recent research on problem solving

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

• View all journals
• Explore content
• About the journal
• Publish with us
• Sign up for alerts
• Review Article
• Published: 14 December 2023

Restructuring processes and Aha! experiences in insight problem solving

• Jennifer Wiley   ORCID: orcid.org/0000-0002-2590-7392 1 &
• Amory H. Danek   ORCID: orcid.org/0000-0002-2849-8774 2  

Nature Reviews Psychology volume  3 ,  pages 42–55 ( 2024 ) Cite this article

422 Accesses

1 Citations

7 Altmetric

Metrics details

• Human behaviour

Insightful solution processes represent cases of problem solving in which the emergence of a new interpretation allows for an abrupt shift from bewilderment to clarity. One approach to researching insight problem solving emphasizes cognitive restructuring of the problem representation as a defining feature of the insightful solution process. By contrast, another approach emphasizes phenomenological Aha! experiences. In this Review, we summarize both approaches, considering the restructuring processes involved in finding a solution and the Aha! experiences that might accompany solutions. We then consider the extent to which Aha! experiences co-occur with restructuring, and the critical observation that sometimes they do not. We conclude by proposing avenues for future research that combine the methodologies used to study restructuring and Aha! experiences to better understand the cognitive and phenomenological underpinnings of insight problem solving and the connections between them.

This is a preview of subscription content, access via your institution

Access options

Subscribe to this journal

Receive 12 digital issues and online access to articles

55,14 € per year

only 4,60 € per issue

Rent or buy this article

Prices vary by article type

Prices may be subject to local taxes which are calculated during checkout

Similar content being viewed by others

Microdosing with psilocybin mushrooms: a double-blind placebo-controlled study

Federico Cavanna, Stephanie Muller, … Enzo Tagliazucchi

The process and mechanisms of personality change

Joshua J. Jackson & Amanda J. Wright

Artificial intelligence and illusions of understanding in scientific research

Lisa Messeri & M. J. Crockett

Duncker, K. On problem-solving. Psychol. Monogr. 58 , 270 (1945).

Article   Google Scholar  

Ellen, P. Direction, past experience, and hints in creative problem solving: reply to Weisberg and Alba. J. Exp. Psychol. 111 , 316–325 (1982).

Katona, G. Organizing and Memorizing: Studies in the Psychology of Learning and Teaching (Columbia Univ. Press, 1940).

Köhler, W. An aspect of Gestalt psychology. Ped. Sem. J. Genet. Psychol. 32 , 691–723 (1925).

Google Scholar  

Luchins, A. S. Mechanization in problem solving: the effect of Einstellung . Psychol. Monogr. 54 , i–95 (1945).

Maier, N. R. F. Reasoning in humans. I. On direction. J. Comp. Psychol. 10 , 115–143 (1930).

Maier, N. R. F. Reasoning in humans. II. The solution of a problem and its appearance in consciousness. J. Comp. Psychol. 12 , 181–194 (1931).

Wertheimer, M. Productive Thinking Enlarged edn (Harper and Brothers, 1945/1959).

Ash, I. K., Cushen, P. J., & Wiley, J. Obstacles in investigating the role of restructuring in insightful problem solving. J. Probl. Solving https://doi.org/10.7771/1932-6246.1056 (2009).

Ohlsson, S. in Advances in the Psychology of Thinking (eds Keane, M. T. & Gilhooly, K. J.) 1–44 (Harvester Wheatsheaf, 1992).

Ohlsson, S. Deep Learning: How the Mind Overrides Experience (Cambridge Univ. Press, 2011).

Bühler, K. Tatsachen und Probleme zu einer Psychologie der Denkvorgänge. II. Über Gedankenzusammenhänge. Arch. Gesamte Psychol. 12 , 1–23 (1908).

Bowden, E. M. The effect of reportable and unreportable hints on anagram solution and the Aha! Experience. Conscious. Cogn. 6 , 545–573 (1997).

Article   PubMed   Google Scholar  

Bowden, E. M., Jung-Beeman, M., Fleck, J. I. & Kounios, J. New approaches to demystifying insight. Trends Cogn. Sci. 9 , 322–328 (2005).

Danek, A. H. in Routledge International Handbook of Creative Cognition (eds Ball, L. J. & Vallée-Tourangeau, F.) (Routledge, 2023).

Kaplan, C. A. & Simon, H. A. In search of insight. Cogn. Psychol. 22 , 374–419 (1990).

Kounios, J. & Beeman, M. The cognitive neuroscience of insight. Annu. Rev. Psychol. 65 , 71–93 (2014).

Smith, R. W. & Kounios, J. Sudden insight: all-or-none processing revealed by speed–accuracy decomposition. J. Exp. Psychol. Learn. Mem. Cogn. 22 , 1443–1462 (1996).

Gilhooly, K. J. Incubation and intuition in creative problem solving. Front. Psychol. 7 , 1076 (2016).

Article   PubMed   PubMed Central   Google Scholar  

Metcalfe, J. Premonitions of insight predict impending error. J. Exp. Psychol. Learn. Mem. Cogn. 12 , 623–634 (1986).

Metcalfe, J. & Wiebe, D. Intuition in insight and noninsight problem solving. Mem. Cogn. 15 , 238–246 (1987).

Newell, A., & Simon, H. A. Human Problem Solving (Prentice-Hall, 1972).

Davidson, J. E. in The Nature of Insight (eds Sternberg, R. J. & Davidson, J. E.) 125–155 (MIT Press, 1995).

MacGregor, J. N., Ormerod, T. C. & Chronicle, E. P. Information processing and insight: a process model of performance on the nine-dot and related problems. J. Exp. Psychol. Learn. Mem. Cogn. 27 , 176–201 (2001).

Weisberg, R. W. in The Nature of Insight (Sternberg, R. J. & Davidson, J. E.) 157–196 (MIT Press, 1995).

Ash, I. K. & Wiley, J. The nature of restructuring in insight: an individual-differences approach. Psychon. Bull. Rev. 13 , 66–73 (2006).

Cushen, P. J. & Wiley, J. Cues to solution, restructuring patterns, and reports of insight in creative problem solving. Consc. Cogn. 21 , 1166–1175 (2012).

Fedor, A., Szathmáry, E. & Öllinger, M. Problem solving stages in the five square problem. Front. Psychol. 6 , 1050 (2015).

Knoblich, G., Ohlsson, S., Haider, H. & Rhenius, D. Constraint relaxation and chunk decomposition in insight problem solving. J. Exp. Psychol. Learn. Mem. Cogn. 25 , 1534–1555 (1999).

Ormerod, T. C., MacGregor, J. N. & Chronicle, E. P. Dynamics and constraints in insight problem solving. J. Exp. Psychol. Learn. Mem. Cogn. 28 , 791–799 (2002).

Danek, A. H., Fraps, T., von Müller, A., Grothe, B. & Öllinger, M. Working wonders? Investigating insight with magic tricks. Cognition 130 , 174–185 (2014).

Hedne, M. R., Norman, E. & Metcalfe, J. Intuitive feelings of warmth and confidence in insight and noninsight problem solving of magic tricks. Front. Psychol. 7 , 1314 (2016).

Thomas, C., Didierjean, A. & Kuhn, G. It is magic! How impossible solutions prevent the discovery of obvious ones. Q. J. Exp. Psychol. 71 , 2481–2487 (2018).

Danek, A. H., Wiley, J. & Öllinger, M. Solving classical insight problems without Aha! experience: 9 dot, 8 coin, and matchstick arithmetic problems. J. Probl. Solving https://doi.org/10.7771/1932-6246.1183 (2016).

Gilhooly, K. J. & Murphy, P. Differentiating insight from non-insight problems. Think. Reason. 11 , 279–302 (2005).

Öllinger, M., Jones, G. & Knoblich, G. The dynamics of search, impasse, and representational change provide a coherent explanation of difficulty in the nine-dot problem. Psychol. Res. 78 , 266–275 (2014).

Webb, M. E., Little, D. R. & Cropper, S. J. Insight is not in the problem: investigating insight in problem solving across task types. Front. Psychol. 7 , 1424 (2016).

Dygert, S. K. & Jarosz, A. F. Individual differences in creative cognition. J. Exp. Psychol. Gen. 149 , 1249–1274 (2020).

MacGregor, J. N. & Cunningham, J. B. Rebus puzzles as insight problems. Behav. Res. Meth. 40 , 263–268 (2008).

Salvi, C., Costantini, G., Bricolo, E., Perugini, M. & Beeman, M. Validation of Italian rebus puzzles and compound remote associate problems. Behav. Res. Meth. 48 , 664–685 (2016).

Smith, S. M. & Blankenship, S. E. Incubation effects. Bull. Psychon. Soc. 27 , 311–314 (1989).

Threadgold, E., Marsh, J. E. & Ball, L. J. Normative data for 84 UK English rebus puzzles. Front. Psychol. 9 , 2513 (2018).

Mednick, S. The associative basis of the creative process. Psychol. Rev. 69 , 220–232 (1962).

Bowden, E. M. & Beeman, M. J. Getting the right idea: semantic activation in the right hemisphere may help solve insight problems. Psychol. Sci. 9 , 435–440 (1998).

Bowers, K. S., Regehr, G., Balthazard, C. & Parker, K. Intuition in the context of discovery. Cogn. Psychol. 22 , 72–110 (1990).

Schooler, J. W. & Melcher, J. in The Creative Cognition Approach (Smith, S. M., Ward, T. B. & Finke, R. A.) 97–143 (MIT Press, 1995).

Smith, S. M. & Blankenship, S. E. Incubation and the persistence of fixation in problem solving. Am. J. Psychol. 104 , 61–87 (1991).

Wiley, J. Expertise as mental set: the effects of domain knowledge in creative problem solving. Mem. Cogn 26 , 716–730 (1998).

Beeftink, F., Van Eerde, W. & Rutte, C. G. The effect of interruptions and breaks on insight and impasses: do you need a break right now? Creativ. Res. J. 20 , 358–364 (2008).

Friedlander, K. J. & Fine, P. A. “The penny drops”: investigating insight through the medium of cryptic crosswords. Front. Psychol. 9 , 904 (2018).

Bowden, E. M. & Jung-Beeman, M. Normative data for 144 compound remote associate problems. Behav. Res. Meth. Instrum. Comput. 35 , 634–639 (2003).

Cranford, E. A. & Moss, J. Is insight always the same? A protocol analysis of insight in compound remote associate problems. J. Probl. Solving 4 , https://doi.org/10.7771/1932-6246.1129 (2012).

Öllinger, M. & von Müller, A. Search and coherence-building in intuition and insight problem solving. Front. Psychol. 8 , 827 (2017).

Zander, T., Öllinger, M. & Volz, K. G. Intuition and insight: two processes that build on each other or fundamentally differ? Front. Psychol. 7 , 1395 (2016).

Ellis, J. J., Glaholt, M. G. & Reingold, E. M. Eye movements reveal solution knowledge prior to insight. Consc. Cogn. 20 , 768–776 (2011).

Novick, L. R. & Sherman, S. J. On the nature of insight solutions: evidence from skill differences in anagram solution. Q. J. Exp. Psychol. A 56 , 351–382 (2003).

Rees, H. J. & Israel, H. E. An investigation of the establishment and operation of mental sets. Psychol. Monogr. 46 , 1–26 (1935).

Tempel, T. & Frings, C. Directed forgetting in problem solving. Acta Psychol. 201 , 102955 (2019).

Jacoby, L. L. On interpreting the effects of repetition: solving a problem versus remembering a solution. J. Verb. Learn. Verb. Behav. 17 , 649–667 (1978).

Koppel, R. H. & Storm, B. C. Unblocking memory through directed forgetting. J. Cogn. Psychol. 24 , 901–907 (2012).

Smith, S. M. & Beda, Z. Old problems in new contexts: the context-dependent fixation hypothesis. J. Exp. Psychol. Gen. 149 , 192–197 (2020).

Auble, P. M., Franks, J. J. & Soraci, S. A. Effort toward comprehension: elaboration or “Aha”? Mem. Cogn. 7 , 426–434 (1979).

Bar-Hillel, M. Stumpers: an annotated compendium. Think. Reason. 27 , 536–566 (2021).

Bowden, E. M. Accessing relevant information during problem solving: time constraints on search in the problem space. Mem. Cogn. 13 , 280–286 (1985).

Dow, G. T. & Mayer, R. E. Teaching students to solve insight problems: evidence for domain specificity in creativity training. Creativ. Res. J. 16 , 389–398 (2004).

Durso, F. T., Rea, C. B. & Dayton, T. Graph-theoretic confirmation of restructuring during insight. Psychol. Sci. 5 , 94–98 (1994).

Lockhart, R. S., Lamon, M. & Gick, M. L. Conceptual transfer in simple insight problems. Mem. Cogn. 16 , 36–44 (1988).

Patrick, J. & Ahmed, A. Facilitating representation change in insight problems through training. J. Exp. Psychol. Learn. Mem. Cogn. 40 , 532–543 (2014).

Bar-Hillel, M., Noah, T. & Frederick, S. Solving stumpers, CRT and CRAT: are the abilities related? Judgm. Decis. Mak. 14 , 620–623 (2019).

Webb, M. E., Little, D. R. & Cropper, S. J. Once more with feeling: normative data for the Aha experience in insight and noninsight problems. Behav. Res. Meth. 50 , 2035–2056 (2018).

Beilock, S. L. & DeCaro, M. S. From poor performance to success under stress: working memory, strategy selection, and mathematical problem solving under pressure. J. Exp. Psychol. Learn. Mem. Cogn. 33 , 983–998 (2007).

DeCaro, M. S., Van Stockum, C. A. & Wieth, M. B. When higher working memory capacity hinders insight. J. Exp. Psychol. Learn. Mem. Cogn. 42 , 39–49 (2016).

Van Stockum Jr, C. A. & DeCaro, M. S. When working memory mechanisms compete: predicting cognitive flexibility versus mental set. Cognition 201 , 104313 (2020).

Koppel, R., George, T. & Wiley, J. in The Emergence of Insight (Cambridge Press, 2024).

Bilalić, M., McLeod, P. & Gobet, F. The mechanism of the Einstellung (set) effect: a pervasive source of cognitive bias. Curr. Dir. Psychol. Sci. 19 , 111–115 (2010).

Sheridan, H. & Reingold, E. M. The mechanisms and boundary conditions of the Einstellung effect in chess: evidence from eye movements. PLoS One 8 , e75796 (2013).

Ellis, J. J. & Reingold, E. M. The Einstellung effect in anagram problem solving: evidence from eye movements. Front. Psychol. 5 , 679 (2014).

Beda, Z. & Smith, S. M. Chasing red herrings: memory of distractors causes fixation in creative problem solving. Mem. Cogn. 46 , 671–684 (2018).

Howe, M. L. & Garner, S. R. Can false memories prime alternative solutions to ambiguous problems? Memory 26 , 96–105 (2018).

Smith, S. M. in The Nature of Insight (Sternberg, R. J. & Davidson, J. E.) 229–251 (MIT Press, 1995).

Kohn, N. & Smith, S. M. Partly versus completely out of your mind: effects of incubation and distraction on resolving fixation. J. Creativ. Behav. 43 , 102–118 (2009).

Koppel, R. H. & Storm, B. C. Escaping mental fixation: incubation and inhibition in creative problem solving. Memory 22 , 340–348 (2014).

May, C. P. Synchrony effects in cognition: the costs and a benefit. Psychon. Bull. Rev. 6 , 142–147 (1999).

Penaloza, A. A. & Calvillo, D. P. Incubation provides relief from artificial fixation in problem solving. Creativ. Res. J. 24 , 338–344 (2012).

Storm, B. C. & Angello, G. Overcoming fixation: creative problem solving and retrieval-induced forgetting. Psychol. Sci. 21 , 1263–1265 (2010).

Storm, B. C. & Hickman, M. L. Mental fixation and metacognitive predictions of insight in creative problem solving. Q. J. Exp. Psychol. 68 , 802–813 (2015).

Vul, E. & Pashler, H. Incubation benefits only after people have been misdirected. Mem. Cogn. 35 , 701–710 (2007).

Ricks, T. R., Turley-Ames, K. J. & Wiley, J. Effects of working memory capacity on mental set due to domain knowledge. Mem. Cogn. 35 , 1456–1462 (2007).

Dodds, R. A., Ward, T. B. & Smith, S. M. in Creativity Research Handbook (ed. Runco, M. A.) 291–322 (Hampton Press, 2012).

Sio, U. N. & Ormerod, T. C. Does incubation enhance problem solving? A meta-analytic review. Psychol. Bull. 135 , 94–120 (2009).

Caravona, L. & Macchi, L. Different incubation tasks in insight problem solving: evidence for unconscious analytic thought. Think. Reason. 29 , 559–593 (2023).

Sanders, K. E. & Beeman, M. Sleep and incubation: using problem reactivation during sleep to study forgetting fixation and unconscious processing during sleep incubation. J. Cogn. Psychol. 33 , 738–756 (2021).

Cai, D. J., Mednick, S. A., Harrison, E. M., Kanady, J. C. & Mednick, S. C. REM, not incubation, improves creativity by priming associative networks. Proc. Natl Acad. Sci. USA 106 , 10130–10134 (2009).

Stickgold, R. & Walker, M. P. Sleep-dependent memory triage: evolving generalization through selective processing. Nat. Neurosci. 16 , 139–145 (2013).

Segal, E. Incubation in insight problem solving. Creativ. Res. J. 16 , 141–148 (2004).

George, T. & Wiley, J. Fixation, flexibility, and forgetting during alternate uses tasks. Psychol. Aesth. Creativ. Arts 13 , 305–313 (2019).

Lu, J. G., Akinola, M. & Mason, M. F. “Switching on” creativity: task switching can increase creativity by reducing cognitive fixation. Organ. Behav. Hum. Decis. Process. 139 , 63–75 (2017).

Smith, S. M., Gerkens, D. R. & Angello, G. Alternating incubation effects in the generation of category exemplars. J. Creativ. Behav. 51 , 95–106 (2017).

Ansburg, P. I. & Hill, K. Creative and analytic thinkers differ in their use of attentional resources. Pers. Individ. Differ. 34 , 1141–1152 (2003).

Kim, S., Hasher, L. & Zacks, R. T. Aging and a benefit of distractibility. Psychon. Bull. Rev. 14 , 301–305 (2007).

Reverberi, C., Toraldo, A., D’Agostini, S. & Skrap, M. Better without (lateral) frontal cortex? Insight problems solved by frontal patients. Brain 128 , 2882–2890 (2005).

Wiley, J. & Jarosz, A. How working memory capacity affects problem solving. Psychol. Learn. Motiv. 56 , 185–227 (2012).

Zmigrod, S., Zmigrod, L. & Hommel, B. The relevance of the irrelevant: attentional distractor-response binding predicts performance in the remote associates task. Psychol. Aesth. Creativ. Arts 13 , 15–23 (2019).

Ninomiya, Y. et al. Effect of cognitive load and working memory capacity on the efficiency of discovering better alternatives: a survival analysis. Mem. Cogn . https://doi.org/10.3758/s13421-023-01448-w (2023).

Tan, T., Zou, H., Chen, C. & Luo, J. Mind wandering and the incubation effect in insight problem solving. Creativ. Res. J. 27 , 375–382 (2015).

Yang, T. & Wu, G. Spontaneous or deliberate: the dual influence of mind wandering on creative incubation. J. Creativ. Behav. 56 , 584–600 (2022).

Zedelius, C. M. & Schooler, J. W. Mind wandering “Ahas” versus mindful reasoning: alternative routes to creative solutions. Front. Psychol. 6 , 834 (2015).

Benedek, M., Panzierer, L., Jauk, E. & Neubauer, A. C. Creativity on tap? Effects of alcohol intoxication on creative cognition. Consc. Cogn. 56 , 128–134 (2017).

Jarosz, A. F., Colflesh, G. J. & Wiley, J. Uncorking the muse: alcohol intoxication facilitates creative problem solving. Consc. Cogn. 21 , 487–493 (2012).

Wieth, M. B. & Zacks, R. T. Time of day effects on problem solving: when the non-optimal is optimal. Think. Reason. 17 , 387–401 (2011).

Bolte, A., Goschke, T. & Kuhl, J. Emotion and intuition: effects of positive and negative mood on implicit judgments of semantic coherence. Psychol. Sci. 14 , 416–421 (2003).

Rowe, G., Hirsh, J. B. & Anderson, A. K. Positive affect increases the breadth of attentional selection. Proc. Natl Acad. Sci. USA 104 , 383–388 (2007).

Aiello, D. A., Jarosz, A. F., Cushen, P. J. & Wiley, J. Firing the executive: when an analytic approach to problem solving helps and hurts. J. Probl. Solving https://doi.org/10.7771/1932-6246.1128 (2012).

Ellis, D. M., Robison, M. K. & Brewer, G. A. The cognitive underpinnings of multiply-constrained problem solving. J. Intell. 9 , 7 (2021).

Chein, J. M., Weisberg, R. W., Streeter, N. L. & Kwok, S. Working memory and insight in the nine-dot problem. Mem. Cogn. 38 , 883–892 (2010).

Kershaw, T. C. & Ohlsson, S. Multiple causes of difficulty in insight: the case of the nine-dot problem. J. Exp. Psychol. Learn. Mem. Cogn. 30 , 3–13 (2004).

Lung, C. T. & Dominowski, R. L. Effects of strategy instructions and practice on nine-dot problem solving. J. Exp. Psychol. Learn. Mem. Cogn. 11 , 804–811 (1985).

Öllinger, M., Jones, G., Faber, A. H. & Knoblich, G. Cognitive mechanisms of insight: the role of heuristics and representational change in solving the eight-coin problem. J. Exp. Psychol. Learn. Mem. Cogn. 39 , 931–939 (2013).

