Advertisement

Topoi

, Volume 37, Issue 1, pp 185–199 | Cite as

Stimulating Reflection and Self-correcting Reasoning Through Argument Mapping: Three Approaches

  • Michael H. G. Hoffmann
Article

Abstract

A large body of research in cognitive science differentiates human reasoning into two types: fast, intuitive, and emotional “System 1” thinking, and slower, more reflective “System 2” reasoning. According to this research, human reasoning is by default fast and intuitive, but that means that it is prone to error and biases that cloud our judgments and decision making. To improve the quality of reasoning, critical thinking education should develop strategies to slow it down and to become more reflective. The goal of such education should be to enable and motivate students to identify weaknesses, gaps, biases, and limiting perspectives in their own reasoning and to correct them. This contribution discusses how this goal could be achieved with regard to reasoning that involves the construction of arguments; or more precisely: how computer-supported argument visualization (CSAV) tools could be designed that support reflection on the quality of arguments and their improvement. Three types of CSAV approaches are distinguished that focus on reflection and self-correcting reasoning. The first one is to trigger reflection by confronting the user with specific questions that direct attention to critical points. The second approach uses templates that, on the one hand, provide a particular structure to reason about an issue by means of arguments and, on the other, include prompts to enter specific items. And a third approach is realized in specifically designed user guidance (“scripts”) that attempts to trigger reflection and self-correction. These types of approaches are currently realized only in very few CSAV tools. In order to inform the future development of what I call reflection tools, this article discusses the potential and limitations of these types and tools with regard to five explanations of the observation that students hardly ever engage in substantial revisions of what they wrote: a lack of strategies how to do it; cognitive overload; certain epistemic beliefs; myside bias; and over-confidence in the quality of one’s own reasoning. The question is: To what degree can each of the CSAV approaches and tools address these five potential obstacles to reflection and self-correction?

Keywords

Argumentation Cognitive load Cognitive schema Computer-supported argument visualization Critical thinking Education Myside bias Reflective judgement Self-regulated learning 

Notes

Acknowledgments

Many thanks to Bryan Norton for helpful feedback on the first version of this paper. I am grateful also for the insights and suggestions provided by two anonymous reviewers, and for the excellent work done by Frank Zenker, the editor of this special issue.

