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Integrating failure in case-based learning: a conceptual framework for failure classification and its instructional implications

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Abstract

Employing authentic cases experienced by practitioners in educational contexts is critical to expanding students’ experience and engaging students in authentic problems to promote their real-world problem-solving skills. Although in real life, practitioners experience both success and failure and learn from both, little research has been done so far to conceptualize why and how failure should be employed in case-based learning (CBL) as a way to develop students’ abilities to solve ill-structured problems. The goal of this paper is to theoretically justify the need for integrating failure cases in CBL to help students become better problem solvers. To achieve this, this paper attempted to approach failure from the perspective of human error and proposed a classification of failure based on the degree of explicitness of human error involved in problem solving. Based on discussions of potential benefits and challenges of integrating different types of failure cases in education, this paper also proposed instructional design strategies that can help facilitate better use of failure cases.

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References

  • Aamodt, A., & Plaza, E. (1994). Case-based reasoning: Foundational issues, methodological variations, and system approaches. Artificial Intelligence Communications, 7(1), 39–59.

    Google Scholar 

  • Adams, D. M., McLaren, B. M., Durkin, K., Mayer, R. E., Rittle-Johnson, B., Isotani, S., et al. (2014). Using erroneous examples to improve mathematics learning with a web-based tutoring system. Computers in Human Behavior, 36, 401–411.

    Article  Google Scholar 

  • Andrieux, M., & Proteau, L. (2013). Observation learning of a motor task: Who and when? Experimental Brain Research, 229(1), 125–137.

    Article  Google Scholar 

  • Atkinson, R. K., Derry, S. J., Renkl, A., & Waltham, D. (2000). Learning from examples: Instructional principles from the worked examples research. Review of Educational Research, 70(2), 181–214.

    Article  Google Scholar 

  • Ayers, M. S., & Reder, L. M. (1998). A theoretical review of the misinformation effect: Predictions from an activation-based memory model. Psychonomic Bulletin and Review, 5, 1–21.

    Article  Google Scholar 

  • Bandura, A. (1977). Social learning theory (2nd ed.). Englewood Cliffs, NJ: Prentice Hall.

    Google Scholar 

  • Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Englewood Cliffs, NJ: Prentice-Hall.

    Google Scholar 

  • Baum, J. A. C., & Dahlin, K. B. (2007). Aspiration performance and railroads’ patterns of learning from train wrecks and crashes. Organization Science, 18(3), 368–385.

    Article  Google Scholar 

  • Baumard, P., & Starbuck, W. H. (2005). Learning from failures: Why it may not happen. Long Range Planning, 38(3), 281–291.

    Article  Google Scholar 

  • Bjerrum, A. S., Hilberg, O., van Gog, T., Charles, P., & Eika, B. (2013). Effects of modelling examples in complex procedural skills training: A randomised study. Medical Education, 47, 888–898.

    Article  Google Scholar 

  • Booth, J. L., Lange, K. E., Koedinger, K. R., & Newton, K. J. (2013). Using example problems to improve student learning in algebra: Differentiating between correct and incorrect examples. Learning and Instruction, 25, 24–34.

    Article  Google Scholar 

  • Boud, D., Keogh, R., & Walker, D. (1985). Reflection turning experience into learning. New York: Nichols Publishers.

    Google Scholar 

  • Cannon, M. D., & Edmondson, A. C. (2005). Failing to learn and learning to fail (intelligently): How great organizations put failure to work to innovate and improve. Long Range Planning, 38(3), 299–319.

    Article  Google Scholar 

  • Catino, M., & Patriotta, G. (2013). Learning from errors: Cognition, emotions and safety culture in the Italian Air Force. Organization Studies, 34(4), 437–467.

    Article  Google Scholar 

  • Chi, M. T. H., Bassok, M., Lewis, M., Reimann, P., & Glaser, R. (1989). Self-explanations: How students study and use examples in learning to solve problems. Cognitive Science, 13, 145–182.