Thomas, L. E. & Lleras, A. Swinging into thought: directed movement guides insight in problem solving. Psychon Bull. Rev. 16 , 719–723 (2009).

Hattori, M., Sloman, S. A. & Orita, R. Effects of subliminal hints on insight problem solving. Psychon. Bull. Rev. 20 , 790–797 (2013).

Moss, J., Kotovsky, K. & Cagan, J. The influence of open goals on the acquisition of problem-relevant information. J. Exp. Psychol. Learn. Mem. Cogn. 33 , 876–891 (2007).

Moss, J., Kotovsky, K. & Cagan, J. The effect of incidental hints when problems are suspended before, during, or after an impasse. J. Exp. Psychol. Learn. Mem. Cogn. 37 , 140–148 (2011).

Pétervári, J. & Danek, A. H. Problem solving of magic tricks: guiding to and through an impasse with solution cues. Think. Reason. 26 , 502–533 (2020).

Seifert, C. M., Meyer, D. E., Davidson, N., Patalano, A. L., & Yaniv, I. in The Nature of Insight (Sternberg, R. J. & Davidson, J. E.) 65–124 (MIT Press, 1995).

Gick, M. L. & McGarry, S. J. Learning from mistakes: inducing analogous solution failures to a source problem produces later successes in analogical transfer. J. Exp. Psychol. Learn. Mem. Cogn. 18 , 623–639 (1992).

Ash, I. K., Jee, B. D. & Wiley, J. Investigating insight as sudden learning. J. Probl. Solving https://doi.org/10.7771/1932-6246.1123 (2012).

Ansburg, P. I. & Dominowski, R. I. Promoting insightful problem solving. J. Creat. Behav. 34 , 30–60 (2000).

Bianchi, I., Branchini, E., Burro, R., Capitani, E. & Savardi, U. Overtly prompting people to “think in opposites” supports insight problem solving. Think. Reason. 26 , 31–67 (2020).

Chrysikou, E. G. When shoes become hammers: goal-derived categorization training enhances problem-solving performance. J. Exp. Psychol. Learn. Mem. Cogn. 32 , 935–942 (2006).

Blech, C., Gaschler, R. & Bilalić, M. Why do people fail to see simple solutions? Using think-aloud protocols to uncover the mechanism behind the Einstellung (mental set) effect. Think. Reason. 26 , 552–580 (2020).

Fleck, J. I. & Weisberg, R. W. The use of verbal protocols as data: an analysis of insight in the candle problem. Mem. Cogn. 32 , 990–1006 (2004).

Fleck, J. I. & Weisberg, R. W. Insight versus analysis: evidence for diverse methods in problem solving. J. Cogn. Psychol. 25 , 436–463 (2013).

Tidikis, V. & Ash, I. K. Working in dyads and alone: examining process variables in solving insight problems. Creativ. Res. J. 25 , 189–198 (2013).

Gupta, N., Jang, Y., Mednick, S. C. & Huber, D. E. The road not taken: creative solutions require avoidance of high-frequency responses. Psychol. Sci. 23 , 288–294 (2012).

Bilalić, M., Graf, M., Vaci, N. & Danek, A. H. The temporal dynamics of insight problem solving—restructuring might not always be sudden. Think. Reason. 27 , 1–37 (2021).

Knoblich, G., Ohlsson, S. & Raney, G. E. An eye movement study of insight problem solving. Mem. Cogn. 29 , 1000–1009 (2001).

Nathan, M. J., Schenck, K. E., Vinsonhaler, R., Michaelis, J. E., Swart, M. I. & Walkington, C. Embodied geometric reasoning: dynamic gestures during intuition, insight, and proof. J. Educ. Psychol. 113 , 929–948 (2020).

Vallée-Tourangeau, F., Ross, W., Ruffatto Rech, R. & Vallée-Tourangeau, G. Insight as discovery. J. Cogn. Psychol. 33 , 718–737 (2021).

Loesche, F., Goslin, J. & Bugmann, G. Paving the way to Eureka—introducing “Dira” as an experimental paradigm to observe the process of creative problem solving. Front. Psychol. 9 , 1773 (2018).

Ash, I. K. & Wiley, J. Hindsight bias in insight and mathematical problem solving: evidence of different reconstruction mechanisms for metacognitive versus situational judgments. Mem. Cogn. 36 , 822–837 (2008).

Danek, A. H. & Wiley, J. What causes the insight memory advantage? Cognition 205 , 104411 (2020).

Danek, A. H., Williams, J. & Wiley, J. Closing the gap: connecting sudden representational change to the subjective Aha! experience in insightful problem solving. Psychol. Res. 84 , 111–119 (2020).

Bowden, E. M. & Grunewald, K. in Insight: On the Origins of New Ideas F. (ed. Vallée-Tourangeau, F.) 28–50 (Routledge, 2018).

Gick, M. L., & Lockhart, R. S. in The Nature of Insight (Sternberg, R. J. & Davidson, J. E.) 197–228 (MIT Press, 1995).

Bilalić, M., Graf, M., Vaci, N., & Danek, A. H. When the solution is on the doorstep: better solving performance, but diminished Aha! experience for chess experts on the mutilated checkerboard problem. Cogn. Sci. 43 , e12771 (2019).

Laukkonen, R. E., Ingledew, D. J., Grimmer, H. J., Schooler, J. W. & Tangen, J. M. Getting a grip on insight: real-time and embodied Aha experiences predict correct solutions. Cogn. Emot. 35 , 918–935 (2021).

Ross, W. & Vallée-Tourangeau, F. Insight with stumpers: normative solution data for 25 stumpers and a fresh perspective on the accuracy effect. Think. Skills Creat. 46 , 101114 (2022).

Köhler, W. The Task of Gestalt Psychology (Princeton Univ. Press, 1969).

Ovington, L. A., Saliba, A. J., Moran, C. C., Goldring, J. & MacDonald, J. B. Do people really have insights in the shower? The when, where and who of the Aha! moment. J. Creativ. Behav. 52 , 21–34 (2018).

Gable, S. L., Hopper, E. A. & Schooler, J. W. When the muses strike: creative ideas of physicists and writers routinely occur during mind wandering. Psychol. Sci. 30 , 396–404 (2019).

Jung-Beeman, M. et al. Neural activity when people solve verbal problems with insight. PLoS Biol. 2 , 500–510 (2004).

Danek, A. H. & Wiley, J. What about false insights? Deconstructing the Aha! experience along its multiple dimensions for correct and incorrect solutions separately. Front. Psychol. 7 , 2077 (2017).

Danek, A. H., Fraps, T., von Müller, A., Grothe, B., & Öllinger, M. It’s a kind of magic — what self-reports can reveal about the phenomenology of insight problem solving. Front. Psychol.   5 , 1408 (2014).

Thagard, P. & Stewart, T. C. The Aha! experience: creativity through emergent binding in neural networks. Cogn. Sci. 35 , 1–33 (2011).

Gruber, H. E. in The Nature of Insight (Sternberg, R. J. & Davidson, J. E.) 397–431 (MIT Press, 1995).

Skaar, Ø. O. & Reber, R. Motivation through insight: the phenomenological correlates of insight and spatial ability tasks. J. Cogn. Psychol. 33 , 631–643 (2021).

Spiridonov, V., Loginov, N. & Ardislamov, V. Dissociation between the subjective experience of insight and performance in the CRA paradigm. J. Cogn. Psychol. 33 , 685–699 (2021).

Stuyck, H., Aben, B., Cleeremans, A. & Van den Bussche, E. The Aha! moment: is insight a different form of problem solving? Consc. Cogn. 90 , 103055 (2021).

Webb, M. E., Cropper, S. J. & Little, D. R. Unusual uses and experiences are good for feeling insightful, but not for problem solving: contributions of schizotypy, divergent thinking, and fluid reasoning, to insight moments. J. Cogn. Psychol. 33 , 770–792 (2021).

Kizilirmak, J. M., Serger, V., Kehl, J., Öllinger, M., Folta-Schoofs, K. & Richardson-Klavehn, A. Feelings-of-warmth increase more abruptly for verbal riddles solved with in contrast to without Aha! experience. Front. Psychol. 9 , 1404 (2018).

Becker, M., Kühn, S. & Sommer, T. Verbal insight revisited—dissociable neurocognitive processes underlying solutions accompanied by an Aha! experience with and without prior restructuring. J. Cogn. Psychol. 33 , 659–684 (2021).

Topolinski, S. & Reber, R. Gaining insight into the “Aha” experience. Curr. Dir. Psychol. Sci. 19 , 402–405 (2010).

Salvi, C., Simoncini, C., Grafman, J. & Beeman, M. Oculometric signature of switch into awareness? Pupil size predicts sudden insight whereas microsaccades predict problem-solving via analysis. NeuroImage 217 , 116933 (2020).

Danek, A. H. & Salvi, C. Moment of truth: why Aha! experiences are correct. J. Creativ. Behav. 54 , 484–486 (2020).

Dietrich, A. & Haider, H. Human creativity, evolutionary algorithms, and predictive representations: the mechanics of thought trials. Psychon. Bull. Rev. 22 , 897–915 (2015).

Salvi, C., Bricolo, E., Kounios, J., Bowden, E. M. & Beeman, M. Insight solutions are correct more often than analytic solutions. Think. Reason. 22 , 1–18 (2016).

Webb, M. E., Laukkonen, R. E., Cropper, S. J. & Little, D. R. Commentary: moment of (perceived) truth: exploring accuracy of Aha! experiences. J. Creativ. Behav. 55 , 289–293 (2021).

Shen, W., Tong, Y., Yuan, Y., Zhan, H., Liu, C., Luo, J. & Cai, H. Feeling the insight: uncovering somatic markers of the “Aha” experience. Appl. Psychophysiol. Biofeedback 43 , 13–21 (2018).

Stuyck, H., Cleeremans, A. & Van den Bussche, E. Aha! under pressure: the Aha! experience is not constrained by cognitive load. Cognition 219 , 104946 (2022).

Strickland, T., Wiley, J. & Ohlsson, S. Hints and the Aha-accuracy effect in insight problem solving. Proc. Annu. Meet. Cogn. Sci. Soc. 44 , 3209–3215 (2022).

Kizilirmak, J. M., Gallisch, N., Schott, B. H. & Folta-Schoofs, K. Insight is not always the same: differences between true, false, and induced insights in the matchstick arithmetic task. J. Cogn. Psychol. 33 , 700–717 (2021).

Webb, M. E., Cropper, S. J. & Little, D. R. “Aha!” is stronger when preceded by a “huh?”: presentation of a solution affects ratings of Aha experience conditional on accuracy. Think. Reason. 25 , 324–364 (2019).

Kizilirmak, J. M., Galvao Gomes da Silva, J., Imamoglu, F. & Richardson-Klavehn, A. Generation and the subjective feeling of “Aha!” are independently related to learning from insight. Psychol. Res. 80 , 1059–1074 (2016).

Kounios, J., Fleck, J. I., Green, D. L., Payne, L., Stevenson, J. L., Bowden, E. M. & Jung-Beeman, M. The origins of insight in resting-state brain activity. Neuropsychologia 46 , 281–291 (2008).

Sadler-Smith, E. Wallas’ four-stage model of the creative process: more than meets the eye? Creativ. Res. J. 27 , 342–352 (2015).

Wallas, G. The Art of Thought (Harcourt and Brace, 1926).

Chronicle, E. P., MacGregor, J. N. & Ormerod, T. C. What makes an insight problem? The roles of heuristics, goal conception, and solution recoding in knowledge-lean problems. J. Exp. Psychol. Learn. Mem. Cogn. 30 , 14–27 (2004).

Grimmer, H., Laukkonen, R., Tangen, J. & von Hippel, W. Eliciting false insights with semantic priming. Psychon. Bull. Rev. 29 , 954–970 (2022).

Laukkonen, R. E., Kaveladze, B. T., Tangen, J. M. & Schooler, J. W. The dark side of Eureka: artificially induced Aha moments make facts feel true. Cognition 196 , 104122 (2020).

Laukkonen, R. E., Kaveladze, B. T., Protzko, J., Tangen, J. M., von Hippel, W. & Schooler, J. W. Irrelevant insights make worldviews ring true. Sci. Rep. 12 , 2075 (2022).

Metcalfe, J., Schwartz, B. L., & Bloom, P. A. The tip-of-the-tongue state and curiosity. Cogn. Res. Princ. Implic.   2 , 31 (2017).  

Bianchi, I., Branchini, E., Canestrari, C. & Burro, R. On pleasures of the mind related to humour and insight problem solving: an investigation of people’s awareness of what they like and why. J. Cogn. Psychol. 34 , 778–795 (2022).

Kozbelt, A. & Nishioka, K. Humor comprehension, humor production, and insight: an exploratory study. Int. J. Humor Res. 23 , 375–401 (2010).

Chesebrough, C., Chrysikou, E. G., Holyoak, K. J., Zhang, F. & Kounios, J. Conceptual change induced by analogical reasoning sparks aha moments. Creativ. Res. J. 35 , 1–23 (2010).

George T., & Wiley, J. in Insight: On the Origin of New Ideas (ed. Vallée-Tourangeau, F.) 143–168 (Routledge, 2018).

Lv, K. The involvement of working memory and inhibition functions in the different phases of insight problem solving. Mem. Cogn. 43 , 709–722 (2015).

Weisberg, R. W. Toward an integrated theory of insight in problem solving. Think. Reason. 21 , 5–39 (2015).

Slamecka, N. J. & Graf, P. The generation effect: delineation of a phenomenon. J. Exp. Psychol. Hum. Learn. Mem. 4 , 592–604 (1978).

Buyer, L. S. & Dominowski, R. L. Retention of solutions: it is better to give than to receive. Am. J. Psychol. 102 , 353–363 (1989).

Kizilirmak, J. M., Wiegmann, B. & Richardson-Klavehn, A. Problem solving as an encoding task: a special case of the generation effect. J. Probl. Solving 9 , 59–76 (2016).

Patalano, A. L. & Seifert, C. M. Memory for impasses during problem solving. Mem. Cogn. 22 , 234–242 (1994).

Dominowski, R. L. & Buyer, L. S. Retention of problem solutions: the re-solution effect. Am. J. Psychol. 113 , 249–274 (2000).

Schwartz, D. & Martin, T. Inventing to prepare for future learning: the hidden efficiency of encouraging original student production in statistics instruction. Cogn. Instr. 22 , 129–184 (2004).

Jarosz, A. F., Goldenberg, O. & Wiley, J. Learning by invention: small group discussion activities that support learning in statistics. Discourse Process. 54 , 285–302 (2017).

Sinha, T. & Kapur, M. When problem solving followed by instruction works: evidence for productive failure. Rev. Educ. Res. 91 , 761–798 (2021).

Danek, A. H., Fraps, T., von Müller, A., Grothe, B. & Öllinger, M. Aha! experiences leave a mark: facilitated recall of insight solutions. Psychol. Res. 77 , 659–669 (2013).

Liljedahl, P. G. Mathematical discovery and affect: the effect of Aha! experiences on undergraduate mathematics students. Int. J. Math. Educ. Sci. Technol. 36 , 219–234 (2005).

Metcalfe, J., Schwartz, B. L. & Eich, T. S. Epistemic curiosity and the region of proximal learning. Curr. Opin. Behav. Sci. 35 , 40–47 (2020).

Van de Cruys, S., Damiano, C., Boddez, Y., Król, M., Goetschalckx, L. & Wagemans, J. Visual affects: linking curiosity, Aha-Erlebnis, and memory through information gain. Cognition 212 , 104698 (2021).

Kizilirmak, J. M., Thuerich, H., Folta-Schoofs, K., Schott, B. H. & Richardson-Klavehn, A. Neural correlates of learning from induced insight: a case for reward-based episodic encoding. Front. Psychol. 7 , 1693 (2016). (2016).

Oh, Y., Chesebrough, C., Erickson, B., Zhang, F. & Kounios, J. An insight-related neural reward signal. NeuroImage 214 , 116757 (2020).

Salvi, C., Leiker, E. K., Baricca, B., Molinari, M. A., Eleopra, R., Nichelli, P. F., Grafman, J. & Dunsmoor, J. E. The effect of dopaminergic replacement therapy on creative thinking and insight problem-solving in Parkinson’s disease patients. Front. Psychol. 12 , 646448 (2021).

Tik, M., Sladky, R., Luft, C. D. B., Willinger, D., Hoffmann, A., Banissy, M. J. & Windischberger, C. Ultra‐high‐field fMRI insights on insight: neural correlates of the Aha!‐moment. Hum. Brain Mapp. 39 , 3241–3252 (2018).

Download references

Acknowledgements

The authors thank I. K. Ash, P. J. Cushen, T. George, A. F. Jarosz, T. S. Miller and S. Ohlsson for discussion on these topics.

Author information

Authors and affiliations.

Department of Psychology, University of Illinois at Chicago, Chicago, IL, USA

Jennifer Wiley

Department of Psychology, Heidelberg University, Heidelberg, Germany

Amory H. Danek

You can also search for this author in PubMed   Google Scholar

Contributions

The authors contributed equally to all aspects of the article.

Corresponding author

Correspondence to Jennifer Wiley .

Ethics declarations

Competing interests.

The authors declare no competing interests.

Peer review

Peer review information.

Nature Reviews Psychology thanks Rolf Reber and the other anonymous, reviewers for their contribution to the peer review of this work.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Cite this article.

Wiley, J., Danek, A.H. Restructuring processes and Aha! experiences in insight problem solving. Nat Rev Psychol 3 , 42–55 (2024). https://doi.org/10.1038/s44159-023-00257-x

Download citation

Accepted : 30 October 2023

Published : 14 December 2023

Issue Date : January 2024

DOI : https://doi.org/10.1038/s44159-023-00257-x

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Quick links

• Explore articles by subject
• Guide to authors
• Editorial policies

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Articles on Problem solving

Displaying 1 - 20 of 27 articles.

The surprising key to magpie intelligence: it’s not genetic

Lizzie Speechley , The University of Western Australia

‘Smart drugs’ make you worse at solving complex problems, new study finds

Elizabeth Bowman , The University of Melbourne

Lockdown schooling: research from around the world shows reasons to be hopeful

Nina Bergdahl , Stockholm University and Melissa Bond , University of South Australia

Future engineers need to understand their work’s human impact – here’s how my classes prepare students to tackle problems like climate change

Gordon D. Hoople , University of San Diego

Being good at maths might help you become great at sports – Emma Raducanu showed us why

Laurence Shaw , Nottingham Trent University

Why students learn better when they move their bodies – instead of sitting still at their desks

Katie Headrick Taylor , University of Washington

5 digital games that teach civics through play

Karen "Kat" Schrier , Marist College

Is gaming good for kids?

John Velez , Indiana University

Your coping and resilience strategies might need to shift as the COVID-19 crisis continues

Craig Polizzi , Binghamton University, State University of New York and Steven Jay Lynn , Binghamton University, State University of New York

Feeling overwhelmed? Approach coronavirus as a challenge to be met, not a threat to be feared

Bethany Teachman , University of Virginia

Collaborative problem solvers are made not born – here’s what you need to know

Stephen M. Fiore , University of Central Florida

Customer service staff need to be problem solving not apologising

Jagdip Singh , Case Western Reserve University

Stuck in the past: the UK needs to produce creative thinkers not exam-passing machines

Thusha Rajendran , Heriot-Watt University

Distance learning: the five qualities student teachers need to succeed

Nhlanhla Mpofu , Sol Plaatje University

Otter Tupperware party we threw reveals how animals copy each other to learn

Neeltje Boogert , University of Exeter

Apps to keep kids thinking and learning even during school holidays

Craig Blewett , University of KwaZulu-Natal

Schools will teach ‘soft skills’ from 2017, but assessing them presents a challenge

Bill Lucas , Victoria University

Engineers don’t just build things, they can help save the world

Petr Matous , University of Sydney and Abbas El-Zein , University of Sydney

Outdated exams are holding children back – not computers in the classroom

James Stanfield , Newcastle University and Angelika Strohmayer , Newcastle University

Why students make silly mistakes in class (and what can be done)

Greg Ashman , UNSW Sydney

Related Topics

• Engineering
• Maths education
• Organisation for Economic Co-operation and Development (OECD)
• Remote learning

Top contributors

Research group leader, principal investigator, and ATTRACT-fellow, University of Luxembourg

Researcher, University of California, Berkeley

Royal Society Dorothy Hodgkin Research Fellow, University of Exeter

Research associate and doctoral candidate, University of Luxembourg

Senior Lecturer in Computing and Communications, The Open University

Senior Lecturer, The Open University

Head of Learning Sciences Lab, National Institute of Education of Singapore

Professor of Psychology and Educational Science, University of Luxembourg

PhD candidate in Instructional Design, UNSW Sydney

Professor of Cognition, Lancaster University

Associate Professor in Education & Technology, University of KwaZulu-Natal

Behavioural Ecologist, The University of Western Australia

Lecturer, School of Education, Communication and Language Sciences, Newcastle University

Doctoral Trainee in Digital Civics, Newcastle University

Senior Lecturer in Education, Canterbury Christ Church University

• X (Twitter)
• Unfollow topic Follow topic

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• Elsevier - PMC COVID-19 Collection

Problem solving through values: A challenge for thinking and capability development

• • This paper introduces the 4W framework of consistent problem solving through values.
• • The 4W suggests when, how and why the explication of values helps to solve a problem.
• • The 4W is significant to teach students to cope with problems having crucial consequences.
• • The paper considers challenges using such framework of thinking in different fields of education.