References

  1. Andriessen JEB, Baker M, Suthers DD (eds) (2003) Arguing to learn. Confronting cognitions in computer-supported collaborative learning environments. Kluwer Academic Publishers, DordrechtGoogle Scholar
  2. Atkinson K, Bench-Capon T (2007) Practical reasoning as presumptive argumentation using action based alternating transition systems. Artif Intell 171(10–15):855–874. doi: 10.1016/j.artint.2007.04.009 CrossRefGoogle Scholar
  3. Azevedo R, Hadwin AF (2005) Scaffolding self-regulated learning and metacognition—implications for the design of computer-based scaffolds. Instr Sci 33(5–6):367–379CrossRefGoogle Scholar
  4. Braet AC (2004) The oldest typology of argumentation schemes. Argumentation 18(1):127–148CrossRefGoogle Scholar
  5. Bridwell LS (1980) Revising strategies in twelfth grade students’ transactional writing. Res Teach Engl 14(3):197–222Google Scholar
  6. Butler JA, Britt MA (2011) Investigating instruction for improving revision of argumentative essays. Writ Commun 28(1):70–96. doi: 10.1177/0741088310387891 CrossRefGoogle Scholar
  7. Campbell J, Smith D, Brooker R (1998) From conception to performance: how undergraduate students conceptualise and construct essays. High Educ 36(4):449–469. doi: 10.2307/3448209 CrossRefGoogle Scholar
  8. Catrambone R (1998) The subgoal learning model: creating better examples so that students can solve novel problems. J Exp Psychol Gen 127(4):355–376. doi: 10.1037/0096-3445.127.4.355 CrossRefGoogle Scholar
  9. Catrambone R, Holyoak KJ (1990) Learning subgoals and methods for solving probability problems. Mem Cogn 18(6):593–603. doi: 10.3758/bf03197102 CrossRefGoogle Scholar
  10. Cowan N (2001) The magical number 4 in short-term memory: a reconsideration of mental storage capacity. Behav Brain Sci 24:87–114CrossRefGoogle Scholar
  11. Dettori G, Persico D (2011) Fostering self-regulated learning through ICT. Information Science Reference, Hershey PACrossRefGoogle Scholar
  12. Duschl RA, Schweingruber HA, Shouse AW, National Research Council (U.S.), Committee on Science Learning Kindergarten Through Eighth Grade, National Research Council (U.S.), Board on Science Education, National Research Council (U.S.) (2007) Taking science to school: learning and teaching science in grades K-8. Washington, D.C.: National Academies PressGoogle Scholar
  13. Ericsson KA, Kintsch W (1995) Long-term working memory. Psychol Rev 102(2):211–245CrossRefGoogle Scholar
  14. Facione PA (1990) Critical thinking: a statement of expert consensus for purposes of educational assessment and instruction. The Delphi Report. Executive summary. http://assessment.aas.duke.edu/documents/Delphi_Report.pdf
  15. Feldman R (1994) Good arguments. In: Schmitt FF (ed) Socializing epistemology. The social dimensions of knowledge. Rowman & Littlefield Publishers, Lanham, pp 159–188Google Scholar
  16. Felton M, Crowell A, Liu T (2015) Arguing to agree: mitigating my-side bias through consensus-seeking dialogue. Writ Commun 32(3):317–331CrossRefGoogle Scholar
  17. Fitzgerald J (1987) Research on revision in writing. Rev Educ Res 57(4):481–506CrossRefGoogle Scholar
  18. Flower L, Hayes JR, Carey L, Schriver K, Stratman J (1986) Detection, diagnosis, and the strategies of revision. Coll Compos Commun 37(1):16–55. doi: 10.2307/357381 CrossRefGoogle Scholar
  19. Frederick S (2005) Cognitive reflection and decision making. J Econ Perspect 19(4):25–42. doi: 10.1257/089533005775196732 CrossRefGoogle Scholar
  20. Gastil J, Levine P (eds) (2005) The deliberative democracy handbook: strategies for effective civic engagement in the twenty-first century. Jossey-Bass, San FranciscoGoogle Scholar
  21. Gerjets P, Scheiter K, Catrambone R (2006) Can learning from molar and modular worked examples be enhanced by providing instructional explanations and prompting self-explanations? Learn Instr 16(2):104–121. doi: 10.1016/j.learninstruc.2006.02.007 CrossRefGoogle Scholar
  22. Govier T (2010) A practical study of argument, 7th edn. Cengage Learning, BelmontGoogle Scholar
  23. Groarke L (1999) Deductivism within pragma-dialectics. Argumentation 13(1):1–16CrossRefGoogle Scholar
  24. Harrell M (2011) Argument diagramming and critical thinking in introductory philosophy. High Educ Res Dev 30(3):371–385CrossRefGoogle Scholar
  25. Hoffmann MHG (2011a) Analyzing framing processes in conflicts and communication by means of logical argument mapping. In WA Donohue, RG Rogan, S Kaufman (eds) Framing matters: perspectives on negotiation research and practice in communication (pp. 136–164). New York, NY: Peter Lang (pre-print available at http://works.bepress.com/michael_hoffmann/37/)
  26. Hoffmann MHG (2011b) Climate Ethics: structuring Deliberation by means of Logical Argument Mapping. Journal of Speculative Philosophy 25(1):64–97CrossRefGoogle Scholar