    Article  Google Scholar 

  • Chi, M. T. H., & Glaser, R. (1985). Problem solving ability. In R. Sternberg (Ed.), Human abilities: An information-processing approach (pp. 227–257). San Francisco: W. H. Freeman and Co.

    Google Scholar 

  • Choi, I., Hong, Y. C., Park, H., & Lee, Y. (2013). Case-based learning for anesthesiology: Enhancing dynamic decision-making skills through cognitive apprenticeship and cognitive flexibility. In R. Luckin, P. Goodyear, B. Grabowski, S. Puntambeker, J. Underwood, & N. Winters (Eds.), Handbook on design in educational technology (pp. 230–240). New York: Routledge.

    Google Scholar 

  • Choi, I., & Lee, K. (2009). Designing and implementing a case-based learning environment for enhancing ill-structured problem solving: Classroom management problems for prospective teachers. Educational Technology Research and Development, 57, 99–129.

    Article  Google Scholar 

  • Collins, A., Brown, J. S., & Holum, A. (1991). Cognitive apprenticeship: Making thinking visible. American Educator, 15(3), 6–11, 38–46.

  • Creevy, K. E., Cornell, K. K., Schmiedt, C., Park, H., Rong, H., Radlinsky, M. G., et al. (2018). Impact of expert commentary and student reflection on veterinary clinical decision-making skills in an innovative electronic-learning case-based platform. Journal of Veterinary Medical Education, 45(3), 307–319.

    Article  Google Scholar 

  • Custers, E. J., Regehr, G., McCulloch, W., Peniston, C., & Reznick, R. (1999). The effects of modelling on learning a simple surgical procedure: See one, do one or see many, do one? Advanced Health Science Education: Theory and Practice, 4(2), 123–143.

    Article  Google Scholar 

  • D’Mello, S., Lehman, B., Pekrun, R., & Graesser, A. (2014). Confusion can be beneficial for learning. Learning and Instruction, 29, 153–170. https://doi.org/10.1016/j.learninstruc.2012.05.003.

    Article  Google Scholar 

  • Domuracki, K., Wong, A., Olivieri, L., & Grierson, L. E. M. (2015). The impacts of observing flawed and flawless demonstrations on clinical skill learning. Medical Education, 49, 186–192.

    Article  Google Scholar 

  • Edelson, D. C. (1996). Learning from cases and questions: The Socratic case-based teaching architecture. The Journal of the Learning Sciences, 5(4), 357–410.

    Article  Google Scholar 

  • Edmondson, A. C. (2011). Strategies for learning from failure. Harvard Business Review, 89(4), 49–55.

    Google Scholar 

  • Ellet, W. (2007). The case study handbook: How to read, discuss, and write persuasively about cases. Boston: Harvard Business School Press.

    Google Scholar 

  • Ellis, S., & Davidi, I. (2005). After-event reviews: Drawing lessons from successful and failed experience. Journal of Applied Psychology, 90(5), 857–871.

    Article  Google Scholar 

  • Ellis, S., Mendel, R., & Nir, M. (2006). Learning from successful and failed experience: The moderating role of kind of after-event review. Journal of Applied Psychology, 91(3), 669–680.

    Article  Google Scholar 

  • Ertmer, P. A., & Koehler, A. A. (2014). Online case-based discussions: Examining coverage of the afforded problem space. Educational Technology Research and Development, 62(5), 617–636.

    Article  Google Scholar 

  • Ferguson, W., Bareiss, R., Birnbaum, L., & Osgood, R. (1992). ASK systems: An approach to the realization of story-based teachers. Journal of the Learning Sciences, 2(1), 95–134.

    Article  Google Scholar 

  • Fischer, M. A., Mazor, K. M., Baril, J., Alper, E., DeMarco, D., & Pugnaire, M. (2006). Learning from mistakes: Factors that influence how students and residents learn from medical errors. Journal of General Internal Medicine, 21, 419–423. https://doi.org/10.1111/j.1525-1497.2006.00420.x.