The paper aims to introduce the conceptual framework of problem solving through values. The framework consists of problem analysis, selection of value(s) as a background for the solution, the search for alternative ways of the solution, and the rationale for the solution. This framework reveals when, how, and why is important to think about values when solving problems. A consistent process fosters cohesive and creative value-based thinking during problem solving rather than teaching specific values. Therefore, the framework discloses the possibility for enabling the development of value-grounded problem solving capability.The application of this framework highlights the importance of responsibility for the chosen values that are the basis for the alternatives which determine actions. The 4W framework is meaningful for the people’s lives and their professional work. It is particularly important in the process of future professionals’ education. Critical issues concerning the development of problem solving through values are discussed when considering and examining options for the implementation of the 4W framework in educational institutions.

1. Introduction

The core competencies necessary for future professionals include problem solving based on complexity and collaborative approaches ( OECD, 2018 ). Currently, the emphasis is put on the development of technical, technological skills as well as system thinking and other cognitive abilities (e.g., Barber, 2018 ; Blanco, Schirmbeck, & Costa, 2018 ). Hence, education prepares learners with high qualifications yet lacking in moral values ( Nadda, 2017 ). Educational researchers (e.g., Barnett, 2007 ; Harland & Pickering, 2010 ) stress that such skills and abilities ( the how? ), as well as knowledge ( the what? ), are insufficient to educate a person for society and the world. The philosophy of education underlines both the epistemological and ontological dimensions of learning. Barnett (2007) points out that the ontological dimension has to be above the epistemological one. The ontological dimension encompasses the issues related to values that education should foster ( Harland & Pickering, 2010 ). In addition, values are closely related to the enablement of learners in educational environments ( Jucevičienė et al., 2010 ). For these reasons, ‘ the why ?’ based on values is required in the learning process. The question arises as to what values and how it makes sense to educate them. Value-based education seeks to address these issues and concentrates on values transfer due to their integration into the curriculum. Yazdani and Akbarilakeh (2017) discussed that value-based education could only convey factual knowledge of values and ethics. However, such education does not guarantee the internalization of values. Nevertheless, value-based education indicates problem solving as one of the possibilities to develop values.

Values guide and affect personal behavior encompassing the ethical aspects of solutions ( Roccas, Sagiv, & Navon, 2017 ; Schwartz, 1992 , 2012 ; Verplanken & Holland, 2002 ). Therefore, they represent the essential foundation for solving a problem. Growing evidence indicates the creative potential of values ( Dollinger, Burke, & Gump, 2007 ; Kasof, Chen, Himsel, & Greenberger, 2007 ; Lebedeva et al., 2019) and emphasizes their significance for problem solving. Meanwhile, research in problem solving pays little attention to values. Most of the problem solving models (e.g., Newell & Simon, 1972 ; Jonassen, 1997 ) utilize a rational economic approach. Principally, the research on the mechanisms of problem solving have been conducted under laboratory conditions performing simple tasks ( Csapó & Funke, 2017 ). Moreover, some of the decision-making models share the same steps as problem solving (c.f., Donovan, Guss, & Naslund, 2015 ). This explains why these terms are sometimes used interchangeably ( Huitt, 1992 ). Indeed, decision-making is a part of problem solving, which emerges while choosing between alternatives. Yet, values, moral, and ethical issues are more common in decision-making research (e.g., Keeney, 1994 ; Verplanken & Holland, 2002 ; Hall & Davis, 2007 ; Sheehan & Schmidt, 2015 ). Though, research by Shepherd, Patzelt, and Baron (2013) , Baron, Zhao, and Miao (2015) has affirmed that contemporary business decision makers rather often leave aside ethical issues and moral values. Thus, ‘ethical disengagement fallacy’ ( Sternberg, 2017, p.7 ) occurs as people think that ethics is more relevant to others. In the face of such disengagement, ethical issues lose their prominence.

The analysis of the literature revealed a wide field of problem solving research presenting a range of more theoretical insights rather empirical evidence. Despite this, to date, a comprehensive model that reveals how to solve problems emphasizing thinking about values is lacking. This underlines the relevance of the chosen topic, i.e. a challenge for thinking and for the development of capabilities addressing problems through values. To address this gap, the following issues need to be investigated: When, how, and why a problem solver should take into account values during problem solving? What challenges may occur for using such framework of thinking in different fields of education? Aiming this, the authors of the paper substantiated the conceptual framework of problem solving grounded in consistent thinking about values. The substantiation consists of several parts. First, different approaches to solving problems were examined. Second, searching to reveal the possibilities of values integration into problem solving, value-based approaches significant for problem solving were critically analyzed. Third, drawing on the effect of values when solving a problem and their creative potential, the authors of this paper claim that the identification of values and their choice for a solution need to be specified in the process of problem solving. As a synthesis of conclusions coming from the literature review and conceptual extensions regarding values, the authors of the paper created the coherent framework of problem solving through values (so called 4W).

The novelty of the 4W framework is exposed by several contributions. First, the clear design of overall problem solving process with attention on integrated thinking about values is used. Unlike in most models of problem solving, the first stage encompass the identification of a problem, an analysis of a context and the perspectives that influence the whole process, i.e. ‘What?’. The stage ‘What is the basis for a solution?’ focus on values identification and their choice. The stage ‘Ways how?’ encourages to create alternatives considering values. The stage ‘Why?’ represent justification of a chosen alternative according particular issues. Above-mentioned stages including specific steps are not found in any other model of problem solving. Second, even two key stages nurture thinking about values. The specificity of the 4W framework allows expecting its successful practical application. It may help to solve a problem more informed revealing when and how the explication of values helps to reach the desired value-based solution. The particular significance is that the 4W framework can be used to develop capabilities to solve problems through values. The challenges to use the 4W framework in education are discussed.

2. Methodology

To create the 4W framework, the integrative literature review was chosen. According to Snyder (2019) , this review is ‘useful when the purpose of the review is not to cover all articles ever published on the topic but rather to combine perspectives to create new theoretical models’ (p.334). The scope of this review focused on research disclosing problem solving process that paid attention on values. The following databases were used for relevant information search: EBSCO/Hostdatabases (ERIC, Education Source), Emerald, Google Scholar. The first step of this search was conducted using integrated keywords problem solving model , problem solving process, problem solving steps . These keywords were combined with the Boolean operator AND with the second keywords values approach, value-based . The inclusion criteria were used to identify research that: presents theoretical backgrounds and/or empirical evidences; performed within the last 5 years; within an educational context; availability of full text. The sources appropriate for this review was very limited in scope (N = 2).

We implemented the second search only with the same set of the integrated keywords. The inclusion criteria were the same except the date; this criterion was extended up to 10 years. This search presented 85 different sources. After reading the summaries, introductions and conclusions of the sources found, the sources that do not explicitly provide the process/models/steps of problem solving for teaching/learning purposes and eliminates values were excluded. Aiming to see a more accurate picture of the chosen topic, we selected secondary sources from these initial sources.

Several important issues were determined as well. First, most researchers ground their studies on existing problem solving models, however, not based on values. Second, some of them conducted empirical research in order to identify the process of studies participants’ problem solving. Therefore, we included sources without date restrictions trying to identify the principal sources that reveal the process/models/steps of problem solving. Third, decision-making is a part of problem solving process. Accordingly, we performed a search with the additional keywords decision-making AND values approach, value-based decision-making . We used such inclusion criteria: presents theoretical background and/or empirical evidence; no date restriction; within an educational context; availability of full text. These all searches resulted in a total of 16 (9 theoretical and 7 empirical) sources for inclusion. They were the main sources that contributed most fruitfully for the background. We used other sources for the justification the wholeness of the 4W framework. We present the principal results of the conducted literature review in the part ‘The background of the conceptual framework’.

3. The background of the conceptual framework

3.1. different approaches of how to solve a problem.

Researchers from different fields focus on problem solving. As a result, there still seems to be a lack of a conventional definition of problem solving. Regardless of some differences, there is an agreement that problem solving is a cognitive process and one of the meaningful and significant ways of learning ( Funke, 2014 ; Jonassen, 1997 ; Mayer & Wittrock, 2006 ). Differing in approaches to solving a problem, researchers ( Collins, Sibthorp, & Gookin, 2016 ; Jonassen, 1997 ; Litzinger et al., 2010 ; Mayer & Wittrock, 2006 ; O’Loughlin & McFadzean, 1999 ; ect.) present a variety of models that differ in the number of distinct steps. What is similar in these models is that they stress the procedural process of problem solving with the focus on the development of specific skills and competences.

For the sake of this paper, we have focused on those models of problem solving that clarify the process and draw attention to values, specifically, on Huitt (1992) , Basadur, Ellspermann, and Evans (1994) , and Morton (1997) . Integrating the creative approach to problem solving, Newell and Simon (1972) presents six phases: phase 1 - identifying the problem, phase 2 - understanding the problem, phase 3 - posing solutions, phase 4 - choosing solutions, phase 5 - implementing solutions, and phase 6 - final analysis. The weakness of this model is that these phases do not necessarily follow one another, and several can coincide. However, coping with simultaneously occurring phases could be a challenge, especially if these are, for instance, phases five and six. Certainly, it may be necessary to return to the previous phases for further analysis. According to Basadur et al. (1994) , problem solving consists of problem generation, problem formulation, problem solving, and solution implementation stages. Huitt (1992) distinguishes four stages in problem solving: input, processing, output, and review. Both Huitt (1992) and Basadur et al. (1994) four-stage models emphasize a sequential process of problem solving. Thus, problem solving includes four stages that are used in education. For example, problem-based learning employs such stages as introduction of the problem, problem analysis and learning issues, discovery and reporting, solution presentation and evaluation ( Chua, Tan, & Liu, 2016 ). Even PISA 2012 framework for problem solving composes four stages: exploring and understanding, representing and formulating, planning and executing, monitoring and reflecting ( OECD, 2013 ).

Drawing on various approaches to problem solving, it is possible to notice that although each stage is named differently, it is possible to reveal some general steps. These steps reflect the essential idea of problem solving: a search for the solution from the initial state to the desirable state. The identification of a problem and its contextual elements, the generation of alternatives to a problem solution, the evaluation of these alternatives according to specific criteria, the choice of an alternative for a solution, the implementation, and monitoring of the solution are the main proceeding steps in problem solving.

3.2. Value-based approaches relevant for problem solving

Huitt (1992) suggests that important values are among the criteria for the evaluation of alternatives and the effectiveness of a chosen solution. Basadur et al. (1994) point out to visible values in the problem formulation. Morton (1997) underlines that interests, investigation, prevention, and values of all types, which may influence the process, inspire every phase of problem solving. However, the aforementioned authors do not go deeper and do not seek to disclose the significance of values for problem solving.

Decision-making research shows more possibilities for problem solving and values integration. Sheehan and Schmidt (2015) model of ethical decision-making includes moral sensitivity, moral judgment, moral motivation, and moral action where values are presented in the component of moral motivation. Another useful approach concerned with values comes from decision-making in management. It is the concept of Value-Focused Thinking (VFT) proposed by Keeney (1994) . The author argues that the goals often are merely means of achieving results in traditional models of problem solving. Such models frequently do not help to identify logical links between the problem solving goals, values, and alternatives. Thus, according to Keeney (1994) , the decision-making starts with values as they are stated in the goals and objectives of decision-makers. VFT emphasizes the core values of decision-makers that are in a specific context as well as how to find a way to achieve them by using means-ends analysis. The weakness of VFT is its restriction to this means-ends analysis. According to Shin, Jonassen, and McGee (2003) , in searching for a solution, such analysis is weak as the problem solver focuses simply on removing inadequacies between the current state and the goal state. The strengths of this approach underline that values are included in the decision before alternatives are created. Besides, values help to find creative and meaningful alternatives and to assess them. Further, they include the forthcoming consequences of the decision. As VFT emphasizes the significant function of values and clarifies the possibilities of their integration into problem solving, we adapt this approach in the current paper.

3.3. The effect of values when solving a problem

In a broader sense, values provide a direction to a person’s life. Whereas the importance of values is relatively stable over time and across situations, Roccas et al. (2017) argue that values differ in their importance to a person. Verplanken and Holland (2002) investigated the relationship between values and choices or behavior. The research revealed that the activation of a value and the centrality of a value to the self, are the essential elements for value-guided behavior. The activation of values could happen in such cases: when values are the primary focus of attention; if the situation or the information a person is confronted with implies values; when the self is activated. The centrality of a particular value is ‘the degree to which an individual has incorporated this value as part of the self’ ( Verplanken & Holland, 2002, p.436 ). Thus, the perceived importance of values and attention to them determine value-guided behavior.

According to Argandoña (2003) , values can change due to external (changing values in the people around, in society, changes in situations, etc.) and internal (internalization by learning) factors affecting the person. The research by Hall and Davis (2007) indicates that the decision-makers’ applied value profile temporarily changed as they analyzed the issue from multiple perspectives and revealed the existence of a broader set of values. The study by Kirkman (2017) reveal that participants noticed the relevance of moral values to situations they encountered in various contexts.

Values are tightly related to personal integrity and identity and guide an individual’s perception, judgment, and behavior ( Halstead, 1996 ; Schwartz, 1992 ). Sheehan and Schmidt (2015) found that values influenced ethical decision-making of accounting study programme students when they uncovered their own values and grounded in them their individual codes of conduct for future jobs. Hence, the effect of values discloses by observing the problem solver’s decision-making. The latter observations could explain the abundance of ethics-laden research in decision-making rather than in problem solving.

Contemporary researchers emphasize the creative potential of values. Dollinger et al. (2007) , Kasof et al. (2007) , Lebedeva, Schwartz, Plucker, & Van De Vijver, 2019 present to some extent similar findings as they all used Schwartz Value Survey (respectively: Schwartz, 1992 ; ( Schwartz, 1994 ), Schwartz, 2012 ). These studies disclosed that such values as self-direction, stimulation and universalism foster creativity. Kasof et al. (2007) focused their research on identified motivation. Stressing that identified motivation is the only fully autonomous type of external motivation, authors define it as ‘the desire to commence an activity as a means to some end that one greatly values’ (p.106). While identified motivation toward specific values (italic in original) fosters the search for outcomes that express those specific values, this research demonstrated that it could also inhibit creative behavior. Thus, inhibition is necessary, especially in the case where reckless creativity could have painful consequences, for example, when an architect creates a beautiful staircase without a handrail. Consequently, creativity needs to be balanced.

Ultimately, values affect human beings’ lives as they express the motivational goals ( Schwartz, 1992 ). These motivational goals are the comprehensive criteria for a person’s choices when solving problems. Whereas some problem solving models only mention values as possible evaluation criteria, but they do not give any significant suggestions when and how the problem solver could think about the values coming to the understanding that his/her values direct the decision how to solve the problem. The authors of this paper claim that the identification of personal values and their choice for a solution need to be specified in the process of problem solving. This position is clearly reflected in humanistic philosophy and psychology ( Maslow, 2011 ; Rogers, 1995 ) that emphasize personal responsibility for discovering personal values through critical questioning, honest self-esteem, self-discovery, and open-mindedness in the constant pursuit of the truth in the path of individual life. However, fundamental (of humankind) and societal values should be taken into account. McLaughlin (1997) argues that a clear boundary between societal and personal values is difficult to set as they are intertwined due to their existence in complex cultural, social, and political contexts at a particular time. A person is related to time and context when choosing values. As a result, a person assumes existing values as implicit knowledge without as much as a consideration. This is particularly evident in the current consumer society.

Moreover, McLaughlin (1997) stresses that if a particular action should be tolerated and legitimated by society, it does not mean that this action is ultimately morally acceptable in all respects. Education has possibilities to reveal this. One such possibility is to turn to the capability approach ( Sen, 1990 ), which emphasizes what people are effectively able to do and to be. Capability, according to Sen (1990) , reflects a person’s freedom to choose between various ways of living, i.e., the focus is on the development of a person’s capability to choose the life he/she has a reason to value. According to Webster (2017) , ‘in order for people to value certain aspects of life, they need to appreciate the reasons and purposes – the whys – for certain valuing’ (italic in original; p.75). As values reflect and foster these whys, education should supplement the development of capability with attention to values ( Saito, 2003 ). In order to attain this possibility, a person has to be aware of and be able to understand two facets of values. Argandoña (2003) defines them as rationality and virtuality . Rationality refers to values as the ideal of conduct and involves the development of a person’s understanding of what values and why he/she should choose them when solving a problem. Virtuality approaches values as virtues and includes learning to enable a person to live according to his/her values. However, according to McLaughlin (1997) , some people may have specific values that are deep or self-evidently essential. These values are based on fundamental beliefs about the nature and purpose of the human being. Other values can be more or less superficial as they are based on giving priority to one or the other. Thus, virtuality highlights the depth of life harmonized to fundamentally rather than superficially laden values. These approaches inform the rationale for the framework of problem solving through values.

4. The 4W framework of problem solving through values

Similar to the above-presented stages of the problem solving processes, the introduced framework by the authors of this paper revisits them (see Fig. 1 ). The framework is titled 4W as its four stages respond to such questions: Analyzing the Problem: W hat ? → Choice of the value(s): W hat is the background for the solution? → Search for the alternative w ays of the solution: How ? → The rationale for problem solution: W hy is this alternative significant ? The stages of this framework cover seven steps that reveal the logical sequence of problem solving through values.

The 4 W framework: problem solving through values.

Though systematic problem solving models are criticized for being linear and inflexible (e.g., Treffinger & Isaksen, 2005 ), the authors of this paper assume a structural view of the problem solving process due to several reasons. First, the framework enables problem solvers to understand the thorough process of problem solving through values. Second, this framework reveals the depth of each stage and step. Third, problem solving through values encourages tackling problems that have crucial consequences. Only by understanding and mastering the coherence of how problems those require a value-based approach need to be addressed, a problem solver will be able to cope with them in the future. Finally, this framework aims at helping to recognize, to underline personal values, to solve problems through thinking about values, and to take responsibility for choices, even value-based. The feedback supports a direct interrelation between stages. It shapes a dynamic process of problem solving through values.

The first stage of problem solving through values - ‘ The analysis of the problem: What? ’- consists of three steps (see Fig. 1 ). The first step is ‘ Recognizing the problematic situation and naming the problem ’. This step is performed in the following sequence. First, the problem solver should perceive the problematic situation he/she faces in order to understand it. Dostál (2015) argues that the problematic situation has the potential to become the problem necessary to be addressed. Although each problem is limited by its context, not every problematic situation turns into a problem. This is related to the problem solver’s capability and the perception of reality: a person may not ‘see’ the problem if his/her capability to perceive it is not developed ( Dorst, 2006 ; Dostál, 2015 ). Second, after the problem solver recognizes the existence of the problematic situation, the problem solver has to identify the presence or absence of the problem itself, i.e. to name the problem. This is especially important in the case of the ill-structured problems since they cannot be directly visible to the problem solver ( Jonassen, 1997 ). Consequently, this step allows to determine whether the problem solver developed or has acquired the capability to perceive the problematic situation and the problem (naming the problem).

The second step is ‘ Analysing the context of the problem as a reason for its rise ’. At this step, the problem solver aims to analyse the context of the problem. The latter is one of the external issues, and it determines the solution ( Jonassen, 2011 ). However, if more attention is paid to the solution of the problem, it diverts attention from the context ( Fields, 2006 ). The problem solver has to take into account both the conveyed and implied contextual elements in the problematic situation ( Dostál, 2015 ). In other words, the problem solver has to examine it through his/her ‘contextual lenses’ ( Hester & MacG, 2017 , p.208). Thus, during this step the problem solver needs to identify the elements that shape the problem - reasons and circumstances that cause the problem, the factors that can be changed, and stakeholders that are involved in the problematic situation. Whereas the elements of the context mentioned above are within the problematic situation, the problem solver can control many of them. Such control can provide unique ways for a solution.

Although the problem solver tries to predict the undesirable results, some criteria remain underestimated. For that reason, it is necessary to highlight values underlying the various possible goals during the analysis ( Fields, 2006 ). According to Hester and MacG (2017) , values express one of the main features of the context and direct the attention of the problem solver to a given problematic situation. Hence, the problem solver should explore the value-based positions that emerge in the context of the problem.

The analysis of these contextual elements focus not only on a specific problematic situation but also on the problem that has emerged. This requires setting boundaries of attention for an in-depth understanding ( Fields, 2006 ; Hester & MacG, 2017 ). Such understanding influences several actions: (a) the recognition of inappropriate aspects of the problematic situation; (b) the emergence of paths in which identified aspects are expected to change. These actions ensure consistency and safeguard against distractions. Thus, the problem solver can now recognize and identify the factors that influence the problem although they are outside of the problematic situation. However, the problem solver possesses no control over them. With the help of such context analysis, the problem solver constructs a thorough understanding of the problem. Moreover, the problem solver becomes ready to look at the problem from different perspectives.

The third step is ‘ Perspectives emerging in the problem ’. Ims and Zsolnai (2009) argue that problem solving usually contains a ‘problematic search’. Such a search is a pragmatic activity as the problem itself induces it. Thus, the problem solver searches for a superficial solution. As a result, the focus is on control over the problem rather than a deeper understanding of the problem itself. The analysis of the problem, especially including value-based approaches, reveals the necessity to consider the problem from a variety of perspectives. Mitroff (2000) builds on Linstone (1989) ideas and claims that a sound foundation of both naming and solving any problem lays in such perspectives: the technical/scientific, the interpersonal/social, the existential, and the systemic (see Table 1 ).

The main characteristics of four perspectives for problem solving

Whereas all problems have significant aspects of each perspective, disregarding one or another may lead to the wrong way of solving the problem. While analysing all four perspectives is essential, this does not mean that they all are equally important. Therefore, it is necessary to justify why one or another perspective is more relevant and significant in a particular case. Such analysis, according to Linstone (1989) , ‘forces us to distinguish how we are looking from what we are looking at’ (p.312; italic in original). Hence, the problem solver broadens the understanding of various perspectives and develops the capability to see the bigger picture ( Hall & Davis, 2007 ).

