), Human abilities. Their nature and their measurement (pp. 39–48). Mahwah, NJ: Erlbaum
Hussy, W. (1989). Intelligenz und komplexes Problemlösen [Intelligence and complex problem solving]. Diagnostica, 35, 1–16Google Scholar
Hussy, W. (1991). Problemlösen und Verarbeitungskapazität [Complex problem solving and processing capacity]. Sprache & Kognition, 10, 208–220Google Scholar
Jäger, A. O. (1982). Mehrmodale Klassifikation von Intelligenzleistungen [Multimodal classification of intelligent performance]. Diagnostica, 28, 195–225Google Scholar
Jäger, A. O., Süß, H.-M., & Beauducel, A. (1997). Berliner Intelligenzstrukturtest. BIS-Test, Form 4 [Berlin Intelligence Structure Test, Manual]. Göttingen: Hogrefe
Kersting, M. (1999). Diagnostik und Personalauswahl mit computergestützten Problemlöseszenarien? Zur Kriteriumsvalidität von Problemlöseszenarien und Intelligenztests [Assessment and personnel selection with computer simulated problem-solving scenarios? On the validity of problem-solving scenarios and intelligence tests]. Göttingen: Hogrefe
Kersting, M., & Süß, H.-M. (1995). Kontentvalide Wissensdiagnostik und Problemlösen: Zur Entwicklung, testtheoretischen Begründung und empirischen Bewährung eines problemspezifischen Diagnoseverfahrens [Content-validity of knowledge assessment and problem-solving: Development, psychometric foundation, and empirical assessment of a problem-specific assessment instrument]. Zeitschrift für Pädagogische Psychologie, 9, 83–93Google Scholar
Kluwe, R. H., Misiak, C., & Haider, H. (1991a). Systems and performance in intelligence tests. In H. Rowe (Ed.), Intelligence: Reconceptualization and measurement (pp. 227–244). Hillsdale, NJ: Erlbaum
Kluwe, R. H., Schilde, A., Fischer, C., & Oellerer, N. (1991b). Problemlöseleistungen beim Umgang mit komplexen Systemen und Intelligenz [Problem solving performance when interacting with complex systems and intelligence]. Diagnostica, 37, 291–313Google Scholar
Kray, J., & Frensch, P. A. (2001). A view from cognitive psychology: “g” — (G)host in the correlation matrix? In R. J. Sternberg & E. E. Grigorenko (Eds.), The general factor of intelligence: Fact or fiction? Hillsdale, NJ: Erlbaum
Maybery, M., Taylor, M., & O'Brien-Malone, A. (1995). Implicit learning: Sensitive to age but not IQ. Australian Journal of Psychology, 47, 8–17CrossRefGoogle Scholar
Mayer, R. E. (1992). Thinking, problem solving, cognition. Second ed. New York: Freeman
McGeorge, P., Crawford, J. R., & Kelly, S. W. (1997). The relationships between psychometric intelligence and learning in an explicit and an implicit task. Journal of Experimental Psychology: Learning, Memory, & Cognition, 23, 239–245Google Scholar
Müller, H. (1993). Komplexes Problemlösen: Reliabilität und Wissen [Complex problem solving: Reliability and knowledge]. Bonn: Holos
Newell, A., & Simon, H. A. (1972). Human information processing. Englewood Cliffs, NJ: Prentice-Hall
Nissen, M. J., & Bullemer, P. (1987). Attentional requirements of learning: Evidence from performance measures. Cognitive Psychology, 19, 1–32CrossRefGoogle Scholar
Putz-Osterloh, W. (1981). Über die Beziehung zwischen Testintelligenz und Problemlöseerfolg [On the relationship between test intelligence and success in problem solving]. Zeitschrift für Psychologie, 189, 79–100Google Scholar
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: ElsevierCrossRef
Putz-Osterloh, W., & Haupts, I. (1989). Zur Reliabilität und Validität computergestützter Diagnostik komplexer Organisations-und Entscheidungsstrategien [On the reliability and validity of computer-based assessment of complex organizational and decision strategies]. Untersuchungen des Psychologischen Dienstes der Bundeswehr, 24, 5–48Google Scholar
Putz-Osterloh, W., & Lüer, G. (1981). Über die Vorhersagbarkeit komplexer Problemlöseleistungen durch Ergebnisse in einem Intelligenztest [On the predictability of complex problem solving performance by intelligence test scores]. Zeitschrift für Experimentelle und Angewandte Psychologie, 28, 309–334Google Scholar