    Article  Google Scholar 

  • Gallagher, T. H. (2009). A 62-year-old woman with skin cancer who experienced wrong-site surgery. Journal of the American Medical Association, 302(6), 669–677.

    Article  Google Scholar 

  • Gartmeier, M., Bauer, J., Gruber, H., & Heid, H. (2008). Negative knowledge: Understanding professional learning and expertise. Vocations and Learning, 1(2), 87–103.

    Article  Google Scholar 

  • Graber, M., Gordon, R., & Franklin, N. (2002). Reducing diagnostic errors in medicine: What’s the goal? Academic Medicine, 77, 981–992.

    Article  Google Scholar 

  • Grassinger, R., & Dresel, M. (2017). Who learns from errors on a class test? Antecedents and profiles of adaptive reactions to errors in a failure situation. Learning and Individual Differences, 53, 61–68.

    Article  Google Scholar 

  • Grierson, L. E., Barry, M., Kapralos, B., Carnahan, H., & Dubrowski, A. (2012). The role of collaborative interactivity in the observational practice of clinical skills. Medical Education, 46(4), 409–416.

    Article  Google Scholar 

  • GroBe, C., & Renkl, A. (2007). Finding and fixing errors in worked examples: Can this foster learning outcomes? Learning and Instruction, 17(6), 612–634.

    Article  Google Scholar 

  • Groopman, J. (2007). How doctors think. New York: Houghton Mifflin.

    Google Scholar 

  • Hattie, J., & Timperley, H. (2007). The power of feedback. Review of Educational Research, 77, 81–112.

    Article  Google Scholar 

  • Heimbeck, D., Frese, M., Sonneentag, S., & Keith, N. (2003). Integrating errors into the training process: The function of error management instructions and the role of goal orientation. Personnel Psychology, 56(2), 333–361.

    Article  Google Scholar 

  • Herreid, C. F. (2007). Start with a story: The case study method of teaching college science. Arlington, VA: NSTA Press.

    Google Scholar 

  • Hong, Y. C., & Choi, I. (2011). Three dimensions of reflective thinking in solving design problems: A conceptual model. Educational Technology Research and Development, 59, 687–710.

    Article  Google Scholar 

  • Huang, X. (2017). Example-based learning: Effects of different types of examples on student performance, cognitive load and self-efficacy in a statistical learning task. Interactive Learning Environments, 25(3), 28–294. https://doi.org/10.1080/10494820.2015.1121154.

    Article  Google Scholar 

  • Jonassen, D. H. (1997). Instructional design models for well-structured and ill-structured problem-solving learning outcomes. Educational Technology Research and Development, 45(1), 65–94.

    Article  Google Scholar 

  • Jonassen, D. H. (2000). Toward a design theory of problem solving. Educational Technology Research and Development, 48(4), 63–85.

    Article  Google Scholar 

  • Jonassen, D. H. (2011). Learning to solve problems: A handbook for designing problem-solving learning environments. New York: Routledge.

    Google Scholar 

  • Jonassen, D. H. (2012). Designing for decision making. Educational Technology Research and Development, 60(2), 341–359. https://doi.org/10.1007/s11423-011-9230-5.

    Article  Google Scholar 

  • Jonassen, D. H., & Hernandez-Serrano, J. (2002). Case-based reasoning and instructional design: Using stories to support problem solving. Educational Technology Research and Development, 50(2), 65–77.

    Article  Google Scholar 

  • Kim, E., & Rhee, M. (2017). How airlines learn from airline accidents: An empirical study of how attributed errors and performance feedback affect learning from failure. Journal of Air Transport Management, 58, 135–143.

    Article  Google Scholar 

  • Kohn, L. T., Corrigan, J. M., & Donaldson, M. S. (2000). To err is human: Building a safer health system (p. 2000). Washington, DC: National Academy Press.

    Google Scholar 

  • Kolodner, J. L. (1997). Educational implications of Analogy—A view from case based reasoning. American Psychologist, 52(1), 57–66.