The problem solver aims to identify and describe four perspectives that have emerged in the problem during this step. In order to identify perspectives, the problem solver search answers to the following questions. First, regarding the technical/scientific perspective: What technical/scientific reasons are brought out in the problem? How and to what extent do they influence a problem and its context? Second, regarding the interpersonal/social perspective: What is the impact of the problem on stakeholders? How does it influence their attitudes, living conditions, interests, needs? Third, regarding the existential perspective: How does the problem affect human feelings, experiences, perception, and/or discovery of meaning? Fourth, regarding the systemic perspective: What is the effect of the problem on the person → community → society → the world? Based on the analysis of this step, the problem solver obtains a comprehensive picture of the problem. The next stage is to choose the value(s) that will address the problem.

The second stage - ‘ The choice of value(s): What is the background for the solution?’ - includes the fourth and the fifth steps. The fourth step is ‘ The identification of value(s) as a base for the solution ’. During this step, the problem solver should activate his/her value(s) making it (them) explicit. In order to do this, the problem solver proceeds several sub-steps. First, the problem solver reflects taking into account the analysis done in previous steps. He/she raises up questions revealing values that lay in the background of this analysis: What values does this analyzed context allow me to notice? What values do different perspectives of the problem ‘offer’? Such questioning is important as values are deeply hidden ( Verplanken & Holland, 2002 ) and they form a bias, which restricts the development of the capability to see from various points of view ( Hall & Paradice, 2007 ). In the 4W framework, this bias is relatively eliminated due to the analysis of the context and exploration of the perspectives of a problem. As a result, the problem solver discovers distinct value-based positions and gets an opportunity to identify the ‘value uncaptured’ ( Yang, Evans, Vladimirova, & Rana, 2017, p.1796 ) within the problem analyzed. The problem solver observes that some values exist in the context (the second step) and the disclosed perspectives (the third step). Some of the identified values do not affect the current situation as they are not required, or their potential is not exploited. Thus, looking through various value-based lenses, the problem solver can identify and discover a congruence between the opportunities offered by the values in the problem’s context, disclosed perspectives and his/her value(s). Consequently, the problem solver decides what values he/she chooses as a basis for the desired solution. Since problems usually call for a list of values, it is important to find out their order of priority. Thus, the last sub-step requires the problem solver to choose between fundamentally and superficially laden values.

In some cases, the problem solver identifies that a set of values (more than one value) can lead to the desired solution. If a person chooses this multiple value-based position, two options emerge. The first option is concerned with the analysis of each value-based position separately (from the fifth to the seventh step). In the second option, a person has to uncover which of his/her chosen values are fundamentally laden and which are superficially chosen, considering the desired outcome in the current situation. Such clarification could act as a strategy where the path for the desired solution is possible going from superficially chosen value(s) to fundamentally laden one. When a basis for the solution is established, the problem solver formulates the goal for the desired solution.

The fifth step is ‘ The formulation of the goal for the solution ’. Problem solving highlights essential points that reveal the structure of a person’s goals; thus, a goal is the core element of problem solving ( Funke, 2014 ). Meantime, values reflect the motivational content of the goals ( Schwartz, 1992 ). The attention on the chosen value not only activates it, but also motivates the problem solver. The motivation directs the formulation of the goal. In such a way, values explicitly become a basis of the goal for the solution. Thus, this step involves the problem solver in formulating the goal for the solution as the desired outcome.

The way how to take into account value(s) when formulating the goal is the integration of value(s) chosen by the problem solver in the formulation of the goal ( Keeney, 1994 ). For this purpose the conjunction of a context for a solution (it is analyzed during the second step) and a direction of preference (the chosen value reveals it) serves for the formulation of the goal (that represents the desired solution). In other words, a value should be directly included into the formulation of the goal. The goal could lose value, if value is not included into the goal formulation and remains only in the context of the goal. Let’s take the actual example concerning COVID-19 situation. Naturally, many countries governments’ preference represents such value as human life (‘it is important of every individual’s life’). Thus, most likely the particular country government’s goal of solving the COVID situation could be to save the lifes of the country people. The named problem is a complex where the goal of its solution is also complex, although it sounds simple. However, if the goal as desired outcome is formulated without the chosen value, this value remains in the context and its meaning becomes tacit. In the case of above presented example - the goal could be formulated ‘to provide hospitals with the necessary equipment and facilities’. Such goal has the value ‘human’s life’ in the context, but eliminates the complexity of the problem that leads to a partial solution of the problem. Thus, this step from the problem solver requires caution when formulating the goal as the desired outcome. For this reason, maintaining value is very important when formulating the goal’s text. To avoid the loss of values and maintain their proposed direction, is necessary to take into account values again when creating alternatives.

The third stage - ‘ Search for the alternative ways for a solution: How? ’ - encompasses the sixth step, which is called ‘ Creation of value-based alternatives ’. Frequently problem solver invokes a traditional view of problem identification, generation of alternatives, and selection of criteria for evaluating findings. Keeney (1994) ; Ims and Zsolnai (2009) criticize this rational approach as it supports a search for a partial solution where an active search for alternatives is neglected. Moreover, a problematic situation, according to Perkins (2009) , can create the illusion of a fully framed problem with some apparent weighting and some variations of choices. In this case, essential and distinct alternatives to the solution frequently become unnoticeable. Therefore, Perkins (2009) suggest to replace the focus on the attempts to comprehend the problem itself. Thinking through the ‘value lenses’ offers such opportunities. The deep understanding of the problem leads to the search for the alternative ways of a solution.

Thus, the aim of this step is for the problem solver to reveal the possible alternative ways for searching a desired solution. Most people think they know how to create alternatives, but often without delving into the situation. First of all, the problem solver based on the reflection of (but not limited to) the analysis of the context and the perspectives of the problem generates a range of alternatives. Some of these alternatives represent anchored thinking as he/she accepts the assumptions implicit in generated alternatives and with too little focus on values.

The chosen value with the formulated goal indicates direction and encourages a broader and more creative search for a solution. Hence, the problem solver should consider some of the initial alternatives that could best support the achievement of the desired solution. Values are the principles for evaluating the desirability of any alternative or outcome ( Keeney, 1994 ). Thus, planned actions should reveal the desirable mode of conduct. After such consideration, he/she should draw up a plan setting out the actions required to implement each of considered alternatives.

Lastly, after a thorough examination of each considered alternative and a plan of its implementation, the problem solver chooses one of them. If the problem solver does not see an appropriate alternative, he/she develops new alternatives. However, the problem solver may notice (and usually does) that more than one alternative can help him/her to achieve the desired solution. In this case, he/she indicates which alternative is the main one and has to be implemented in the first place, and what other alternatives and in what sequence will contribute in searching for the desired solution.

The fourth stage - ‘ The rationale for the solution: Why ’ - leads to the seventh step: ‘ The justification of the chosen alternative ’. Keeney (1994) emphasizes the compatibility of alternatives in question with the values that guide the action. This underlines the importance of justifying the choices a person makes where the focus is on taking responsibility. According to Zsolnai (2008) , responsibility means a choice, i.e., the perceived responsibility essentially determines its choice. Responsible justification allows for discovering optimal balance when choosing between distinct value-based alternatives. It also refers to the alternative solution that best reflects responsibility in a particular value context, choice, and implementation.

At this stage, the problem solver revisits the chosen solution and revises it. The problem solver justifies his/her choice based on the following questions: Why did you choose this? Why is this alternative significant looking from the technical/scientific, the interpersonal/social, the existential, and the systemic perspectives? Could you take full responsibility for the implementation of this alternative? Why? How clearly do envisaged actions reflect the goal of the desired solution? Whatever interests and for what reasons do this alternative satisfies in principle? What else do you see in the chosen alternative?

As mentioned above, each person gives priority to one aspect or another. The problem solver has to provide solid arguments for the justification of the chosen alternative. The quality of arguments, according to Jonassen (2011) , should be judged based on the quality of the evidence supporting the chosen alternative and opposing arguments that can reject solutions. Besides, the pursuit of value-based goals reflects the interests of the individual or collective interests. Therefore, it becomes critical for the problem solver to justify the level of responsibility he/she takes in assessing the chosen alternative. Such a complex evaluation of the chosen alternative ensures the acceptance of an integral rather than unilateral solution, as ‘recognizing that, in the end, people benefit most when they act for the common good’ ( Sternberg, 2012, p.46 ).

5. Discussion

The constant emphasis on thinking about values as explicit reasoning in the 4W framework (especially from the choice of the value(s) to the rationale for problem solution) reflects the pursuit of virtues. Virtues form the features of the character that are related to the choice ( Argandoña, 2003 ; McLaughlin, 2005 ). Hence, the problem solver develops value-grounded problem solving capability as the virtuality instead of employing rationality for problem solving.

Argandoña (2003) suggests that, in order to make a sound valuation process of any action, extrinsic, transcendent, and intrinsic types of motives need to be considered. They cover the respective types of values. The 4W framework meets these requirements. An extrinsic motive as ‘attaining the anticipated or expected satisfaction’ ( Argandoña, 2003, p.17 ) is reflected in the formulation of the goal of the solution, the creation of alternatives and especially in the justification of the chosen alternative way when the problem solver revisits the external effect of his/her possible action. Transcendent motive as ‘generating certain effects in others’ ( Argandoña, 2003, p.17 ) is revealed within the analysis of the context, perspectives, and creating alternatives. When the learner considers the creation of alternatives and revisits the chosen alternative, he/she pays more attention to these motives. Two types of motives mentioned so far are closely related to an intrinsic motive that emphasizes learning development within the problem solver. These motives confirm that problem solving is, in fact, lifelong learning. In light of these findings, the 4W framework is concerned with some features of value internalization as it is ‘a psychological outcome of conscious mind reasoning about values’ ( Yazdani & Akbarilakeh, 2017, p.1 ).

The 4W framework is complicated enough in terms of learning. One issue is concerned with the educational environments ( Jucevičienė, 2008 ) required to enable the 4W framework. First, the learning paradigm, rather than direct instruction, lies at the foundation of such environments. Second, such educational environments include the following dimensions: (1) educational goal; (2) learning capacity of the learners; (3) educational content relevant to the educational goal: ways and means of communicating educational content as information presented in advance (they may be real, people among them, as well as virtual); (5) methods and means of developing educational content in the process of learners’ performance; (6) physical environment relevant to the educational goal and conditions of its implementation as well as different items in the environment; (7) individuals involved in the implementation of the educational goal.

Another issue is related to exercising this framework in practice. Despite being aware of the 4W framework, a person may still not want to practice problem solving through values, since most of the solutions are going to be complicated, or may even be painful. One idea worth looking into is to reveal the extent to which problem solving through values can become a habit of mind. Profound focus on personal values, context analysis, and highlighting various perspectives can involve changes in the problem solver’s habit of mind. The constant practice of problem solving through values could first become ‘the epistemic habit of mind’ ( Mezirow, 2009, p.93 ), which means a personal way of knowing things and how to use that knowledge. This echoes Kirkman (2017) findings. The developed capability to notice moral values in situations that students encountered changed some students’ habit of mind as ‘for having “ruined” things by making it impossible not to attend to values in such situations!’ (the feedback from one student; Kirkman, 2017, p.12 ). However, this is not enough, as only those problems that require a value-based approach are addressed. Inevitably, the problem solver eventually encounters the challenges of nurturing ‘the moral-ethical habit of mind’ ( Mezirow, 2009, p.93 ). In pursuance to develop such habits of mind, the curriculum should include the necessity of the practising of the 4W framework.

Thinking based on values when solving problems enables the problem solver to engage in thoughtful reflection in contrast to pragmatic and superficial thinking supported by the consumer society. Reflection begins from the first stage of the 4W framework. As personal values are the basis for the desired solution, the problem solver is also involved in self-reflection. The conscious and continuous reflection on himself/herself and the problematic situation reinforce each step of the 4W framework. Moreover, the fourth stage (‘The rationale for the solution: Why’) involves the problem solver in critical reflection as it concerned with justification of ‘the why , the reasons for and the consequences of what we do’ (italic, bold in original; Mezirow, 1990, p.8 ). Exercising the 4W framework in practice could foster reflective practice. Empirical evidence shows that reflective practice directly impacts knowledge, skills and may lead to changes in personal belief systems and world views ( Slade, Burnham, Catalana, & Waters, 2019 ). Thus, with the help of reflective practice it is possible to identify in more detail how and to what extent the 4W framework has been mastered, what knowledge gained, capabilities developed, how point of views changed, and what influence the change process.

Critical issues related to the development of problem solving through values need to be distinguished when considering and examining options for the implementation of the 4W framework at educational institutions. First, the question to what extent can the 4W framework be incorporated into various subjects needs to be answered. Researchers could focus on applying the 4W framework to specific subjects in the humanities and social sciences. The case is with STEM subjects. Though value issues of sustainable development and ecology are of great importance, in reality STEM teaching is often restricted to the development of knowledge and skills, leaving aside the thinking about values. The special task of the researchers is to help practitioners to apply the 4W framework in STEM subjects. Considering this, researchers could employ the concept of ‘dialogic space’ ( Wegerif, 2011, p.3 ) which places particular importance of dialogue in the process of education emphasizing both the voices of teachers and students, and materials. In addition, the dimensions of educational environments could be useful aligning the 4W framework with STEM subjects. As STEM teaching is more based on solving various special tasks and/or integrating problem-based learning, the 4W framework could be a meaningful tool through which content is mastered, skills are developed, knowledge is acquired by solving pre-prepared specific tasks. In this case, the 4W framework could act as a mean addressing values in STEM teaching.

Second is the question of how to enable the process of problem solving through values. In the current paper, the concept of enabling is understood as an integral component of the empowerment. Juceviciene et al. (2010) specify that at least two perspectives can be employed to explain empowerment : a) through the power of legitimacy (according to Freire, 1996 ); and b) through the perspective of conditions for the acquisition of the required knowledge, capabilities, and competence, i.e., enabling. In this paper the 4W framework does not entail the issue of legitimacy. This issue may occur, for example, when a teacher in economics is expected to provide students with subject knowledge only, rather than adding tasks that involve problem solving through values. Yet, the issue of legitimacy is often implicit. A widespread phenomenon exists that teaching is limited to certain periods that do not have enough time for problem solving through values. The issue of legitimacy as an organizational task that supports/or not the implementation of the 4W framework in any curriculum is a question that calls for further discussion.

Third (if not the first), the issue of an educator’s competence to apply such a framework needs to be addressed. In order for a teacher to be a successful enabler, he/she should have the necessary competence. This is related to the specific pedagogical knowledge and skills, which are highly dependent on the peculiarities of the subject being taught. Nowadays actualities are encouraging to pay attention to STEM subjects and their teacher training. For researchers and teacher training institutions, who will be interested in implementing the 4W framework in STEM subjects, it would be useful to draw attention to ‘a material-dialogic approach to pedagogy’ ( Hetherington & Wegerif, 2018, p.27 ). This approach creates the conditions for a deep learning of STEM subjects revealing additional opportunities for problem solving through values in teaching. Highlighting these opportunities is a task for further research.

In contrast to traditional problem solving models, the 4W framework is more concerned with educational purposes. The prescriptive approach to teaching ( Thorne, 1994 ) is applied to the 4W framework. This approach focuses on providing guidelines that enable students to make sound decisions by making explicit value judgements. The limitation is that the 4W framework is focused on thinking but not executing. It does not include the fifth stage, which would focus on the execution of the decision how to solve the problem. This stage may contain some deviation from the predefined process of the solution of the problem.

6. Conclusions

The current paper focuses on revealing the essence of the 4W framework, which is based on enabling the problem solver to draw attention to when, how, and why it is essential to think about values during the problem solving process from the perspective of it’s design. Accordingly, the 4W framework advocates the coherent approach when solving a problem by using a creative potential of values.

The 4W framework allows the problem solver to look through the lens of his/her values twice. The first time, while formulating the problem solving goal as the desired outcome. The second time is when the problem solver looks deeper into his/her values while exploring alternative ways to solve problems. The problem solver is encouraged to reason about, find, accept, reject, compare values, and become responsible for the consequences of the choices grounded on his/her values. Thus, the problem solver could benefit from the 4W framework especially when dealing with issues having crucial consequences.

An educational approach reveals that the 4W framework could enable the development of value-grounded problem solving capability. As problem solving encourages the development of higher-order thinking skills, the consistent inclusion of values enriches them.

The 4W framework requires the educational environments for its enablement. The enablement process of problem solving through values could be based on the perspective of conditions for the acquisition of the required knowledge and capability. Continuous practice of this framework not only encourages reflection, but can also contribute to the creation of the epistemic habit of mind. Applying the 4W framework to specific subjects in the humanities and social sciences might face less challenge than STEM ones. The issue of an educator’s competence to apply such a framework is highly important. The discussed issues present significant challenges for researchers and educators. Caring that the curriculum of different courses should foresee problem solving through values, both practicing and empirical research are necessary.

Declaration of interests

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Both authors have approved the final article.