  27. Hoffmann MHG (2015a) Changing Philosophy through Technology: complexity and Computer-Supported Collaborative Argument Mapping. Philosophy & Technology 28(2):167–188. doi: 10.1007/s13347-013-0143-6 CrossRefGoogle Scholar
  28. Hoffmann MHG (2015b) Reflective argumentation: a cognitive function of arguing. Argumentation, 1–33. doi: 10.1007/s10503-015-9388-9
  29. Hoffmann MHG (submitted) How to improve the quality of arguments on the web. In: Paglieri F, Reed C (eds) Arguing on the web: theory, analysis and application. John Benjamins, Amsterdam, NLGoogle Scholar
  30. Hoffmann MHG, Lingle J (2015) Facilitating problem-based learning by means of collaborative argument visualization software. Teach Philos 38(4):371–398. doi: 10.5840/teachphil2015112039 Google Scholar
  31. Hogan MJ, Dwyer CP, Harney OM, Noone C, Conway RJ (2015) Metacognitive Skill development and applied systems science: a framework of metacognitive skills, self-regulatory functions and real-world applications. In: Peña-Ayala A (ed) Metacognition. Fundaments, applications, and trends: a profile of the current state-of-the-art. Springer, Cham, New York, pp 75–106Google Scholar
  32. Kahan DM (2013) Ideology, motivated reasoning, and cognitive reflection. Judgment and Decision Making 8(4):407–424Google Scholar
  33. Kahneman D (2011) Thinking, fast and slow, 1st edn. Farrar, Straus and Giroux, New YorkGoogle Scholar
  34. Kalyuga S (2010) Schema acquisition and sources of cognitive load. In: Plass JL, Moreno R, Brünken R (eds) Cognitive load theory. Cambridge University Press, Cambridge; New York, pp 48–64CrossRefGoogle Scholar
  35. Katzav J, Reed CA (2004) On argumentation schemes and the natural classification of arguments. Argumentation 18(2):239–259CrossRefGoogle Scholar
  36. Kellogg RT (1990) Effectiveness of prewriting strategies as a function of task demands. Am J Psychol 103(3):327–342. doi: 10.2307/1423213 CrossRefGoogle Scholar
  37. King PM, Kitchener KS (1994) Developing reflective judgment. Understanding and promoting intellectual growth and critical thinking in adolescents and adults, 1st edn. Jossey-Bass Publishers, San FranciscoGoogle Scholar
  38. King PM, Kitchener KS (2002) The reflective judgment model: twenty years of research on epistemic cognition. In: Hofer BK, Pintrich PR (eds) Personal epistemology: the psychology of beliefs about knowledge and knowing. Erlbaum, MahwahGoogle Scholar
  39. Kirschner PA, Buckingham Shum SJ, Carr CS (eds) (2003) Visualizing argumentation: software tools for collaborative and educational sense-making. Springer, LondonGoogle Scholar
  40. Kitchener KS (1983) Cognition, metacognition, and epistemic cognition. A 3-level model of cognitive processing. Hum Dev 26(4):222–232CrossRefGoogle Scholar
  41. Klein M, Spada P, Calabretta R (2012) Enabling deliberations in a political party using large-scale argumentation: a preliminary report. Proceedings of the 10th international conference on the design of cooperative systems. https://www.researchgate.net/publication/263307756
  42. Kobbe L, Weinberger A, Dillenbourg P, Harrer A, Hamalainen R, Hakkinen P, Fischer F (2007) Specifying computer-supported collaboration scripts. Int J Comput Support Collab Learn 2(2–3):211–224. doi: 10.1007/s11412-007-9014-4 CrossRefGoogle Scholar
  43. Kuhn TS (1970) The structure of scientific revolutions, 2nd edn. The University of Chicago Press, ChicagoGoogle Scholar
  44. Kuhn D (1991) The skills of argument. Cambridge University Press, CambridgeCrossRefGoogle Scholar
  45. Kuhn D (2005) Education for thinking. Harvard University Press, CambridgeGoogle Scholar
  46. Kuhn D, Cheney R, Weinstock M (2000) The development of epistemological understanding. Cogn Dev 15(3):309–328. doi: 10.1016/s0885-2014(00)00030-7 CrossRefGoogle Scholar
  47. Macarthur CA, Graham S, Harris KR (2004) Insights from instructional research on revision with struggling writers. In: Allal L, Chanquoy L, Largy P (eds) Revision cognitive and instructional processes, vol 13. Springer, Netherlands, pp 125–137CrossRefGoogle Scholar
  48. Miller GA (1956) The magical number seven, plus or minus two: some limits on our capacity for processing information. Psychol Rev 93:181–186Google Scholar
  49. Nussbaum EM, Bendixen LD (2003) Approaching and avoiding arguments: the role of epistemological beliefs, need for cognition, and extraverted personality traits. Contemp Educ Psychol 28(4):573–595. doi: 10.1016/s0361-476x(02)00062-0 CrossRefGoogle Scholar
  50. Nussbaum EM, Winsor DL, Aqui YM, Poliquin AM (2007) Putting the pieces together: online argumentation vee diagrams enhance thinking during discussions. Int J Comput Support Collab Learn 2(4):479–500. doi: 10.1007/s11412-007-9025-1 CrossRefGoogle Scholar
  51. Nussbaum EM, Sinatra G, Poliquin A (2008) Role of epistemic beliefs and scientific argumentation in science learning. Int J Sci Educ 30(15):1977–1999. doi: 10.1080/09500690701545919 CrossRefGoogle Scholar