    Article  Google Scholar 

  • Kolodner, J. L., Owensby, J. N., & Guzdial, M. (2004). Case-based learning aids. In D. H. Jonassen (Ed.), Handbook of research for educational communications and technology (2nd ed., pp. 829–862). Mahwah, NJ: Lawrence Erlbaum Associates, Inc.

    Google Scholar 

  • Kopp, V., Stark, R., & Fischer, M. R. (2008). Fostering diagnostic knowledge through computer-supported, case-based worked examples: Effects of erroneous examples and feedback. Medical Education, 42(8), 823–829. https://doi.org/10.1111/j.1365-2923.2008.03122.x.

    Article  Google Scholar 

  • Kopp, V., Stark, R., Kuhne-Eversmann, L., & Fischer, M. R. (2009). Do worked examples foster medical students’ diagnostic knowledge of hyperthyroidism? Medical Education, 43, 1210–1217.

    Article  Google Scholar 

  • Kuhn, T. S. (1957). The Copernican revolution: Planetary astronomy in the development of western thought (1st ed.). Cambridge, MA: Harvard University Press.

    Google Scholar 

  • Labib, A., & Harris, M. J. (2015). Learning how to learn from failures: The Fukushima nuclear disaster. Engineering Failure Analysis, 47, 117–128.

    Article  Google Scholar 

  • Lin-Siegler, X., Ahn, J. N., Chen, J., Fang, F. F. A., & Luna-Lucero, M. (2016). Even Einstein struggled: Effects of learning about great scientists’ struggles on high school students’ motivation to learn science. Journal of Educational Psychology, 108(3), 314–328.

    Article  Google Scholar 

  • Martinez, W., & Lo, B. (2008). Medical students’ experiences with medical errors: An analysis of medical student essays. Medical Education, 42(7), 733–741.

    Article  Google Scholar 

  • McLaren, B. M., Adams, D. M., & Mayer, R. E. (2015). Delayed learning effects with erroneous examples: A study of learning decimals with a web-based tutor. International Journal of Artificial Intelligence in Education, 25(4), 520–542.

    Article  Google Scholar 

  • Mezirow, J. (1990). Fostering critical reflection in adulthood: A guide to transformative and emancipator learning (1st ed.). San Francisco: Jossey-Bass Publishers.

    Google Scholar 

  • Ohlsson, S. (1996). Learning from performance errors. Psychological Review, 103(2), 241–262.

    Article  Google Scholar 

  • Palter, V. N., Orzech, N., Reznick, R. K., & Grantcharov, T. P. (2013). Validation of a structured training and assessment curriculum for technical skill acquisition in minimally invasive surgery. Annals of Surgery, 257(2), 224–230.

    Article  Google Scholar 

  • Pearn, M., Mulrooney, C., & Payne, T. (1998). Ending the blame culture. Brookfield, VT: Gower.

    Google Scholar 

  • Ragin, C. C., & Becker, H. S. (1992). What is a case? Exploring the foundations of social inquiry (1st ed.). Cambridge: Cambridge University Press.

    Google Scholar 

  • Ramaekers, S. P. J., Beukelen, P. V., Kremer, W. D. J., Keulen, H. V., & Pilot, A. (2011). An instructional model for training competence in solving clinical problems. Journal of Veterinary Medical Education, 38(4), 360–372. https://doi.org/10.3138/jvme.38.4.360.

    Article  Google Scholar 

  • Rasmussen, J. (1983). Skills, rules, and knowledge; Signals, signs, and symbols, and other distinctions in human performance models. IEEE Transactions on Systems, Man, and Cybernetics, 13(3), 257–266.

    Article  Google Scholar 

  • Reason, J. T. (1990). Human error (1st ed.). New York: Cambridge University Press.

    Book  Google Scholar 

  • Reason, J. T. (1995). Understanding adverse events: Human factors. Quality in Health Care, 4, 80–89.