Raven, J. C., Court, J. & Raven, J., Jr. (1980). Advanced Progressive Matrices (APM). Weinheim: Beltz
Reber, A. S. (1967). Implicit learning of artificial grammars. Journal of Verbal Learning and Verbal Behavior, 77, 317–327Google Scholar
Reber, A. S. (1969). Transfer of syntactic structure in synthetic languages. Journal of Experimental Psychology, 81, 115–119CrossRefGoogle Scholar
Reber, A. S. (1976). Implicit learning and tacit knowledge. Journal of Experimental Psychology: Human Learning and Memory, 2, 88–94Google Scholar
Reber, A. S., Walkenfield, F. F., & Hernstadt, R. (1991). Implicit and explicit learning: Individual differences and IQ. Journal of Experimental Psychology. Learning, Memory, and Cognition, 17, 888–896CrossRefGoogle ScholarPubMed
Stanley, W. B., Mathews, R. C., Buss, R. R., & Kotler-Cope, S. (1989). Insight without awareness: On the interaction of verbalization, instruction, and practice in a simulated process control task. Quarterly Journal of Experimental Psychology, 41A, 553–577CrossRefGoogle Scholar
Sternberg, R. J. (1982). Reasoning, problem solving, and intelligence. In R. J. Sternberg (Ed.), Handbook of human intelligence (pp. 225–307). Cambridge, UK: Cambridge University Press
Sternberg, R. J. (1995). 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: Erlbaum
Sternberg, R. J., & Berg, C. A. (1986). Quantitative integration: Definitions of intelligence: A comparison of the 1921 and 1986 symposia. In R. J. Sternberg & D. K. Detterman (Eds.), What is intelligence? Contemporary viewpoints on its nature and definition (pp. 155–162). Norwood, NJ: Ablex
Sternberg, R. J., & Frensch, P. A. (Eds.). (1991). Complex problem solving: Principles and mechanisms. Hillsdale, NJ: Erlbaum
Sternberg, R. J., Nokes, C., Geissler, P. W., Prince, R., Okatcha, F., Bundy, D. A., & Grigorenko, E. L. (2001). The relationship between academic and practical intelligence: A case study in Kenya. Intelligence, 29, 401–418CrossRefGoogle Scholar
Strohschneider, S. (1986). Zur Stabilität und Validität von Handeln in komplexen Realitätsbereichen [On the stability and validity of complex problem-solving behavior]. Sprache & Kognition, 5, 42–48Google Scholar
Strohschneider, S. (1991). Problemlösen und Intelligenz: Über die Effekte der Konkretisierung komplexer Probleme [Complex problem solving and intelligence: On the effects of problem concreteness]. Diagnostica, 37, 353–371Google Scholar
Süß, H. M., Kersting, M., & Oberauer, K. (1991). Intelligenz und Wissen als Prädiktoren für Leistungen bei computersimulierten komplexen Problemen [Intelligence and knowledge as predictors of performance in solving complex computer-simulated problems]. Diagnostica, 37, 334–352Google Scholar
Süß, H.-M., Kersting, M., & Oberauer, K. (1993). Zur Vorhersage von Steuerungsleistungen an computersimulierten Systemen durch Wissen und Intelligenz [Predicting control performance in computer-simulated systems by means of knowledge and intelligence]. Zeitschrift für Differentielle und Diagnostische Psychologie, 14, 189–203Google Scholar
Vollmeyer, R., Burns, B. D., & Holyoak, K. J. (1996). The impact of goal specificity on strategy use and the acquisition of problem structure. Cognitive Science, 20, 75–100CrossRefGoogle Scholar
Wenke, D., & Frensch, P. A. (2003). Is success or failure at solving complex problems related to intellectual ability?. In J. E. Davidson & R. J. Sternberg (Eds.), The nature of problem solving (pp. 87–126). New York: Cambridge University PressCrossRef
Zacks, R. T., Hasher, L., & Sanft, H. (1982). Automatic encoding of event frequency: Further findings. Journal of Experimental Psychology: Learning, Memory, & Cognition, 8, 106–116Google Scholar

Save book to Kindle

To save this book to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×