• Argandoña A. Fostering values in organizations. Journal of Business Ethics. 2003; 45 (1–2):15–28. https://link.springer.com/content/pdf/10.1023/A:1024164210743.pdf [ Google Scholar ]
• Barber S. A truly “Transformative” MBA: Executive education for the fourth industrial revolution. Journal of Pedagogic Development. 2018; 8 (2):44–55. [ Google Scholar ]
• Barnett R. McGraw-Hill Education; UK): 2007. Will to learn: Being a student in an age of uncertainty. [ Google Scholar ]
• Baron R.A., Zhao H., Miao Q. Personal motives, moral disengagement, and unethical decisions by entrepreneurs: Cognitive mechanisms on the “slippery slope” Journal of Business Ethics. 2015; 128 (1):107–118. doi: 10.1007/s10551-014-2078-y. [ CrossRef ] [ Google Scholar ]
• Basadur M., Ellspermann S.J., Evans G.W. A new methodology for formulating ill-structured problems. Omega. 1994; 22 (6):627–645. doi: 10.1016/0305-0483(94)90053-1. [ CrossRef ] [ Google Scholar ]
• Blanco E., Schirmbeck F., Costa C. International Conference on Remote Engineering and Virtual Instrumentation . Springer; Cham: 2018. Vocational Education for the Industrial Revolution; pp. 649–658. [ Google Scholar ]
• Chua B.L., Tan O.S., Liu W.C. Journey into the problem-solving process: Cognitive functions in a PBL environment. Innovations in Education and Teaching International. 2016; 53 (2):191–202. doi: 10.1080/14703297.2014.961502. [ CrossRef ] [ Google Scholar ]
• Collins R.H., Sibthorp J., Gookin J. Developing ill-structured problem-solving skills through wilderness education. Journal of Experiential Education. 2016; 39 (2):179–195. doi: 10.1177/1053825916639611. [ CrossRef ] [ Google Scholar ]
• Csapó B., Funke J., editors. The nature of problem solving: Using research to inspire 21st century learning. OECD Publishing; 2017. The development and assessment of problem solving in 21st-century schools. (Chapter 1). [ CrossRef ] [ Google Scholar ]
• Dollinger S.J., Burke P.A., Gump N.W. Creativity and values. Creativity Research Journal. 2007; 19 (2-3):91–103. doi: 10.1080/10400410701395028. [ CrossRef ] [ Google Scholar ]
• Donovan S.J., Guss C.D., Naslund D. Improving dynamic decision making through training and self-reflection. Judgment and Decision Making. 2015; 10 (4):284–295. http://digitalcommons.unf.edu/apsy_facpub/2 [ Google Scholar ]
• Dorst K. Design problems and design paradoxes. Design Issues. 2006; 22 (3):4–17. doi: 10.1162/desi.2006.22.3.4. [ CrossRef ] [ Google Scholar ]
• Dostál J. Theory of problem solving. Procedia-Social and Behavioral Sciences. 2015; 174 :2798–2805. doi: 10.1016/j.sbspro.2015.01.970. [ CrossRef ] [ Google Scholar ]
• Fields A.M. Ill-structured problems and the reference consultation: The librarian’s role in developing student expertise. Reference Services Review. 2006; 34 (3):405–420. doi: 10.1108/00907320610701554. [ CrossRef ] [ Google Scholar ]
• Freire P. Continuum; New York: 1996. Pedagogy of the oppressed (revised) [ Google Scholar ]
• Funke J. Problem solving: What are the important questions?. Proceedings of the 36th Annual Conference of the Cognitive Science Society; Austin, TX: Cognitive Science Society; 2014. pp. 493–498. [ Google Scholar ]
• Hall D.J., Davis R.A. Engaging multiple perspectives: A value-based decision-making model. Decision Support Systems. 2007; 43 (4):1588–1604. doi: 10.1016/j.dss.2006.03.004. [ CrossRef ] [ Google Scholar ]
• Hall D.J., Paradice D. Investigating value-based decision bias and mediation: do you do as you think? Communications of the ACM. 2007; 50 (4):81–85. [ Google Scholar ]
• Halstead J.M. Values and values education in schools. In: Halstead J.M., Taylor M.J., editors. Values in education and education in values. The Falmer Press; London: 1996. pp. 3–14. [ Google Scholar ]
• Harland T., Pickering N. Routledge; 2010. Values in higher education teaching. [ Google Scholar ]
• Hester P.T., MacG K. Springer; New York: 2017. Systemic decision making: Fundamentals for addressing problems and messes. [ Google Scholar ]
• Hetherington L., Wegerif R. Developing a material-dialogic approach to pedagogy to guide science teacher education. Journal of Education for Teaching. 2018; 44 (1):27–43. doi: 10.1080/02607476.2018.1422611. [ CrossRef ] [ Google Scholar ]
• Huitt W. Problem solving and decision making: Consideration of individual differences using the Myers-Briggs type indicator. Journal of Psychological Type. 1992; 24 (1):33–44. [ Google Scholar ]
• Ims K.J., Zsolnai L. The future international manager. Palgrave Macmillan; London: 2009. Holistic problem solving; pp. 116–129. [ Google Scholar ]
• Jonassen D. Supporting problem solving in PBL. Interdisciplinary Journal of Problem-based Learning. 2011; 5 (2):95–119. doi: 10.7771/1541-5015.1256. [ CrossRef ] [ Google Scholar ]
• Jonassen D.H. Instructional design models for well-structured and III-structured problem-solving learning outcomes. Educational Technology Research and Development. 1997; 45 (1):65–94. doi: 10.1007/BF02299613. [ CrossRef ] [ Google Scholar ]
• Jucevičienė P. Educational and learning environments as a factor for socioeducational empowering of innovation. Socialiniai mokslai. 2008; 1 :58–70. [ Google Scholar ]
• Jucevičienė P., Gudaitytė D., Karenauskaitė V., Lipinskienė D., Stanikūnienė B., Tautkevičienė G. Technologija; Kaunas: 2010. Universiteto edukacinė galia: Atsakas XXI amžiaus iššūkiams [The educational power of university: the response to the challenges of the 21st century] [ Google Scholar ]
• Kasof J., Chen C., Himsel A., Greenberger E. Values and creativity. Creativity Research Journal. 2007; 19 (2–3):105–122. doi: 10.1080/10400410701397164. [ CrossRef ] [ Google Scholar ]
• Keeney R.L. Creativity in decision making with value-focused thinking. MIT Sloan Management Review. 1994; 35 (4):33–41. [ Google Scholar ]
• Kirkman R. Problem-based learning in engineering ethics courses. Interdisciplinary Journal of Problem-based Learning. 2017; 11 (1) doi: 10.7771/1541-5015.1610. [ CrossRef ] [ Google Scholar ]
• Lebedeva N., Schwartz S., Plucker J., Van De Vijver F. Domains of everyday creativity and personal values. Frontiers in Psychology. 2019; 9 :1–16. doi: 10.3389/fpsyg.2018.02681. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Linstone H.A. Multiple perspectives: Concept, applications, and user guidelines. Systems Practice. 1989; 2 (3):307–331. [ Google Scholar ]
• Litzinger T.A., Meter P.V., Firetto C.M., Passmore L.J., Masters C.B., Turns S.R.…Zappe S.E. A cognitive study of problem solving in statics. Journal of Engineering Education. 2010; 99 (4):337–353. [ Google Scholar ]
• Maslow A.H. Vaga; Vilnius: 2011. Būties psichologija. [Psychology of Being] [ Google Scholar ]
• Mayer R., Wittrock M. Problem solving. In: Alexander P., Winne P., editors. Handbook of educational psychology. Psychology Press; New York, NY: 2006. pp. 287–303. [ Google Scholar ]
• McLaughlin T. The educative importance of ethos. British Journal of Educational Studies. 2005; 53 (3):306–325. doi: 10.1111/j.1467-8527.2005.00297.x. [ CrossRef ] [ Google Scholar ]
• McLaughlin T.H. Technologija; Kaunas: 1997. Šiuolaikinė ugdymo filosofija: demokratiškumas, vertybės, įvairovė [Contemporary philosophy of education: democracy, values, diversity] [ Google Scholar ]
• Mezirow J. Jossey-Bass Publishers; San Francisco: 1990. Fostering critical reflection in adulthood; pp. 1–12. https://my.liberatedleaders.com.au/wp-content/uploads/2017/02/How-Critical-Reflection-triggers-Transformative-Learning-Mezirow.pdf [ Google Scholar ]
• Mezirow J. Contemporary theories of learning. Routledge; 2009. An overview on transformative learning; pp. 90–105. (Chapter 6) [ Google Scholar ]
• Mitroff I. Šviesa; Kaunas: 2000. Kaip neklysti šiais beprotiškais laikais: ar mokame spręsti esmines problemas. [How not to get lost in these crazy times: do we know how to solve essential problems] [ Google Scholar ]
• Morton L. Teaching creative problem solving: A paradigmatic approach. Cal. WL Rev. 1997; 34 :375. [ Google Scholar ]
• Nadda P. Need for value based education. International Education and Research Journal. 2017; 3 (2) http://ierj.in/journal/index.php/ierj/article/view/690/659 [ Google Scholar ]
• Newell A., Simon H.A. Prentice-Hall; Englewood Cliffs, NJ: 1972. Human problem solving. [ Google Scholar ]
• OECD . PISA, OECD Publishing; Paris: 2013. PISA 2012 assessment and analytical framework: Mathematics, reading, science, problem solving and financial literacy . https://www.oecd.org/pisa/pisaproducts/PISA%202012%20framework%20e-book_final.pdf [ Google Scholar ]
• OECD . PISA, OECD Publishing; 2018. PISA 2015 results in focus . https://www.oecd.org/pisa/pisa-2015-results-in-focus.pdf [ Google Scholar ]
• O’Loughlin A., McFadzean E. Toward a holistic theory of strategic problem solving. Team Performance Management: An International Journal. 1999; 5 (3):103–120. [ Google Scholar ]
• Perkins D.N. Decision making and its development. In: Callan E., Grotzer T., Kagan J., Nisbett R.E., Perkins D.N., Shulman L.S., editors. Education and a civil society: Teaching evidence-based decision making. American Academy of Arts and Sciences; Cambridge, MA: 2009. pp. 1–28. (Chapter 1) [ Google Scholar ]
• Roccas S., Sagiv L., Navon M. Values and behavior. Cham: Springer; 2017. Methodological issues in studying personal values; pp. 15–50. [ Google Scholar ]
• Rogers C.R. Houghton Mifflin Harcourt; Boston: 1995. On becoming a person: A therapist’s view of psychotherapy. [ Google Scholar ]
• Saito M. Amartya Sen’s capability approach to education: A critical exploration. Journal of Philosophy of Education. 2003; 37 (1):17–33. doi: 10.1111/1467-9752.3701002. [ CrossRef ] [ Google Scholar ]
• Schwartz S.H. Universals in the content and structure of values: Theoretical advances and empirical tests in 20 countries. In: Zanna M.P., editor. Vol. 25. Academic Press; 1992. pp. 1–65. (Advances in experimental social psychology). [ Google Scholar ]
• Schwartz S.H. Are there universal aspects in the structure and contents of human values? Journal of social issues. 1994; 50 (4):19–45. [ Google Scholar ]
• Schwartz S.H. An overview of the Schwartz theory of basic values. Online Readings in Psychology and Culture. 2012; 2 (1):1–20. doi: 10.9707/2307-0919.1116. [ CrossRef ] [ Google Scholar ]
• Sen A. Development as capability expansion. The community development reader. 1990:41–58. http://www.masterhdfs.org/masterHDFS/wp-content/uploads/2014/05/Sen-development.pdf [ Google Scholar ]
• Sheehan N.T., Schmidt J.A. Preparing accounting students for ethical decision making: Developing individual codes of conduct based on personal values. Journal of Accounting Education. 2015; 33 (3):183–197. doi: 10.1016/j.jaccedu.2015.06.001. [ CrossRef ] [ Google Scholar ]
• Shepherd D.A., Patzelt H., Baron R.A. “I care about nature, but…”: Disengaging values in assessing opportunities that cause harm. The Academy of Management Journal. 2013; 56 (5):1251–1273. doi: 10.5465/amj.2011.0776. [ CrossRef ] [ Google Scholar ]
• Shin N., Jonassen D.H., McGee S. Predictors of well‐structured and ill‐structured problem solving in an astronomy simulation. Journal of Research in Science Teaching. 2003; 40 (1):6–33. doi: 10.1002/tea.10058. [ CrossRef ] [ Google Scholar ]
• Slade M.L., Burnham T.J., Catalana S.M., Waters T. The impact of reflective practice on teacher candidates’ learning. International Journal for the Scholarship of Teaching and Learning. 2019; 13 (2):15. doi: 10.20429/ijsotl.2019.130215. [ CrossRef ] [ Google Scholar ]
• Snyder H. Literature review as a research methodology: An overview and guidelines. Journal of Business Research. 2019; 104 :333–339. doi: 10.1016/j.jbusres.2019.07.039. [ CrossRef ] [ Google Scholar ]
• Sternberg R. Teaching for ethical reasoning. International Journal of Educational Psychology. 2012; 1 (1):35–50. doi: 10.4471/ijep.2012.03. [ CrossRef ] [ Google Scholar ]
• Sternberg R. Speculations on the role of successful intelligence in solving contemporary world problems. Journal of Intelligence. 2017; 6 (1):4. doi: 10.3390/jintelligence6010004. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Thorne D.M. Environmental ethics in international business education: Descriptive and prescriptive dimensions. Journal of Teaching in International Business. 1994; 5 (1–2):109–122. doi: 10.1300/J066v05n01_08. [ CrossRef ] [ Google Scholar ]
• Treffinger D.J., Isaksen S.G. Creative problem solving: The history, development, and implications for gifted education and talent development. The Gifted Child Quarterly. 2005; 49 (4):342–353. doi: 10.1177/001698620504900407. [ CrossRef ] [ Google Scholar ]
• Verplanken B., Holland R.W. Motivated decision making: Effects of activation and self-centrality of values on choices and behavior. Journal of Personality and Social Psychology. 2002; 82 (3):434–447. doi: 10.1037/0022-3514.82.3.434. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Webster R.S. Re-enchanting education and spiritual wellbeing. Routledge; 2017. Being spiritually educated; pp. 73–85. [ Google Scholar ]
• Wegerif R. Towards a dialogic theory of how children learn to think. Thinking Skills and Creativity. 2011; 6 (3):179–190. doi: 10.1016/j.tsc.2011.08.002. [ CrossRef ] [ Google Scholar ]
• Yang M., Evans S., Vladimirova D., Rana P. Value uncaptured perspective for sustainable business model innovation. Journal of Cleaner Production. 2017; 140 :1794–1804. doi: 10.1016/j.jclepro.2016.07.102. [ CrossRef ] [ Google Scholar ]
• Yazdani S., Akbarilakeh M. The model of value-based curriculum for medicine and surgery education in Iran. Journal of Minimally Invasive Surgical Sciences. 2017; 6 (3) doi: 10.5812/minsurgery.14053. [ CrossRef ] [ Google Scholar ]
• Zsolnai L. Transaction Publishers; New Brunswick and London: 2008. Responsible decision making. [ Google Scholar ]

• Open access
• Published: 05 February 2018

The role of problem solving ability on innovative behavior and opportunity recognition in university students

• Ji Young Kim 1 ,
• Dae Soo Choi 1 ,
• Chang-Soo Sung 1 &
• Joo Y. Park 2  

Journal of Open Innovation: Technology, Market, and Complexity volume  4 , Article number:  4 ( 2018 ) Cite this article

24k Accesses

30 Citations

1 Altmetric

Metrics details

Universities engage in entrepreneurship education to increase social value creation, through students’ new opportunities recognition. However, there are not enough of empirical researches on whether the current entrepreneurship education can be differentiated from other curriculum to improve the opportunity recognition process. This study argues that it is very important for cognitive abilities to be manifested as behavior when students in university are new opportunities recognition. For this purpose, the relationship between problem solving ability, innovation behavior, and opportunity perception was verified empirically. This study was conducted on 203 students who took entrepreneurship education courses at Korean universities. The results of this study showed that problem solving ability positively influenced innovation behavior and opportunity perception. Innovation behavior was identified as a key parameter that partially mediated the relationship between problem solving ability and innovation behavior. The implication of this study is to prove the relationship between individual ‘s problem - solving ability considering the characteristics of education in Korea and the opportunity through innovative behavior and various learning strategies to help entrepreneurship education to design better courses for the future It has important implications for strategic pedagogy that can enhance behavioral elements in development.

It is the new opportunity recognition that all firms focus on for a new economic paradigm (Ancona and Caldwell, 1992 ). Recognizing high opportunities can significantly improve profit, growth, and / or competitive positioning. And this new opportunity leads to innovation. From a conceptual point of view, research is continuing on the question of ‘what is opportunity’ and ‘where is opportunity’ (Gartner and Carter, 2003 ; Venkataraman & Sarasvathy, 2001 ). Research on the discovery and realization of new opportunities is a very important research area that suggests how to discover and utilize creative opportunities that create new value and profit for pre-service workers, and is the ultimate goal of entrepreneurship education. (Kim et al., 2016 ). Particularly, there is a lot of debate about the relationship between opportunity perception and personal characteristics. Despite many arguments, however, research on individual characteristics and opportunity perceptions is still insufficient, and a unified opinion has not been created due to differences between cognitive and behavioral theories (Ko & Butler, 2003 ). In particular, there is much controversy over the relationship between opportunity recognition and personal traits, and research has been continuing to demonstrate that organizational learning in organizations can influence opportunity recognition (Shane & Venkataraman, 2000 ). In particular, learning enhances cognitive ability, which is an opportunity that leads to opportunity recognition through the manifestation of behavior (Lumpkin and Dess, 2004 ). Many studies have also demonstrated the difference in behavior that successful entrepreneurs see as contributing to their ability to recognize opportunities and create innovative business ideas (Dyer et al., 2008 ; Kim et al., 2017 ). For example, Alvarez and Barney ( 2005 ) argue for mountain climbing and mountain building to understand the implications of entrepreneurial behavior in relation to these theories. In other words, a new opportunity for entrepreneurs is not a passive case that is generally found and climbed by climbers such as mountains, but rather by the actions of entrepreneurs, creating competition for the market, creating another market, Is the same. Therefore, in order for a person’s cognitive ability to recognize a new opportunity, it must focus on manifesting an action that can realize an innovative idea. In this regard, Kanter ( 1988 ) proved the relationship between new opportunity recognition and those with innovative tendencies and regarded this new opportunity recognition as innovation activity through organizational education. Scott and Bruce ( 1994 ) have integrated a number of research flows into innovation pioneers to develop and test individual innovative behavioral models. In particular, they argued that individual problem-solving styles are very important to induce innovative behavior. Although there are a number of studies on problem solving ability, innovation behavior, and new opportunities, most of the opportunistic researches have been conducted in organizational units of companies. Is still insufficient. Furthermore, unified opinions were not created due to differences between cognitive theory and behavioral theory (Ko & Butler, 2003 ). It is also true that the effects of entrepreneurship education in university have not been studied empirically because they are mainly focused on promoting cognitive ability and applied to various kinds of teaching methods.

This study argues that it is very important for cognitive abilities to be manifested as behavior that. “Through” courses, In other words, it is very important to induce students to act through ‘learning through process’ learning through behavioral learning by providing students with some (virtual or real) business to start doing some of the actions of the entrepreneur. When students in university are new opportunity recognition. Especially, entrepreneurship education, which ultimately focuses on whether it is a new opportunity, is very important to induce behavior through behavior learning beyond the cognitive ability as the general education curriculum. Particularly, innovative behaviors that create and realize innovative ideas are very important for new opportunity recognition (Paine & Organ, 2000 ).In order to achieve this, various kinds of teaching methods are being pursued in the university, but studies on the effectiveness of behavioral learning have not been studied yet. In this study, we are based on team-based learning among various teaching methods for behavior learning that leads to innovative behaviors. Team learning instructional activity sequence designed by Michaelsen and Sweet ( 2008 ), the most well known team-based learning in entrepreneurship education as in class-primarily group work and outside class-primarily individual work. In this way, we demonstrate empirically the relationship between individual problem solving ability and opportunity through innovative behavior, and develop a variety of learning strategies that help entrepreneurship education to design better courses for the future. I would like to point out some implications for strategic pedagogy to increase the element.

The paper proceeds as follows: Initially we present the theory of innovative behavior with individual problem-solving ability, innovative behavior and opportunity recognition. We develop hypotheses to confirm its basic predictions in the student context. Finally, we link the findings with the wider social effect of entrepreneurship literature and highlight the theoretical contributions and practical implications.

Theoretical background

‘opportunity recognition’ as entrepreneurship education unit of analysis.

A commonly focused analysis in entrepreneurship research over the last 30 years has been the ‘opportunity’, most simply defined as any situation in which new products or services can be development of production (Casson, 1982 ; Shane & Venkataraman, 2000 ; Venkataraman, 1997 ). The definition of opportunity recognition is defined in many ways, but opportunity is defined as a perceived means of generating economic value (ie, profit) that has not been exploited previously and is not currently exploited by others. If opportunity is defined in this way, opportunity recognition can be defined as a cognitive process (or process) that concludes that an individual has identified an opportunity (Baron and Ensley, 2006 ). Kirzner ( 1997 ) pointed out that the distribution of information in society affects the discovery of entrepreneurial opportunities and that only a few individuals can identify and recognize specific opportunities in the market. The process of finding opportunities also depends on the individual’s ability and discovery (Stevenson & Gumpert, 1985 ). For example, people may miss opportunities due to a lack of cognitive ability to change external environments (Stevenson & Gumpert, 1985 ). Only those who recognize and value the existence of opportunity can benefit from new opportunities (Ardichvili et al., 2003a , b ; Shane & Venkataraman, 2000 ). Opportunity recognition is an early step in transforming value into a business concept that creates value and generates revenue and distinguishes it from the aggressive stages of detailed assessment and development of recognized opportunities and potential economic value. The focus of the new venture business is also an innovative opportunity to create new opportunities rather than merely expanding or repeating existing business models (Gaglio & Katz, 2001 ). As a result, universities need to make use of a variety of initiatives to educate students to recognize innovative opportunities. Therefore, entrepreneurship education aimed at a new opportunity recognition should be able to provide learning opportunities based on various theories of favorable conditions for new business creation and the types of traits required for new ventures (Garavan & O’Cinne’ide, 1994 ).

Based on these considerations, we also define opportunity recognition as the formation of beliefs that can be translated into actions in order to understand the signals of change (new information on new conditions) and respond to these changes.

Problem-solving ability and innovative behavior of education for students

Problem-solving abilities have been proven to be one of the key factors for success in organizations and personal careers (Anderson & Anderson 1995 ). Through decades of research data, organizations and schools have studied factors that affect improvement. Problem-solving abilities are defined in a number of prior studies, and problem-solving abilities in a volatile and sophisticated knowledge- and technology-based industry are an important ability to drive innovation and sustainable growth and development in the industry. Table  1 show the concept of problem solving ability defined in previous research.

There have been a number of previous studies, emphasis has been placed on the importance and meaning of rational problem-solving processes in order to improve problem-solving abilities, and research has focused on individual problem solving styles (Woodman et al., 1993 ; Scott & Bruce, 1994 ). According to the personal innovation behavior model of Scott and Bruce ( 1994 ), climate has shown individual innovative behavior as a result of individuals signaling the organization’s expectations of behavior and the potential consequences of action. Innovative organizations are, last but not least, equipment, facilities and time, including the direction of creativity and innovative change (Kanter, 1983 ; Siegel & Kaemmerer, 1978 ) Proper supply of such resources is important to innovation (Amabile, 1988 ; Van de Ven & Angle, 1989 ; Dubickis & Gaile-Sarkane, 2017 ). Based on a study of Koestler’s ( 1964 ) creative thinking, Jabri conceptualized a problem-solving style consisting of two independent thinking styles. He uses a structured problem-solving styles that is based on associative thinking, follows a set of rules, resolves reasonably logically, and uses an intuitive problem-solving ability that focuses on problem-solving, not tied to existing rules with multiple ideas. Intuitive problem solving styles tend to process information from different paradigms simultaneously. It is therefore more likely to create new problem solutions as possible (Isaksen, 1987 ; Kirton, 1976 ). However, style assessment is not desirable because the style of problem solving affects style differently depending on the individual problem-solving situations (Scott & Bruce, 1994 ). We are proposing a role for the University to encourage innovative behavior based on the individuality of our students in order to recognize new opportunities through education about Scott and Bruce’s innovative behavioral models and diverse entrepreneurship education approaches. And involvement of resources, such as entrepreneurship awareness programs, ultimately leads to the identification of individual characteristics and innovation. In addition, current Korean entrepreneurship education is mainly focused on cognitive learning to improve problem solving ability, and one aspect of cognitive learning plays an important role in learning process of new venture firms. This study has a more direct focus on behavior learning such as team-based learning.

Hypothesis development

Problem-solving ability and innovative behavior.

Problem solving is to discover knowledge and skills that reach the target country by interfering with a set of processes and goals where the solution is unknown, unfamiliar, or reaching a new state of goal (Jonassen, 2004 ; Inkinen, 2015 ). There are various approaches to solve this problem. To solve problems and improve problem solving with a successful solution experience, you should adopt the method that best suits your problem solution. You need to select the appropriate inputs for the solution elements and a flexible process structure. Problem solving ability has been recognized as a key element of innovative behavior in responding to rapid changes with the ability to find various alternatives and predict outcomes from these alternatives to maximize positive results, minimize negative consequences, and select solutions to problems (Barron & Harrington, 1981 ; Jabri, 1991 ; Kirton, 1976 ). We pose the following hypotheses:

Hypothesis 1: Individual problem-solving ability has an effect on the innovative behavior of students.