    Article  Google Scholar 

  • Rebitch, C. B., Fleming, V. H., Palmer, R., Rong, H., & Choi, I. (in press). Evaluation of video-enhanced case-based activities guided by the Pharmacists’ Patient Care Process (PPCP) in a second-year PharmD course. The American Journal of Pharmaceutical Education.

  • Renkl, A. (2014). Toward an instructionally oriented theory of example-based learning. Cognitive Science, 38(1), 1–37. https://doi.org/10.1111/cogs.12086.

    Article  Google Scholar 

  • Renkl, A., & Atkinson, R. K. (2010). Learning from worked-out examples and problem solving. In J. L. Plass, R. Moreno, & R. Brunken (Eds.), Cognitive load theory (pp. 91–108). Cambridge: Cambridge University Press.

    Chapter  Google Scholar 

  • Rohbanfard, H., & Proteau, L. (2011). Learning through observation: A combination of expert and novice models favors learning. Experimental Brain Research, 215, 183–197.

    Article  Google Scholar 

  • Sandage, S. A. (2005). Born losers: A history of failure in America. Cambridge, MA: Harvard University Press.

    Book  Google Scholar 

  • Schank, R. (1999). Dynamic memory revisited (2nd ed.). Cambridge: Cambridge University Press.

    Book  Google Scholar 

  • Schmidt, R. A., & Bjork, R. A. (1992). New conceptualizations of practice: Common principles in three paradigms suggest new concepts for training. Psychological Science, 3, 207–217. https://doi.org/10.1111/j.1467-9280.1992.tb00029.x.

    Article  Google Scholar 

  • Schmitz, F. M., Schnabel, K. P., Stricker, D., Fischer, M. R., & Guttormsen, S. (2017). Learning communication from erroneous video-based examples: A double-blind randomized controlled trial. Patient Education and Counseling, 100, 120–1212.

    Article  Google Scholar 

  • Schön, D. A. (1983). The reflective practitioner: How professionals think in action. New York: Basic Books.

    Google Scholar 

  • Schön, D. A. (1987). Educating the reflective practitioner: Toward a new design for teaching and learning in the professions (1st ed.). San Francisco: Jossey-Bass.

    Google Scholar 

  • Siegler, R. S., & Chen, Z. (2008). Differentiation and integration: Guiding principles for analyzing cognitive change. Developmental Science, 11, 433–448.

    Article  Google Scholar 

  • Sitkin, S. B. (1992). Learning through failures: The strategy of small losses. Research in Organizational Behavior, 14, 231–266.

    Google Scholar 

  • Skinner, B. F. (1968). The technology of teaching. New York: Appleton-Century-Crofts.

    Google Scholar 

  • Spiro, R. J., Coulson, R. L., Feltovich, P. J., & Anderson, D. K. (1988). Cognitive flexibility theory: Advanced knowledge acquisition and ill-structured domains. Tech. Rep. No. 441. Champaign, IL: University of Illinois at Urbana Champaign.

  • Stark, R., Kopp, V., & Fischer, M. R. (2011). Case-based learning with worked examples in complex domains: Two experimental studies in undergraduate medical education. Learning and Instruction, 21(1), 22–33. https://doi.org/10.1016/j.learninstruc.2009.10.001.

    Article  Google Scholar 

  • Strohfeldt, K., & Khutoryanskaya, O. (2015). Using problem-based learning in a chemistry practical class for pharmacy students and engaging them with feedback. American Journal of Pharmaceutical Education, 79(9), 1–11.

    Article  Google Scholar 

  • Swaminath, G., & Raguram, R. (2010). Medical errors—I: The problem. Indian Journal of Psychiatry, 52(2), 110–112.

    Article  Google Scholar 

  • Swaminath, G., & Raguram, R. (2011). Medical errors II, the aftermath: Mea culpa! Indian Journal of Psychiatry, 53, 9–12.

    Article  Google Scholar 

  • Sweller, J., Ayres, P., & Kalyuga, S. (2011). Cognitive load theory. New York: Springer.