  52. Okada A, Buckingham Shum S, Sherborne T (2014) Knowledge cartography. Software tools and mapping techniques. Springer, New YorkGoogle Scholar
  53. Pollock JL (1995) Cognitive carpentry. A blueprint for how to build a person. MIT Press, CambridgeGoogle Scholar
  54. Rosenberg JF (1996) The practice of philosophy. A handbook for beginners, 3rd edn. Prentice Hall, Upper Saddle RiverGoogle Scholar
  55. Sampson V, Enderle P, Grooms J, Witte S (2013) Writing to learn by learning to write during the school science laboratory: helping middle and high school students develop argumentative writing skills as they learn core ideas. Sci Educ 97(5):643–670. doi: 10.1002/sce.21069 CrossRefGoogle Scholar
  56. Schank RC, Abelson RP (1977) Scripts, plans, goals, and understanding. An inquiry into human knowledge structures. L. Erlbaum Associates, HillsdaleGoogle Scholar
  57. Scheuer O, Loll F, Pinkwart N, McLaren BM (2010) Computer-supported argumentation: a review of the state of the art. Int J Comput Support Collab Learn 5(1):43–102CrossRefGoogle Scholar
  58. Schneider J, Groza T, Passant A (2013) A review of argumentation for the social semantic web. Semant Web 4(2):159–218. doi: 10.3233/SW-2012-0073 Google Scholar
  59. Schunk DH, Zimmerman BJ (1998) Self-regulated learning: from teaching to self-reflective practice. Guilford Press, New YorkGoogle Scholar
  60. Schunk DH, Zimmerman BJ (2008) Motivation and self-regulated learning: theory, research, and applications. Lawrence Erlbaum Associates, New YorkGoogle Scholar
  61. Sommers N (1980) Revision strategies of student writers and experienced adult writers. Coll Compos Commun 31(4):378–388. doi: 10.2307/356588 CrossRefGoogle Scholar
  62. Stanovich KE, West RF (2000) Individual differences in reasoning: implications for the rationality debate? Behav Brain Sci 23(5):645–665. doi: 10.1017/s0140525x00003435 CrossRefGoogle Scholar
  63. Stanovich KE, West RF, Toplak ME (2013) Myside bias, rational thinking, and intelligence. Curr Dir Psychol Sci 22(4):259–264. doi: 10.1177/0963721413480174 CrossRefGoogle Scholar
  64. Sweller J (1994) Cognitive load theory, learning difficulty, and instructional design. Learn Instr 4(4):295–312. doi: 10.1016/0959-4752(94)90003-5 CrossRefGoogle Scholar
  65. Sweller J (2010) Cognitive load theory: recent theoretical advances. In: Plass JL, Moreno R, Brünken R (eds) Cognitive load theory. Cambridge University Press, Cambridge; New York, pp 29–47CrossRefGoogle Scholar
  66. Toniolo A, Norman TJ, Etuk A, Cerutti F, Ouyang RW, Srivastava M, et al. (2015) Supporting reasoning with different types of evidence in intelligence analysis. Paper presented at the proceedings of the 2015 international conference on autonomous agents and multiagent systems, Istanbul, Turkey. http://dl.acm.org/citation.cfm?id=2773254
  67. Toplak ME, West RF, Stanovich KE (2011) The cognitive reflection test as a predictor of performance on heuristics-and-biases tasks. Mem Cogn 39(7):1275–1289. doi: 10.3758/s13421-011-0104-1 CrossRefGoogle Scholar
  68. Torrance M, Fidalgo R, García J-N (2007) The teachability and effectiveness of cognitive self-regulation in sixth-grade writers. Learn Instr 17(3):265–285. doi: 10.1016/j.learninstruc.2007.02.003 CrossRefGoogle Scholar
  69. van Bruggen JM, Boshuizen HPA, Kirschner PA (2003) A cognitive framework for cooperative problem solving with argument visualization. In: Kirschner PA, Buckingham Shum SJ, Carr CS (eds) Visualizing argumentation: software tools for collaborative and educational sense-making. Springer, London, pp 25–47CrossRefGoogle Scholar
  70. Walton DN (1996) Argumentation schemes for presumptive reasoning. Lawrence Erlbaum, MahwahGoogle Scholar
  71. Walton DN (2007) Visualization tools, argumentation schemes and expert opinion evidence in law. Law, Probability and Risk, 6, 119–140. http://lpr.oxfordjournals.org/content/6/1-4/119.full.pdf doi: 10.1093/lpr/mgm033
  72. Walton DN (2012) Using argumentation schemes for argument extraction: a bottom-up method. Int J Cogn Inf Nat Intell (IJCINI) 6(3):33–60CrossRefGoogle Scholar
  73. Walton DN, Reed C, Macagno F (2008) Argumentation schemes. Cambridge University Press, Cambridge; New YorkCrossRefGoogle Scholar
  74. Wyner A, Atkinson K, Bench-Capon T (2012) A functional perspective on argumentation schemes. Paper presented at the 9th International workshop on argumentation in multi-agent systems (ArgMAS 2012)Google Scholar
  75. Zimmerman BJ, Schunk DH (2001) Self-regulated learning and academic achievement: theoretical perspectives, 2nd edn. Lawrence Erlbaum Associates Publishers, MahwahGoogle Scholar
  76. Zohar A, Dori YJ (2012) Metacognition in science education: trends in current research. Springer, New YorkCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  1. 1.School of Public PolicyGeorgia Institute of TechnologyAtlantaUSA

Personalised recommendations