Innovative behavior and opportunity recognition

Innovation involves introducing ideas from outside the organization, through creative processes, and linking these ideas to products or processes. Many scholars studying innovation recognize that designing ideas is only one step in the innovation process (Kanter, 1988 ). Innovation is changing at the organizational or individual level. Kanter, Scott and Bruce defined personal innovation. In other words, an innovation act starts with recognition of a problem, adoption of a new idea, or creation of a solution, and an individual with an innovative tendency wants to create a realistically realizable group with the sympathy of such an idea. Innovative individuals create prototypes for innovations that enable ideas to be realized specifically with goods or services and become productive use and social day merchandising. According to previous studies, opportunity perception can be seen as an individual’s corporate strategy that focuses on the perception and exploitation of individuals about potential business ideas and opportunities and finds resources to create innovative outcomes (Manev et al., 2005 ). New Venture Ideas (NVI) are imaginary combinations of product/service offerings; potential markets or users, and means of bringing these offerings into existence (Davidsson, 2015 ). From the viewpoint of a potential entrepreneur like a university student, entrepreneurship starts with an idea. This process continues with a range of practices including attractiveness and feasibility of an idea, gathering information to minimize value-related uncertainty and possibility and perhaps the main idea’s conformity ratio in terms of newly discovered needs (Hayton & Cholakova, 2012 ). Earlier we proposed that the program as a whole increases the students’ innovative behavior and that innovative performance is the new venture ideas. Since it is logical to assume that the relationship between innovative behavior and opportunity recognition. We pose the following hypotheses:

Hypothesis 2: Innovative behavior will be a more potent inducer of opportunity recognition.

Problem-solving ability and opportunity recognition

Among the many factors influencing opportunity perception, the problems that arise in the fourth industry, the knowledge-based industry of the twenty-first century, are unpredictable and unstructured; they cannot be solved with existing solutions and require creative problem-solving skills. In order to determine how to solve problem situations that are different from the current situation and have unknown results, problems are solved through the process of adjusting previous experience, knowledge, and intuition (Charles & Lester, 1982 ). Experience, knowledge, and intuition are applied simultaneously to a single problem, not individually or collectively, and the intellectual and creative results that can be quickly and effectively solved in problem solving are seen as problem solving abilities (Ardichvili et al., 2003a , b ). Empirical studies of problem-solving abilities and opportunity perceptions have provided strong evidence that there is a positive relationship between theoretical integrative processes and corporate opportunity recognition (Ucbasaran et al., 2009 ). Therefore, we hypothesized that:

Hypothesis 3: Problem solving ability has an effect on the opportunity recognition.

The respondents for this study were randomly selected from three universities in Korea. Most of the respondents in this study were Korean university students who experienced team-based learning during behavioral learning through entrepreneurship education. Since then, we have been guided by two main criteria when choosing these universities. First, students who take entrepreneurship courses are critical to their innovation behavior. This led us to realize that innovative behavior is an important factor in an individual’s survival and growth. The second is that the parallel process of theoretical and behavioral learning is highly satisfied. A pilot study was conducted to verify the reliability and validity of the research measurements with 28 students at a university. The results of the pilot study showed high clarity and reliability (Cronbach ‘s alphas were all above 0.70) ​​of the research measurements. The sample of the pilot study was not incorporated in the present study.

This study was conducted in a four - year undergraduate course (various majors) that took entrepreneurship courses in Korea university programs. Students in this course have a mix of students who have previously experienced entrepreneurship and those who have not. During the course, students were taught the theoretical lessons for 8 weeks and the team for the 8 weeks. The questionnaire was administered during the last week of the course.

The data were analyzed from 203 participants, out of a total of 209, of which 7 were not appropriate. Of the 203 participants, 27% were female and 73% were male and the grade distribution was 3% for freshmen, 12% for grade 2, 26% for grade 2, and 59% for grade 2. The main distribution is 26% in social science, 16% in business and economics, 39% in engineering, 11% in music and athletics and 7% in others (see Table  2 ).

Measurement

The structure of the model was measured by questionnaires (problem-solving ability, innovation behavior and opportunity recognition questionnaire) consisting of the scale taken from questionnaires verified in previous studies. Tool selection was performed on two criteria. First, the selected tool should measure the same structure (ie, the original measured structure had to be conceptually identical to the way the structure was defined in this study model). Secondly, the psychometric qualities of the instrument for the student had to be high.

Assessment of the factors was carried out through principal component analyses (varimax rotation with eigenvalues of 1.0 or above) of the scales connected to the same level of the model to confirm the uniqueness of the scales with respect to each other. This was supplemented by the computation of the internal consistency reliability of the scales (Cronbach’s α). These analyses were executed using the individual participants’ responses (Nunnally & Bernstein, 1994 ).

Problem- solving ability was measured on a 7-point Likert-scale (1 = ‘completely disagree’; 7 = ‘completely agree’). Jabri ( 1991 ) used a measurement tool to measure individual problem solving ability.

Innovative behavior was measured on a 7-point Likert-scale (1 = ‘completely disagree’; 7 = ‘completely agree’). In order to measure innovation behavior, we modified the questionnaire items to fit the intention of this study among the questionnaire items used by Scott and Bruce ( 1994 ) and Kim and Rho ( 2010 ).

Opportunity recognition was measured on a 7-point Likert-scale (1 = ‘completely disagree’; 7 = ‘completely agree’). In order to measure opportunity recognition, we modified the questionnaire items to fit the intention of this study among the questionnaire items used by Kim and Rho ( 2010 ).

Methods of analysis

The first two parts of the analysis were primarily based on (multiple) regression analyses. The last part of the analysis was informed through the path analyses. The adequacy of the models was assessed by AMOS 18(Arbuckle & Wothke, 2003 ). Models were all tested with standardized coefficients obtained from the Principal Component Analysis. To ascertain the model fit, we analyzed the comparative fit index (CFI), the normed fit index (NFI), the Root Mean Square Err of Approximation (RMSEA), the standardized root mean square residual (SRMR) and the chi-square test statistic.

Reliability and validity are essential psychometrics to be reported. The first step to evaluate those aspects was to use the Cronbach’s alpha and the composite reliability to test reliability of the proposed scales. The usual threshold level is 0.7 for newly developed measures (Fornell and Larcker, 1981 ). Values range from 0.69 to 0.79 in the case of Cronbach’s alpha, and from 0.85 to 0.92 in the case of composite reliability (see Table  3 ). Therefore, these scales may be considered as reliable. Next, we estimated the research model, displayed in Fig.  1 , using structural equation modeling (SEM) and AMOS 18 (Arbuckle & Wothke, 2003 ). Our analysis revealed an adequate measurement model with high factor loadings for all the items on the expected factors and communalities of each item exceeding 0.50. We discuss three fit indices that are generally considered as important (Hu & Bentler, 1998 ). First, the CFI-value represents the overall difference between observed and predicted correlations. A value of 0.04 which is situated well below the cut-off value of 0.08, suggests that the hypothesized model resembles the actual correlations. Secondly, Bentler’s CFI (comparative fit index) greater than 0.90 and 0.95 which is above the cut-off of 0.90 (Schumacker & Lomax, 1996 ). Thirdly, NFI greater greater than 0.90 and 0.95 which is above the cut-off of 0.90 (Schumacker & Lomax, 1996 ). Fourthly, the standardized root mean square residual (SRMR) value of 0.0392 which is situated well below the cut-off value of 0.05(Hu & Bentler, 1998 ), and the chi-square value of 3581.622 which is situated well below the cut-off value of 0.0005. Finally, the RMSEA (root mean square error of approximation) equals 0.04 with a 90% confidence interval between 0.03 and 0.05.

Analysis of mediation effect

The value and confidence interval are situated over but below the cut-off value of 0.1 which suggests not a great but a good fit. Factor analysis was verified by factor analysis using principal component analysis and only factors with an eigenvalue of 1 or more by orthogonal rotation method were selected. Factor loading was considered to be significant at 0.5 or more (Hair et al., 2006a , b ). As a result of the analysis, cumulative explanation for 72.4% of the total variance. Confirmatory factor analysis thus supported the differentiation of the three components Also we tested the confirmatory validity of the construct by testing whether the structural linkage of each square is greater than the mean variance extraction (AVE) of each structure. The AVE ranged from 0.52 to 0.53, reaching the recommended level of .50 for both Fornell and Larcker ( 1981 ). Therefore, all constructs showed sufficient convergent validity (see Table 3 ).

As shown in Table  4 , the AVE value of each variable has a higher value than that of other factors. Therefore, the discriminant validity of the proposed model can be judged as appropriate.

Means, standard deviations, and correlations among the study variables are shown in Table  5 .

The mean scores for the conceptual model were as follows for problem-solving ability (MD. 5.20, SD.1.08), innovative behavior (MD.5.20, SD.1.03), and opportunity recognition (MD. 5.14, SD. 1.06) conditions. The means of problem-solving ability, innovative behavior, and opportunity recognition were high. Furthermore, those variables correlated positively with each other.

Figure  1 showed that all paths and their significance levels are presented in Table  6 . The path between the latent variables problem-solving ability and innovative behavior was significant (p, 0.001), consistent with Hypotheses 1. In addition, there was innovative behavior and opportunity recognition (p, 0.01), this result provide empirical support for Hypothesis 2.

H3 proposed that Problem-solving ability is positively related to opportunity recognition. The results of the correlation analysis: The coefficient of problem solving and opportunity perception weakened from .717 to .444, but it is still partly mediated because it is still significant (C. R  = 7.604 ***). This supports H3 (see Table 6 ).

In order to verify the significance of the indirect effect, the bootstrapping must be performed in AMOS, and the actual significance test should be identified using two-tailed significance. As a result, the significance of indirect effect is 0.04 ( p  < 0.05), which is statistically significant (see Table  7 ).

Discussion and conclusion

We have tried to demonstrate the effects of behavior and its significance by differentiating from the general curriculum emphasizing cognitive effects as a model of problem solving ability emerging as innovative behavior through opportunity of university entrepreneurship education.. This supports the premise that entrepreneurship education can improve opportunities or processes through behavioral learning. The results of this study support the role of entrepreneurship education in creating opportunities for innovative behavior and problem solving abilities. Entrepreneurship education should provide different types of learning for new opportunities and focus on what is manifested in behavior.

In addition, based on previous research, we propose whether the following contents are well followed and whether it is effective. First, the emergence of innovative behavior in problem-solving abilities increases as the cognitive diversity of students with diverse majors and diverse backgrounds increases. Second, the more entrepreneurial learning experiences, the greater the chance of new opportunities. Third, it is necessary to investigate students’ problem solving style and problem-solving ability first, and then a teaching strategy based on this combination of systematic and effective theory and practice is needed. Of course, as demonstrated by many studies, it may be easier to enhance the effectiveness of opportunity recognition through cognitive learning. This is because it emphasizes the achievement of knowledge and understanding with acquiring skills and competence. This process, however, is not enough for entrepreneurship education. However, we do not support full team-based behavioral learning in the class designed by Michaelsen and Sweet ( 2008 ). As with the results of this study, problem solving ability is positively related to opportunity perception directly. As previously demonstrated in previous studies, problem solving ability can be enhanced by cognitive learning (Anderson et al., 2001 ; Charles & Lester, 1982 ).

Therefore, it has been demonstrated that it is more efficient to balance a certain level of cognitive learning and behavior learning in consideration of the level of students in a course. Also this study satisfies the need for empirical research by Lumpkin and Lichtenstein ( 2005 ) and Robinson et al. ( 2016 ) and others. This will help to improve understanding of how entrepreneurship training is linked to various learning models and their effectiveness and to design better courses for the future. Finally, this study sought to provide an awareness of entrepreneurship education as the best curriculum for solutions that evolved into innovative behaviors that create new values and ultimately represent new opportunities. This study shows that it can positively influence the social effect of creating new value, that is, not only the cognitive effect of general pedagogy, but also the innovation behavior. By providing this awareness, we have laid the groundwork for empirical research on entrepreneurship education in order to create more opportunities for prospective students in education through education and to expand their capabilities.

Limitation and future research

Indeed, the concepts presented here and the limitations of this study have important implications that can fruitfully be addressed in future research. First, we selected a sample of college students taking entrepreneurship training. However, since it is not the whole of Korean university students, it is difficult to extend the research results to all college students in Korea. Second, there is no precedent research on the role of innovation behavior as intermedia in college students. Therefore, we were forced to proceed as an exploratory study.

The ability to recognize opportunities can provide significant benefits that can remain firm and competitive in an ever-changing environment. Future research should therefore expand these insights and try to empirically test more ways in which entrepreneurship pedagogy teaches how learning methods can be integrated into venture creation and growth processes to help new process opportunities. By providing this study, we will help entrepreneurship education in the university to create more opportunities and expand the capacity of prospective members.

Alvarez, S. A., & Barney, J. B. (2005). How do entrepreneurs organize firms under conditions of uncertainty? Journal of Management, 31 (5), 776–793.

Article   Google Scholar  

Amabile, T. M. (1988). A model of creativity and innovation in organizations. Research in Organizational Behavior, 10 (1), 123–167.

Google Scholar  

Ancona, D. G., & Caldwell, D. F. (1992). Demography and design: Predictors of new product team performance. Organization Science, 3 (3), 321–341.

Anderson, P. M., & Anderson, P. M. (1995). Analysis of faulted power systems (Vol. 445). New York: IEEE press.

Anderson, L. W., Krathwohl, D. R., Airasian, P., Cruikshank, K., Mayer, R., Pintrich, P., & Wittrock, M. (2001). A taxonomy for learning, teaching and assessing: A revision of Bloom’s taxonomy . New York: Longman Publishing.

Arbuckle, J. L., & Wothke, W. (2003). AMOS 5 user’s guide . Chicago: Smallwaters.

Ardichvili, A., Cardozo, R., & Ray, S. (2003a). A theory of entrepreneurial opportunity identification and development. Journal of Business Venturing, 18 (1), 105–123.

Ardichvili, A., Cardozo, R., & Ray, S. (2003b). A theory of entrepreneurial opportunity identification and development. Journal of Business Venturing, 18 (1), 105–123.

Baron, R. A., & Ensley, M. D. (2006). Opportunity recognition as the detection of meaningful patterns: Evidence from comparisons of novice and experienced entrepreneurs. Management Science, 52 (9), 1331–1344.

Barron, F., & Harrington, D. M. (1981). Creativity, intelligence, and personality. Annual review of psychology, 32 (1), 439–476.

Casson, M. (1982). The entrepreneur: An economic theory . Lanham: Rowman & Littlefield.

Charles, R., & Lester, F. (1982). Teaching problem solving: What, why & how . Palo Alto: Dale Seymour Publications.

Davidsson, P. (2015). Entrepreneurial opportunities and the entrepreneurship nexus: A re-conceptualization. Journal of Business Venturing, 30 (5), 674–695.

Dubickis, M., & Gaile-Sarkane, E. (2017). Transfer of know-how based on learning outcomes for development of open innovation. Journal of Open Innovation : Technology, market, and complexity , 3 (1), 4.

Dyer, J. H., Gregersen, H. B., & Christensen, C. (2008). Entrepreneur behaviors, opportunity recognition, and the origins of innovative ventures. Strategic Entrepreneurship Journal, 2 (4), 317–338.

D'zurilla, T. J., & Nezu, A. M. (1990). Development and preliminary evaluation of the social problem-solving inventory. Psychological Assessment: A Journal of Consulting and Clinical Psychology, 2 (2), 156.

Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research , 39–50.

Gaglio, C. M., & Katz, J. A. (2001). The psychological basis of opportunity identification: Entrepreneurial alertness. Small Business Economics, 16 (2), 95–111.

Garavan, T. N., & O’Cinneide, B. (1994). Entrepreneurship education and training programmes: A review and evaluation-part 1. Journal of European Industrial Training, 18 (8), 3–12.

Gartner, W. B., & Carter, N. M. (2003). Entrepreneurial behavior and firm organizing processes. In Handbook of entrepreneurship research (pp. 195–221). New Mexico: Springer US.

Hair, E., Halle, T., Terry-Humen, E., Lavelle, B., & Calkins, J. (2006a). Children's school readiness in the ECLS-K: Predictions to academic, health, and social outcomes in first grade. Early Childhood Research Quarterly, 21 (4), 431–454.

Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2006b). Multivariate Data Analysis (6th ed.). Upper Saddle River: Pearson Education, Inc..

Hayton, J. C., & Cholakova, M. (2012). The role of affect in the creation and intentional pursuit of entrepreneurial ideas. Entrepreneurship Theory and Practice, 36 (1), 41–68.

Hu, L. T., & Bentler, P. M. (1998). Fit indices in covariance structure modeling: Sensitivity to underparameterized model misspecification. Psychological Methods, 3 (4), 424.

Inkinen, T. (2015). Reflections on the innovative city: Examining three innovative locations in a knowledge bases framework. Journal of Open Innovation : Technolodgy, market. Complexity, 1 (1), 8.

Isaksen, S. G. (1987). Frontiers of creativity research: Beyond the basics. Bearly Ltd.

Jabri, M. M. (1991). The development of conceptually independent subscales in the measurement of modes of problem solving. Educational and Psychological Measurement, 51 (4), 975–983.

Jonassen, D. H. (2004). Learning to solve problems: An instructional design guide (Vol. 6). Hoboken: John Wiley & Sons.

Kanter, R. M. (1983). The change masters: Binnovation and entrepreneturship in the American corporation. Touchstone Book.

Kanter, R. M. (1988). Three tiers for innovation research. Communication Research, 15 (5), 509–523.

Kim, H. C., Song, C. H., & An, B. R. (2016). A study on effects of personal characteristics on start-up opportunity and entrepreneurial intention of start-up. Korean Management Consulting review, 16 (3), 75–87.

Kim, S. A., Ryoo, H. Y., & Ahn, H. J. (2017). Student customized creative education model based on open innovation. Journal of Open Innovation : Technology, Market, and Complexity , 3 (1), 6.

Kim, T. H., & Roh, J. H. (2010). A Study of the Impact of Public Service Motivation on Innovative Behavior of Organizational Members. Korean Journal of Public Administration, 48(3).

Kirton, M. (1976). Adaptors and innovators: A description and measure. Journal of Applied Psychology, 61 (5), 622.

Kirzner, I. M. (1997). Entrepreneurial discovery and the competitive market process: An Austrian approach. Journal of Economic Literature, 35 (1), 60–85.

Ko, S., & Butler, J. E. (2003). Alertness, bisociative thinking ability, and discovery of entrepreneurial opportunities in Asian hi-tech firms.

Koestler, A. (1964). The act of creation: A study of the conscious and unconscious processes of humor, scientific discovery and art.

Lumpkin, G. T., & Dess, G. G. (2004). E-Business Strategies and Internet Business Models: How the Internet Adds Value. Organizational Dynamics, 33 (2), 161–173.

Lumpkin, G. T., & Lichtenstein, B. B. (2005). The role of organizational learning in the opportunity-recognition process. Entrepreneurship Theory and Practice, 29 (4), 451–472.

Manev, I. M., Gyoshev, B. S., & Manolova, T. S. (2005). The role of human and social capital and entrepreneurial orientation for small business performance in a transitional economy. International Journal of Entrepreneurship and Innovation Management, 5 (3–4), 298–318.

Michaelsen, L. K., & Sweet, M. (2008). The essential elements of team-based learning. New directions for teaching and learning, 2008 (116), 7–27.

Nunnally, J. C., & Bernstein, I. H. (1994). Validity. Psychometric theory, 99–132.

Paine, J. B., & Organ, D. W. (2000). The cultural matrix of organizational citizenship behavior: Some preliminary conceptual and empirical observations. Human Resource Management Review, 10 (1), 45–59.

Robinson, S., Neergaard, H., Tanggaard, L., & Krueger, N. F. (2016). New horizons in entrepreneurship education: from teacher-led to student-centered learning. Education+ Training, 58(7/8), 661–683.

Schumacker, R. E., & Lomax, R. G. (1996). A beginner's guide to structural equation modeling . Mahwah: Laurence Erlbaum Google Scholar.

Scott, S. G., & Bruce, R. A. (1994). Determinants of innovative behavior: A path model of individual innovation in the workplace. Academy of Management Journal, 37 (3), 580–607.

Shane, S. A. (2003). A general theory of entrepreneurship: The individual-opportunity nexus . Cheltenham: Edward Elgar Publishing.

Book   Google Scholar  

Shane, S., & Venkataraman, S. (2000). The promise of entrepreneurship as a field of research. Academy of Management Review, 25 (1), 217–226.

Siegel, S. M., & Kaemmerer, W. F. (1978). Measuring the perceived support for innovation in organizations. Journal of Applied Psychology, 63 (5), 553–562.

Spivack, G., Platt, J. J., & Shure, M. B. (1976). The problem-solving approach to adjustment . San Francisco: Jossey-Bass.

Stevenson, H., & Gumpert, D. (1985). The heart of entrepreneurship.

Stevenson, H. H. & J. C. Jarillo (1990). 'A paradigm of entrepreneurship: Entrepreneurial management', Strategic Management Journal, 11, pp. 17–27.

Ucbasaran, D., Westhead, P., & Wright, M. (2009). The extent and nature of opportunity identification by experienced entrepreneurs. Journal of Business Venturing, 24 (2), 99–115.

Van de Ven, A. H., & Angle, H. L. (1989). Suggestions for managing the innovation journey (No. 9). Strategic Management Research Center, University of Minnesota.

Venkataraman, S. (1997). The distinctive domain of entrepreneurship research. Advances in entrepreneurship, firm emergence and growth, 3 (1), 119–138.

Venkataraman, S., & Sarasvathy, S. D. (2001). Strategy and entrepreneurship: Outlines of an untold story.

Warner, M. (2002). Publics and counterpublics. Public Culture, 14 (1), 49–90.

Woodman, R. W., Sawyer, J. E., & Griffin, R. W. (1993). Toward a theory of organizational creativity. Academy of Management Review, 18 (2), 293–321.

Download references

Author information

Authors and affiliations.

Dept. of Technology Entrepreneurship (Graduate School), Dongguk University, 904 Chungmurogwn, Toegye-ro 36Gil, Jung-gu, Seoul, 100-272, South Korea

Ji Young Kim, Dae Soo Choi & Chang-Soo Sung

Yonsei School of Business, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 120-749, South Korea

Joo Y. Park

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Joo Y. Park .

Ethics declarations

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/ ), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Reprints and permissions

About this article

Cite this article.

Kim, J.Y., Choi, D.S., Sung, CS. et al. The role of problem solving ability on innovative behavior and opportunity recognition in university students. J. open innov. 4 , 4 (2018). https://doi.org/10.1186/s40852-018-0085-4

Download citation

Received : 12 September 2017

Accepted : 22 January 2018

Published : 05 February 2018

DOI : https://doi.org/10.1186/s40852-018-0085-4

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Problem-solving ability
• Innovative behavior
• Opportunity recognition
• Entrepreneurship education

• SUGGESTED TOPICS
• The Magazine
• Newsletters
• Managing Yourself
• Managing Teams
• Work-life Balance
• The Big Idea
• Data & Visuals
• Reading Lists
• Case Selections
• HBR Learning
• Topic Feeds
• Account Settings
• Email Preferences

Share Podcast

Do You Understand the Problem You’re Trying to Solve?

To solve tough problems at work, first ask these questions.

• Apple Podcasts
• Google Podcasts

Problem solving skills are invaluable in any job. But all too often, we jump to find solutions to a problem without taking time to really understand the dilemma we face, according to Thomas Wedell-Wedellsborg , an expert in innovation and the author of the book, What’s Your Problem?: To Solve Your Toughest Problems, Change the Problems You Solve .

In this episode, you’ll learn how to reframe tough problems by asking questions that reveal all the factors and assumptions that contribute to the situation. You’ll also learn why searching for just one root cause can be misleading.

Key episode topics include: leadership, decision making and problem solving, power and influence, business management.

HBR On Leadership curates the best case studies and conversations with the world’s top business and management experts, to help you unlock the best in those around you. New episodes every week.

• Listen to the original HBR IdeaCast episode: The Secret to Better Problem Solving (2016)
• Find more episodes of HBR IdeaCast
• Discover 100 years of Harvard Business Review articles, case studies, podcasts, and more at HBR.org .

HANNAH BATES: Welcome to HBR on Leadership , case studies and conversations with the world’s top business and management experts, hand-selected to help you unlock the best in those around you.

Problem solving skills are invaluable in any job. But even the most experienced among us can fall into the trap of solving the wrong problem.

Thomas Wedell-Wedellsborg says that all too often, we jump to find solutions to a problem – without taking time to really understand what we’re facing.

He’s an expert in innovation, and he’s the author of the book, What’s Your Problem?: To Solve Your Toughest Problems, Change the Problems You Solve .

  In this episode, you’ll learn how to reframe tough problems, by asking questions that reveal all the factors and assumptions that contribute to the situation. You’ll also learn why searching for one root cause can be misleading. And you’ll learn how to use experimentation and rapid prototyping as problem-solving tools.

This episode originally aired on HBR IdeaCast in December 2016. Here it is.

SARAH GREEN CARMICHAEL: Welcome to the HBR IdeaCast from Harvard Business Review. I’m Sarah Green Carmichael.

Problem solving is popular. People put it on their resumes. Managers believe they excel at it. Companies count it as a key proficiency. We solve customers’ problems.

The problem is we often solve the wrong problems. Albert Einstein and Peter Drucker alike have discussed the difficulty of effective diagnosis. There are great frameworks for getting teams to attack true problems, but they’re often hard to do daily and on the fly. That’s where our guest comes in.

Thomas Wedell-Wedellsborg is a consultant who helps companies and managers reframe their problems so they can come up with an effective solution faster. He asks the question “Are You Solving The Right Problems?” in the January-February 2017 issue of Harvard Business Review. Thomas, thank you so much for coming on the HBR IdeaCast .

THOMAS WEDELL-WEDELLSBORG: Thanks for inviting me.

SARAH GREEN CARMICHAEL: So, I thought maybe we could start by talking about the problem of talking about problem reframing. What is that exactly?

THOMAS WEDELL-WEDELLSBORG: Basically, when people face a problem, they tend to jump into solution mode to rapidly, and very often that means that they don’t really understand, necessarily, the problem they’re trying to solve. And so, reframing is really a– at heart, it’s a method that helps you avoid that by taking a second to go in and ask two questions, basically saying, first of all, wait. What is the problem we’re trying to solve? And then crucially asking, is there a different way to think about what the problem actually is?

SARAH GREEN CARMICHAEL: So, I feel like so often when this comes up in meetings, you know, someone says that, and maybe they throw out the Einstein quote about you spend an hour of problem solving, you spend 55 minutes to find the problem. And then everyone else in the room kind of gets irritated. So, maybe just give us an example of maybe how this would work in practice in a way that would not, sort of, set people’s teeth on edge, like oh, here Sarah goes again, reframing the whole problem instead of just solving it.

THOMAS WEDELL-WEDELLSBORG: I mean, you’re bringing up something that’s, I think is crucial, which is to create legitimacy for the method. So, one of the reasons why I put out the article is to give people a tool to say actually, this thing is still important, and we need to do it. But I think the really critical thing in order to make this work in a meeting is actually to learn how to do it fast, because if you have the idea that you need to spend 30 minutes in a meeting delving deeply into the problem, I mean, that’s going to be uphill for most problems. So, the critical thing here is really to try to make it a practice you can implement very, very rapidly.

There’s an example that I would suggest memorizing. This is the example that I use to explain very rapidly what it is. And it’s basically, I call it the slow elevator problem. You imagine that you are the owner of an office building, and that your tenants are complaining that the elevator’s slow.

Now, if you take that problem framing for granted, you’re going to start thinking creatively around how do we make the elevator faster. Do we install a new motor? Do we have to buy a new lift somewhere?

The thing is, though, if you ask people who actually work with facilities management, well, they’re going to have a different solution for you, which is put up a mirror next to the elevator. That’s what happens is, of course, that people go oh, I’m busy. I’m busy. I’m– oh, a mirror. Oh, that’s beautiful.

And then they forget time. What’s interesting about that example is that the idea with a mirror is actually a solution to a different problem than the one you first proposed. And so, the whole idea here is once you get good at using reframing, you can quickly identify other aspects of the problem that might be much better to try to solve than the original one you found. It’s not necessarily that the first one is wrong. It’s just that there might be better problems out there to attack that we can, means we can do things much faster, cheaper, or better.

SARAH GREEN CARMICHAEL: So, in that example, I can understand how A, it’s probably expensive to make the elevator faster, so it’s much cheaper just to put up a mirror. And B, maybe the real problem people are actually feeling, even though they’re not articulating it right, is like, I hate waiting for the elevator. But if you let them sort of fix their hair or check their teeth, they’re suddenly distracted and don’t notice.

But if you have, this is sort of a pedestrian example, but say you have a roommate or a spouse who doesn’t clean up the kitchen. Facing that problem and not having your elegant solution already there to highlight the contrast between the perceived problem and the real problem, how would you take a problem like that and attack it using this method so that you can see what some of the other options might be?

THOMAS WEDELL-WEDELLSBORG: Right. So, I mean, let’s say it’s you who have that problem. I would go in and say, first of all, what would you say the problem is? Like, if you were to describe your view of the problem, what would that be?

SARAH GREEN CARMICHAEL: I hate cleaning the kitchen, and I want someone else to clean it up.

THOMAS WEDELL-WEDELLSBORG: OK. So, my first observation, you know, that somebody else might not necessarily be your spouse. So, already there, there’s an inbuilt assumption in your question around oh, it has to be my husband who does the cleaning. So, it might actually be worth, already there to say, is that really the only problem you have? That you hate cleaning the kitchen, and you want to avoid it? Or might there be something around, as well, getting a better relationship in terms of how you solve problems in general or establishing a better way to handle small problems when dealing with your spouse?

SARAH GREEN CARMICHAEL: Or maybe, now that I’m thinking that, maybe the problem is that you just can’t find the stuff in the kitchen when you need to find it.

THOMAS WEDELL-WEDELLSBORG: Right, and so that’s an example of a reframing, that actually why is it a problem that the kitchen is not clean? Is it only because you hate the act of cleaning, or does it actually mean that it just takes you a lot longer and gets a lot messier to actually use the kitchen, which is a different problem. The way you describe this problem now, is there anything that’s missing from that description?

SARAH GREEN CARMICHAEL: That is a really good question.

THOMAS WEDELL-WEDELLSBORG: Other, basically asking other factors that we are not talking about right now, and I say those because people tend to, when given a problem, they tend to delve deeper into the detail. What often is missing is actually an element outside of the initial description of the problem that might be really relevant to what’s going on. Like, why does the kitchen get messy in the first place? Is it something about the way you use it or your cooking habits? Is it because the neighbor’s kids, kind of, use it all the time?

There might, very often, there might be issues that you’re not really thinking about when you first describe the problem that actually has a big effect on it.

SARAH GREEN CARMICHAEL: I think at this point it would be helpful to maybe get another business example, and I’m wondering if you could tell us the story of the dog adoption problem.

THOMAS WEDELL-WEDELLSBORG: Yeah. This is a big problem in the US. If you work in the shelter industry, basically because dogs are so popular, more than 3 million dogs every year enter a shelter, and currently only about half of those actually find a new home and get adopted. And so, this is a problem that has persisted. It’s been, like, a structural problem for decades in this space. In the last three years, where people found new ways to address it.

So a woman called Lori Weise who runs a rescue organization in South LA, and she actually went in and challenged the very idea of what we were trying to do. She said, no, no. The problem we’re trying to solve is not about how to get more people to adopt dogs. It is about keeping the dogs with their first family so they never enter the shelter system in the first place.

In 2013, she started what’s called a Shelter Intervention Program that basically works like this. If a family comes and wants to hand over their dog, these are called owner surrenders. It’s about 30% of all dogs that come into a shelter. All they would do is go up and ask, if you could, would you like to keep your animal? And if they said yes, they would try to fix whatever helped them fix the problem, but that made them turn over this.

And sometimes that might be that they moved into a new building. The landlord required a deposit, and they simply didn’t have the money to put down a deposit. Or the dog might need a $10 rabies shot, but they didn’t know how to get access to a vet.

And so, by instigating that program, just in the first year, she took her, basically the amount of dollars they spent per animal they helped went from something like $85 down to around $60. Just an immediate impact, and her program now is being rolled out, is being supported by the ASPCA, which is one of the big animal welfare stations, and it’s being rolled out to various other places.

And I think what really struck me with that example was this was not dependent on having the internet. This was not, oh, we needed to have everybody mobile before we could come up with this. This, conceivably, we could have done 20 years ago. Only, it only happened when somebody, like in this case Lori, went in and actually rethought what the problem they were trying to solve was in the first place.

SARAH GREEN CARMICHAEL: So, what I also think is so interesting about that example is that when you talk about it, it doesn’t sound like the kind of thing that would have been thought of through other kinds of problem solving methods. There wasn’t necessarily an After Action Review or a 5 Whys exercise or a Six Sigma type intervention. I don’t want to throw those other methods under the bus, but how can you get such powerful results with such a very simple way of thinking about something?

THOMAS WEDELL-WEDELLSBORG: That was something that struck me as well. This, in a way, reframing and the idea of the problem diagnosis is important is something we’ve known for a long, long time. And we’ve actually have built some tools to help out. If you worked with us professionally, you are familiar with, like, Six Sigma, TRIZ, and so on. You mentioned 5 Whys. A root cause analysis is another one that a lot of people are familiar with.

Those are our good tools, and they’re definitely better than nothing. But what I notice when I work with the companies applying those was those tools tend to make you dig deeper into the first understanding of the problem we have. If it’s the elevator example, people start asking, well, is that the cable strength, or is the capacity of the elevator? That they kind of get caught by the details.

That, in a way, is a bad way to work on problems because it really assumes that there’s like a, you can almost hear it, a root cause. That you have to dig down and find the one true problem, and everything else was just symptoms. That’s a bad way to think about problems because problems tend to be multicausal.

There tend to be lots of causes or levers you can potentially press to address a problem. And if you think there’s only one, if that’s the right problem, that’s actually a dangerous way. And so I think that’s why, that this is a method I’ve worked with over the last five years, trying to basically refine how to make people better at this, and the key tends to be this thing about shifting out and saying, is there a totally different way of thinking about the problem versus getting too caught up in the mechanistic details of what happens.

SARAH GREEN CARMICHAEL: What about experimentation? Because that’s another method that’s become really popular with the rise of Lean Startup and lots of other innovation methodologies. Why wouldn’t it have worked to, say, experiment with many different types of fixing the dog adoption problem, and then just pick the one that works the best?

THOMAS WEDELL-WEDELLSBORG: You could say in the dog space, that’s what’s been going on. I mean, there is, in this industry and a lot of, it’s largely volunteer driven. People have experimented, and they found different ways of trying to cope. And that has definitely made the problem better. So, I wouldn’t say that experimentation is bad, quite the contrary. Rapid prototyping, quickly putting something out into the world and learning from it, that’s a fantastic way to learn more and to move forward.

My point is, though, that I feel we’ve come to rely too much on that. There’s like, if you look at the start up space, the wisdom is now just to put something quickly into the market, and then if it doesn’t work, pivot and just do more stuff. What reframing really is, I think of it as the cognitive counterpoint to prototyping. So, this is really a way of seeing very quickly, like not just working on the solution, but also working on our understanding of the problem and trying to see is there a different way to think about that.

If you only stick with experimentation, again, you tend to sometimes stay too much in the same space trying minute variations of something instead of taking a step back and saying, wait a minute. What is this telling us about what the real issue is?

SARAH GREEN CARMICHAEL: So, to go back to something that we touched on earlier, when we were talking about the completely hypothetical example of a spouse who does not clean the kitchen–

THOMAS WEDELL-WEDELLSBORG: Completely, completely hypothetical.

SARAH GREEN CARMICHAEL: Yes. For the record, my husband is a great kitchen cleaner.

You started asking me some questions that I could see immediately were helping me rethink that problem. Is that kind of the key, just having a checklist of questions to ask yourself? How do you really start to put this into practice?

THOMAS WEDELL-WEDELLSBORG: I think there are two steps in that. The first one is just to make yourself better at the method. Yes, you should kind of work with a checklist. In the article, I kind of outlined seven practices that you can use to do this.

But importantly, I would say you have to consider that as, basically, a set of training wheels. I think there’s a big, big danger in getting caught in a checklist. This is something I work with.

My co-author Paddy Miller, it’s one of his insights. That if you start giving people a checklist for things like this, they start following it. And that’s actually a problem, because what you really want them to do is start challenging their thinking.

So the way to handle this is to get some practice using it. Do use the checklist initially, but then try to step away from it and try to see if you can organically make– it’s almost a habit of mind. When you run into a colleague in the hallway and she has a problem and you have five minutes, like, delving in and just starting asking some of those questions and using your intuition to say, wait, how is she talking about this problem? And is there a question or two I can ask her about the problem that can help her rethink it?

SARAH GREEN CARMICHAEL: Well, that is also just a very different approach, because I think in that situation, most of us can’t go 30 seconds without jumping in and offering solutions.

THOMAS WEDELL-WEDELLSBORG: Very true. The drive toward solutions is very strong. And to be clear, I mean, there’s nothing wrong with that if the solutions work. So, many problems are just solved by oh, you know, oh, here’s the way to do that. Great.

But this is really a powerful method for those problems where either it’s something we’ve been banging our heads against tons of times without making progress, or when you need to come up with a really creative solution. When you’re facing a competitor with a much bigger budget, and you know, if you solve the same problem later, you’re not going to win. So, that basic idea of taking that approach to problems can often help you move forward in a different way than just like, oh, I have a solution.

I would say there’s also, there’s some interesting psychological stuff going on, right? Where you may have tried this, but if somebody tries to serve up a solution to a problem I have, I’m often resistant towards them. Kind if like, no, no, no, no, no, no. That solution is not going to work in my world. Whereas if you get them to discuss and analyze what the problem really is, you might actually dig something up.

Let’s go back to the kitchen example. One powerful question is just to say, what’s your own part in creating this problem? It’s very often, like, people, they describe problems as if it’s something that’s inflicted upon them from the external world, and they are innocent bystanders in that.

SARAH GREEN CARMICHAEL: Right, or crazy customers with unreasonable demands.

THOMAS WEDELL-WEDELLSBORG: Exactly, right. I don’t think I’ve ever met an agency or consultancy that didn’t, like, gossip about their customers. Oh, my god, they’re horrible. That, you know, classic thing, why don’t they want to take more risk? Well, risk is bad.

It’s their business that’s on the line, not the consultancy’s, right? So, absolutely, that’s one of the things when you step into a different mindset and kind of, wait. Oh yeah, maybe I actually am part of creating this problem in a sense, as well. That tends to open some new doors for you to move forward, in a way, with stuff that you may have been struggling with for years.

SARAH GREEN CARMICHAEL: So, we’ve surfaced a couple of questions that are useful. I’m curious to know, what are some of the other questions that you find yourself asking in these situations, given that you have made this sort of mental habit that you do? What are the questions that people seem to find really useful?

THOMAS WEDELL-WEDELLSBORG: One easy one is just to ask if there are any positive exceptions to the problem. So, was there day where your kitchen was actually spotlessly clean? And then asking, what was different about that day? Like, what happened there that didn’t happen the other days? That can very often point people towards a factor that they hadn’t considered previously.

SARAH GREEN CARMICHAEL: We got take-out.

THOMAS WEDELL-WEDELLSBORG: S,o that is your solution. Take-out from [INAUDIBLE]. That might have other problems.

Another good question, and this is a little bit more high level. It’s actually more making an observation about labeling how that person thinks about the problem. And what I mean with that is, we have problem categories in our head. So, if I say, let’s say that you describe a problem to me and say, well, we have a really great product and are, it’s much better than our previous product, but people aren’t buying it. I think we need to put more marketing dollars into this.

Now you can go in and say, that’s interesting. This sounds like you’re thinking of this as a communications problem. Is there a different way of thinking about that? Because you can almost tell how, when the second you say communications, there are some ideas about how do you solve a communications problem. Typically with more communication.

And what you might do is go in and suggest, well, have you considered that it might be, say, an incentive problem? Are there incentives on behalf of the purchasing manager at your clients that are obstructing you? Might there be incentive issues with your own sales force that makes them want to sell the old product instead of the new one?

So literally, just identifying what type of problem does this person think about, and is there different potential way of thinking about it? Might it be an emotional problem, a timing problem, an expectations management problem? Thinking about what label of what type of problem that person is kind of thinking as it of.

SARAH GREEN CARMICHAEL: That’s really interesting, too, because I think so many of us get requests for advice that we’re really not qualified to give. So, maybe the next time that happens, instead of muddying my way through, I will just ask some of those questions that we talked about instead.

THOMAS WEDELL-WEDELLSBORG: That sounds like a good idea.

SARAH GREEN CARMICHAEL: So, Thomas, this has really helped me reframe the way I think about a couple of problems in my own life, and I’m just wondering. I know you do this professionally, but is there a problem in your life that thinking this way has helped you solve?

THOMAS WEDELL-WEDELLSBORG: I’ve, of course, I’ve been swallowing my own medicine on this, too, and I think I have, well, maybe two different examples, and in one case somebody else did the reframing for me. But in one case, when I was younger, I often kind of struggled a little bit. I mean, this is my teenage years, kind of hanging out with my parents. I thought they were pretty annoying people. That’s not really fair, because they’re quite wonderful, but that’s what life is when you’re a teenager.

And one of the things that struck me, suddenly, and this was kind of the positive exception was, there was actually an evening where we really had a good time, and there wasn’t a conflict. And the core thing was, I wasn’t just seeing them in their old house where I grew up. It was, actually, we were at a restaurant. And it suddenly struck me that so much of the sometimes, kind of, a little bit, you love them but they’re annoying kind of dynamic, is tied to the place, is tied to the setting you are in.

And of course, if– you know, I live abroad now, if I visit my parents and I stay in my old bedroom, you know, my mother comes in and wants to wake me up in the morning. Stuff like that, right? And it just struck me so, so clearly that it’s– when I change this setting, if I go out and have dinner with them at a different place, that the dynamic, just that dynamic disappears.

SARAH GREEN CARMICHAEL: Well, Thomas, this has been really, really helpful. Thank you for talking with me today.

THOMAS WEDELL-WEDELLSBORG: Thank you, Sarah.  

HANNAH BATES: That was Thomas Wedell-Wedellsborg in conversation with Sarah Green Carmichael on the HBR IdeaCast. He’s an expert in problem solving and innovation, and he’s the author of the book, What’s Your Problem?: To Solve Your Toughest Problems, Change the Problems You Solve .

We’ll be back next Wednesday with another hand-picked conversation about leadership from the Harvard Business Review. If you found this episode helpful, share it with your friends and colleagues, and follow our show on Apple Podcasts, Spotify, or wherever you get your podcasts. While you’re there, be sure to leave us a review.

We’re a production of Harvard Business Review. If you want more podcasts, articles, case studies, books, and videos like this, find it all at HBR dot org.

This episode was produced by Anne Saini, and me, Hannah Bates. Ian Fox is our editor. Music by Coma Media. Special thanks to Maureen Hoch, Adi Ignatius, Karen Player, Ramsey Khabbaz, Nicole Smith, Anne Bartholomew, and you – our listener.

See you next week.

• Subscribe On:

Latest in this series

This article is about leadership.

• Decision making and problem solving
• Power and influence
• Business management

Partner Center

Mathematical Problem Solving

Current Themes, Trends, and Research

• © 2019
• Peter Liljedahl 0 ,
• Manuel Santos-Trigo 1

Faculty of Education, Simon Fraser University, Burnaby, Canada

You can also search for this editor in PubMed   Google Scholar

Department of Mathematics Education, Cinvestav-Instituto Politecnico Nacional, Mexico City, Mexico

• Brings together some of the latest research on problem solving
• Offers international perspectives on current themes, trends, and research on problem solving
• Presents multiple frameworks and views on problem solving

Part of the book series: ICME-13 Monographs (ICME13Mo)

26k Accesses

64 Citations

2 Altmetric

This is a preview of subscription content, log in via an institution to check access.

Access this book

• Available as EPUB and PDF
• Read on any device
• Instant download
• Own it forever
• Durable hardcover edition
• Dispatched in 3 to 5 business days
• Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

Licence this eBook for your library

Institutional subscriptions

Table of contents (15 chapters)

Front matter, problem solving heuristics, “looking back” to solve differently: familiarity, fluency, and flexibility.

• Hartono Tjoe

Future-Oriented Thinking and Activity in Mathematical Problem Solving

• Wes Maciejewski

Problem Solving and Technology

A model of mathematical problem solving with technology: the case of marco solving-and-expressing two geometry problems.

• Susana Carreira, Hélia Jacinto

Mathematical Problem Solving and the Use of Digital Technologies

Manuel Santos-Trigo

The Spreadsheet Affordances in Solving Complex Word Problems

• Nélia Amado, Susana Carreira, Sandra Nobre

Inquiry and Problem Posing in Mathematics Education

Is an inquiry-based approach possible at the elementary school.

• Magali Hersant, Christine Choquet

How to Stimulate In-Service Teachers’ Didactic Analysis Competence by Means of Problem Posing

• Uldarico Malaspina, Carlos Torres, Norma Rubio

Assessment of and Through Problem Solving

The impact of various methods in evaluating metacognitive strategies in mathematical problem solving.

• Mei Yoke Loh, Ngan Hoe Lee

Assessing Inquiry-Based Mathematics Education with Both a Summative and Formative Purpose

• Maud Chanudet

Beyond the Standardized Assessment of Mathematical Problem Solving Competencies: From Products to Processes

• Pietro Di Martino, Giulia Signorini

Toward Designing and Developing Likert Items to Assess Mathematical Problem Solving

• James A. Mendoza Álvarez, Kathryn Rhoads, R. Cavender Campbell

The Problem Solving Environment

Creating and sustaining online problem solving forums: two perspectives.

• Boris Koichu, Nelly Keller

Conditions for Supporting Problem Solving: Vertical Non-permanent Surfaces

Peter Liljedahl

The ARPA Experience in Chile: Problem Solving for Teachers’ Professional Development

• Patricio Felmer, Josefa Perdomo-Díaz, Cristián Reyes
• Mathematical problem solving
• Problem solving heuristics
• Problem posing in mathematics education
• Problem solving environment
• Future-oriented Thinking in Mathematical Problem Solving
• Mathematical problem solving with technology
• Spreadsheet affordances in solving complex word problems
• Didactic analysis by means of problem posing
• Mathematical problem solving competencies
• Activating Problem Solving in the Classroom
• Creating and sustaining online problem-solving forums
• Methods in Evaluating Metacognitive Strategies

About this book

This book contributes to the field of mathematical problem solving by exploring current themes, trends and research perspectives. It does so by addressing five broad and related dimensions: problem solving heuristics, problem solving and technology, inquiry and problem posing in mathematics education, assessment of and through problem solving, and the problem solving environment.

Mathematical problem solving has long been recognized as an important aspect of mathematics, teaching mathematics, and learning mathematics. It has influenced mathematics curricula around the world, with calls for the teaching of problem solving as well as the teaching of mathematics through problem solving. And as such, it has been of interest to mathematics education researchers for as long as the field has existed. Research in this area has generally aimed at understanding and relating the processes involved in solving problems to students’ development of mathematical knowledge and problem solving skills. The accumulated knowledge and field developments have included conceptual frameworks for characterizing learners’ success in problem solving activities, cognitive, metacognitive, social and affective analysis, curriculum proposals, and ways to promote problem solving approaches. 

“The volume will be a useful addition to the libraries of education researchers and to mathematics teacher educators who are charged with supporting preservice or inservice teachers’ development of capacities to incorporate problem solving into their instruction. … this volume offer interesting insights into the phenomenon of problem solving and the technological tools and learning environments that support students to engage in problem solving.” (Duane Gaysay, MAA Reviews, August 16, 2020)

Editors and Affiliations

Bibliographic information.

Book Title : Mathematical Problem Solving

Book Subtitle : Current Themes, Trends, and Research

Editors : Peter Liljedahl, Manuel Santos-Trigo

Series Title : ICME-13 Monographs

DOI : https://doi.org/10.1007/978-3-030-10472-6

Publisher : Springer Cham

eBook Packages : Education , Education (R0)

Copyright Information : Springer Nature Switzerland AG 2019

Hardcover ISBN : 978-3-030-10471-9 Published: 21 February 2019

eBook ISBN : 978-3-030-10472-6 Published: 12 February 2019

Series ISSN : 2520-8322

Series E-ISSN : 2520-8330

Edition Number : 1

Number of Pages : XI, 362

Number of Illustrations : 30 b/w illustrations, 82 illustrations in colour

Topics : Mathematics Education , Teaching and Teacher Education , Study and Learning Skills , International and Comparative Education

• Publish with us

Policies and ethics

• Find a journal
• Track your research

share this!

April 10, 2024

This article has been reviewed according to Science X's editorial process and policies . Editors have highlighted the following attributes while ensuring the content's credibility:

fact-checked

trusted source

written by researcher(s)

Using research to solve societal problems starts with building connections and making space for young people

by Zoey England, Jennifer Forbey and Michael Muszynski, The Conversation

Often, when scientists do research around a specific societal challenge, they hope their work will help solve that larger problem. Yet translating findings into long-lasting, community-driven solutions is much harder than most expect.

It seems intuitive that scientists studying living organisms, microbes, and ecosystems could apply their findings to tackle food shortages, help keep environments healthy, and improve human and animal health . But it's not always that easy. Issues like climate change , renewable energy, public health, and migration are complex , making direct solutions challenging to develop and implement.

As a group of researchers invested in helping scientists create meaningful impact with their work, we understand problems like these will need experts from different fields and industries to work together.

This means we might need to reevaluate certain aspects of the inquiry process and embrace fresh perspectives if we, as members of the scientific community, want to improve our capacity for producing solutions-oriented research.

Defining use-inspired research

Science does not occur in a vacuum. Factors including funding availability, access to advanced technologies and political or social contexts can influence the kinds of studies that get done. A framework called use-inspired research and engagement, or UIRE, acknowledges this fact.

In use-inspired research , the potential applications of findings for society shape the directions of exploration.

In UIRE, researchers work with members of a community to figure out what questions they should look into. They form partnerships with other stakeholders, including governments, businesses of all scales and nonprofits, to form a collaborative foundation. This way, researchers can tailor investigations from the outset to be useful to and usable by decision-makers.

Translational research , or intentionally grounding scientific exploration in practical applications, isn't new . Use-inspired research expands on translational research, prioritizing building connections between practitioners and communities.

In the U.S., the passage of the CHIPS and Science Act in 2022 further codified use-inspired research. The act directed US$280 billion over the next 10 years toward funding scientific inquiry to boost domestic competitiveness, innovation and national security.

This legislation also authorized the establishment of the National Science Foundation's Directorate for Technology, Innovation and Partnerships, called NSF TIP . TIP marks the agency's first new directorate in over three decades, created with the aim of sparking the growth of diverse innovation and technology landscapes.

Producing science in partnership

In use-inspired research and engagement, collaboration is a big part of each project from the start, when the researchers are first deciding what to study. These cooperative partnerships continue throughout data collection and analysis. Together, these teams apply the results and develop products, implement behavior changes, or further inform community decision-making.

For example, a large hospital, an academic organization and several nonprofits may partner together to explore issues affecting health care accessibility in the region. Researchers collect data through surveys and interviews, and interpret the findings within the community's specific circumstances. They can then coordinate data evaluation with the health care and nonprofit partners, which helps take socioeconomic status, cultural beliefs and built infrastructure like grocery stores and public transportation into account.

This approach brings together the broad perspectives of a large hospital network, academic expertise around survey creation and data analysis, and specialized knowledge held by nonprofits. These groups can then collaborate further to develop specific programs, such as educational initiatives and enhanced health care services. They can tailor these to the needs of the community they serve.

Use-inspired research matters because it looks at all the different issues facing a community holistically and keeps them in mind when investigating potential solutions. UIRE is not a substitute for basic, foundational research, which explores new questions to fundamentally understand a topic. Rather, it's an approach centered around selecting questions and developing methods based on real-world importance.

UIRE creates a foundation for long-term, inclusive partnerships—and not just within academia. Government, community organizations, large companies and startups can all use the same principles of UIRE to share ideas and craft solutions to issues facing their communities. Individuals from all sorts of backgrounds are equally integral to the entire process, further amplifying the viewpoints present.

Use-inspired methods are not only relevant to improving research outcomes. A use-inspired approach drives innovation and technological advancements across sectors . When used in K-12 classrooms , UIRE leads to well-rounded students .

This approach can also improve learning in workforce development spaces, creating employees trained to build connections.

UIRE provides platforms for the general public to participate in conversations about issues impacting their lives that they may not have otherwise been a part of.

Harnessing early-career engagement

Use-inspired methods challenge not only how, but who contributes to and benefits from scientific inquiry. They also focus on making the findings accessible to those outside academia.

To craft necessary solutions for complex societal problems, institutions will need to continue backing traditional scholars who excel at pure basic research. At the same time, they can support training in use-inspired domains.

Early-career professionals across sectors will continue to play an important role in spreading and sustaining the cultural shifts necessary to embrace use-inspired research at a wider scale. These early-career professionals can bring fresh ideas to the table and craft innovative approaches to problems.

To support translational research long term, institutions and supervisors can support students in hands-on learning opportunities from the first year of undergraduate coursework to postgraduate fellowships. These opportunities can help students learn about UIRE and equip them with the skills needed to build cross-sector partnerships before entering the workforce.

By receiving mentorship from individuals outside academia, students and trainees can gain exposure to different career paths and find motivation to pursue opportunities outside traditional academic roles. This mentorship fosters creative problem-solving and adaptability.

UIRE provides a potential framework to addressing complex societal challenges. Creating opportunities for the ongoing involvement of young people will seed a vibrant future for use-inspired research and engagement.

Provided by The Conversation

Explore further

Feedback to editors

Using CO₂ and biomass, researchers find path to more environmentally friendly recyclable plastics

10 hours ago

Precision agriculture research identifies gene that controls production of flowers and fruits in pea plants

Long-term forest study shows tornado's effects linger 25 years later

11 hours ago

A new coating method in mRNA engineering points the way to advanced therapies

ATLAS provides first measurement of the W-boson width at the LHC

12 hours ago

Smart vest turns fish into underwater spies, providing a glimpse into aquatic life like never before

Ants in Colorado are on the move due to climate change

Caterpillar 'noses' are surprisingly sophisticated, researchers find

Building footprints could help identify neighborhood sociodemographic traits

13 hours ago

Fossilized dinosaur eggshells can preserve amino acids, the building blocks of proteins, over millions of years

14 hours ago

Relevant PhysicsForums posts

Interesting anecdotes in the history of physics.

19 hours ago

What are your favorite Disco "Classics"?

Apr 9, 2024

Cover songs versus the original track, which ones are better?

Biographies, history, personal accounts.

Apr 7, 2024

Purpose of the Roman bronze dodecahedrons: are you convinced?

Apr 6, 2024

Favorite Mashups - All Your Favorites in One Place

Apr 5, 2024

More from Art, Music, History, and Linguistics

Related Stories

Campus garden initiatives can help grow the next generation of environmental change-makers

Mar 7, 2024

Opinion: Person-centered health care means ensuring that affected communities are leaders and partners in research

Apr 2, 2024

Five ways to better build community with international students in Canada

Mar 20, 2024

Preparing for the next health crisis: COVID-19 showed the importance of community-engaged research

Students build science identity through immersive research experience

Jan 4, 2024

Expert tests if AI can help teach students accounting

Feb 27, 2024

Recommended for you

Are the world's cultures growing apart?

17 hours ago

First languages of North America traced back to two very different language groups from Siberia

Can the bias in algorithms help us see our own?

The 'Iron Pipeline': Is Interstate 95 the connection for moving guns up and down the East Coast?

Americans are bad at recognizing conspiracy theories when they believe they're true, says study

Apr 8, 2024

Let us know if there is a problem with our content

Use this form if you have come across a typo, inaccuracy or would like to send an edit request for the content on this page. For general inquiries, please use our contact form . For general feedback, use the public comments section below (please adhere to guidelines ).

Please select the most appropriate category to facilitate processing of your request

Thank you for taking time to provide your feedback to the editors.

Your feedback is important to us. However, we do not guarantee individual replies due to the high volume of messages.

E-mail the story

Your email address is used only to let the recipient know who sent the email. Neither your address nor the recipient's address will be used for any other purpose. The information you enter will appear in your e-mail message and is not retained by Phys.org in any form.

Newsletter sign up

Get weekly and/or daily updates delivered to your inbox. You can unsubscribe at any time and we'll never share your details to third parties.

More information Privacy policy

Donate and enjoy an ad-free experience

We keep our content available to everyone. Consider supporting Science X's mission by getting a premium account.

E-mail newsletter

• Bipolar Disorder
• Therapy Center
• When To See a Therapist
• Types of Therapy
• Best Online Therapy
• Best Couples Therapy
• Best Family Therapy
• Managing Stress
• Sleep and Dreaming
• Understanding Emotions
• Self-Improvement
• Healthy Relationships
• Student Resources
• Personality Types
• Guided Meditations
• Verywell Mind Insights
• 2023 Verywell Mind 25
• Mental Health in the Classroom
• Editorial Process
• Meet Our Review Board
• Crisis Support

Overview of the Problem-Solving Mental Process

Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Rachel Goldman, PhD FTOS, is a licensed psychologist, clinical assistant professor, speaker, wellness expert specializing in eating behaviors, stress management, and health behavior change.

• Identify the Problem
• Define the Problem
• Form a Strategy
• Organize Information
• Allocate Resources
• Monitor Progress
• Evaluate the Results

Frequently Asked Questions

Problem-solving is a mental process that involves discovering, analyzing, and solving problems. The ultimate goal of problem-solving is to overcome obstacles and find a solution that best resolves the issue.

The best strategy for solving a problem depends largely on the unique situation. In some cases, people are better off learning everything they can about the issue and then using factual knowledge to come up with a solution. In other instances, creativity and insight are the best options.

It is not necessary to follow problem-solving steps sequentially, It is common to skip steps or even go back through steps multiple times until the desired solution is reached.

In order to correctly solve a problem, it is often important to follow a series of steps. Researchers sometimes refer to this as the problem-solving cycle. While this cycle is portrayed sequentially, people rarely follow a rigid series of steps to find a solution.

The following steps include developing strategies and organizing knowledge.

1. Identifying the Problem

While it may seem like an obvious step, identifying the problem is not always as simple as it sounds. In some cases, people might mistakenly identify the wrong source of a problem, which will make attempts to solve it inefficient or even useless.

Some strategies that you might use to figure out the source of a problem include :

• Asking questions about the problem
• Breaking the problem down into smaller pieces
• Looking at the problem from different perspectives
• Conducting research to figure out what relationships exist between different variables

2. Defining the Problem

After the problem has been identified, it is important to fully define the problem so that it can be solved. You can define a problem by operationally defining each aspect of the problem and setting goals for what aspects of the problem you will address

At this point, you should focus on figuring out which aspects of the problems are facts and which are opinions. State the problem clearly and identify the scope of the solution.

3. Forming a Strategy

After the problem has been identified, it is time to start brainstorming potential solutions. This step usually involves generating as many ideas as possible without judging their quality. Once several possibilities have been generated, they can be evaluated and narrowed down.

The next step is to develop a strategy to solve the problem. The approach used will vary depending upon the situation and the individual's unique preferences. Common problem-solving strategies include heuristics and algorithms.

• Heuristics are mental shortcuts that are often based on solutions that have worked in the past. They can work well if the problem is similar to something you have encountered before and are often the best choice if you need a fast solution.
• Algorithms are step-by-step strategies that are guaranteed to produce a correct result. While this approach is great for accuracy, it can also consume time and resources.

Heuristics are often best used when time is of the essence, while algorithms are a better choice when a decision needs to be as accurate as possible.

4. Organizing Information

Before coming up with a solution, you need to first organize the available information. What do you know about the problem? What do you not know? The more information that is available the better prepared you will be to come up with an accurate solution.

When approaching a problem, it is important to make sure that you have all the data you need. Making a decision without adequate information can lead to biased or inaccurate results.

5. Allocating Resources

Of course, we don't always have unlimited money, time, and other resources to solve a problem. Before you begin to solve a problem, you need to determine how high priority it is.

If it is an important problem, it is probably worth allocating more resources to solving it. If, however, it is a fairly unimportant problem, then you do not want to spend too much of your available resources on coming up with a solution.

At this stage, it is important to consider all of the factors that might affect the problem at hand. This includes looking at the available resources, deadlines that need to be met, and any possible risks involved in each solution. After careful evaluation, a decision can be made about which solution to pursue.

6. Monitoring Progress

After selecting a problem-solving strategy, it is time to put the plan into action and see if it works. This step might involve trying out different solutions to see which one is the most effective.

It is also important to monitor the situation after implementing a solution to ensure that the problem has been solved and that no new problems have arisen as a result of the proposed solution.

Effective problem-solvers tend to monitor their progress as they work towards a solution. If they are not making good progress toward reaching their goal, they will reevaluate their approach or look for new strategies .

7. Evaluating the Results

After a solution has been reached, it is important to evaluate the results to determine if it is the best possible solution to the problem. This evaluation might be immediate, such as checking the results of a math problem to ensure the answer is correct, or it can be delayed, such as evaluating the success of a therapy program after several months of treatment.

Once a problem has been solved, it is important to take some time to reflect on the process that was used and evaluate the results. This will help you to improve your problem-solving skills and become more efficient at solving future problems.

A Word From Verywell​

It is important to remember that there are many different problem-solving processes with different steps, and this is just one example. Problem-solving in real-world situations requires a great deal of resourcefulness, flexibility, resilience, and continuous interaction with the environment.

Get Advice From The Verywell Mind Podcast

Hosted by therapist Amy Morin, LCSW, this episode of The Verywell Mind Podcast shares how you can stop dwelling in a negative mindset.

Follow Now : Apple Podcasts / Spotify / Google Podcasts

You can become a better problem solving by:

• Practicing brainstorming and coming up with multiple potential solutions to problems
• Being open-minded and considering all possible options before making a decision
• Breaking down problems into smaller, more manageable pieces
• Asking for help when needed
• Researching different problem-solving techniques and trying out new ones
• Learning from mistakes and using them as opportunities to grow

It's important to communicate openly and honestly with your partner about what's going on. Try to see things from their perspective as well as your own. Work together to find a resolution that works for both of you. Be willing to compromise and accept that there may not be a perfect solution.

Take breaks if things are getting too heated, and come back to the problem when you feel calm and collected. Don't try to fix every problem on your own—consider asking a therapist or counselor for help and insight.

If you've tried everything and there doesn't seem to be a way to fix the problem, you may have to learn to accept it. This can be difficult, but try to focus on the positive aspects of your life and remember that every situation is temporary. Don't dwell on what's going wrong—instead, think about what's going right. Find support by talking to friends or family. Seek professional help if you're having trouble coping.

Davidson JE, Sternberg RJ, editors.  The Psychology of Problem Solving .  Cambridge University Press; 2003. doi:10.1017/CBO9780511615771

Sarathy V. Real world problem-solving .  Front Hum Neurosci . 2018;12:261. Published 2018 Jun 26. doi:10.3389/fnhum.2018.00261

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

ORIGINAL RESEARCH article

Integrating inquiry and mathematical modeling when teaching a common topic in lower secondary school: an istem approach provisionally accepted.

• 1 Hong Kong Baptist University, Hong Kong, SAR China

The final, formatted version of the article will be published soon.

The world has been increasingly shaped by Science, Technology, Engineering and Mathematics (STEM). This has resulted in educational systems across the globe implementing STEM education. To reap maximum benefits, researchers are now advocating for the integration of STEM domains. In recent studies, the integration of science and mathematics has become increasingly popular. The domains are much more suitable for integration because of their fields of application and their mutual approach towards problem-solving. However, there is little empirical evidence to drive the development of a practical model for classroom implementation. This study aims to cover that gap through integrating mathematics and science concepts when teaching a common topic to two classes of Form 1 (13-14 years) students. A mathematics and a science teacher went through two cycles of lesson study, integrating and teaching the concept of density. Results show a strong synergy between the BSCS 5E instructional model of inquiry and mathematical modeling; hence the methodological approaches can be used to integrate common topics like density. Further, teacher collaboration, teacher immersion in the iSTEM practices, teacher's knowledge, and skills of the other subject and an in-depth understanding of a problem and its contextualization, are variables that can be capitalized on to enhance the teacher's capacity to implement innovative and integrated STEM programs effectively.

Keywords: iSTEM1, Inquiry2, mathematical modeling3, Integration model4, Science5. Mathematics6, Density7

Received: 26 Jan 2024; Accepted: 10 Apr 2024.

Copyright: © 2024 Manunure and Leung. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Mr. Kevin Manunure, Hong Kong Baptist University, Kowloon, Hong Kong, SAR China

People also looked at