    Book  Google Scholar 

  • Sweller, J., & Cooper, G. A. (1985). The use of worked examples as a substitute for problem solving in learning algebra. Cognition and Instruction, 2, 59–89.

    Article  Google Scholar 

  • Sweller, J., van Merrienboer, J. J. G., & Pass, F. G. W. C. (1998). Cognitive architecture and instructional design. Educational Psychology Review, 10, 251–296.

    Article  Google Scholar 

  • Tawfik, A., & Jonassen, D. H. (2013). The effects of successful versus failed cases on argumentation while solving decision-making problems. Educational Technology Research and Development, 61(3), 385–406. https://doi.org/10.1007/s11423-013-9294-511423-013-9294-5.

    Article  Google Scholar 

  • Tawfik, A., Rong, H., & Choi, I. (2015). Failing to learn: Towards a unified design approach for failure-based learning. Educational Technology Research and Development, 63(6), 975–994. https://doi.org/10.1007/s11423-015-9399-0.

    Article  Google Scholar 

  • Tsovaltzi, D., Melis, E., McLaren, B. M., Meyer, A.-K., Dietrich, M., & Goguadze, G. (2010). Learning from erroneous examples: When and how do students benefit from them? In Proceedings of the European conference on technology enhanced learning. LNCS (Vol. 6383). Heidelberg: Springer.

  • Tulis, M., Steuer, G., & Dresel, M. (2016). Learning from errors: A model of individual processes. Frontline Learning Research, 4, 12–26.

    Article  Google Scholar 

  • Van Gog, T. (2015). Learning from erroneous examples in medical education. Medical Education, 49, 138–146.

    Article  Google Scholar 

  • van Gog, T., Paas, F., & Van Merriënboer, J. J. G. (2004). Process-oriented worked examples: Improving transfer performance through enhanced understanding. Instructional Science, 32, 83–98. https://doi.org/10.1023/b:truc.0000021810.70784.b0.

    Article  Google Scholar 

  • Van Merriënboer, J. J. G., Clark, R. E., & De Croock, M. B. M. (2002). Blueprints for complex learning: The 4C/ID-model. Educational Technology Research and Development, 50(2), 39–64.

    Article  Google Scholar 

  • VanLehn, K. (1996). Cognitive skill acquisition. Annual Review of Psychology, 47, 513–539.

    Article  Google Scholar 

  • VanLehn, K., Siler, S., Murray, C., Yamauchi, T., & Baggett, W. B. (2003). Why do only some events cause learning during human tutoring? Cognition and Instruction, 21(3), 209–249.

    Article  Google Scholar 

  • Vincent, C., Taylor-Adams, S., & Stanhope, N. (1998). Framework for analysing risk and safety in clinical medicine. BMJ, 316(11), 1154–1157.

    Article  Google Scholar 

  • Vygotsky, L. S. (1979). Consciousness as a problem in the psychology of behavior. Soviet Psychology, 17(4), 3–35.

    Article  Google Scholar 

  • Ward, M., & Sweller, J. (1990). Structuring effective worked examples. Cognition and Instruction, 7, 1–39.

    Article  Google Scholar 

  • Weiner, B. (2000). Intrapersonal and interpersonal theories of motivation from an attributional perspective. Educational Psychology Review, 12, 1–14.

    Article  Google Scholar 

  • Weiss, G. G. (2006). Medical errors. Should you apologize? Medical Education, 83(8), 50–54.

    Google Scholar 

  • Williams, S. M. (1992). Putting case-based instruction into context: Examples from legal and medical education. The Journal of Learning Sciences, 2(4), 367–427.

    Article  Google Scholar 

  • Wu, A. W., & Steckelberg, R. C. (2012). Medical error, incident investigation and the second victim: Doing better but feeling worse? BMJ Quality and Safety, 21(4), 267–270.

    Article  Google Scholar 

  • Zhao, B. (2011). Learning from errors: The role of context, emotion, and personality. Journal of Organizational Behavior, 32, 435–463.

    Article  Google Scholar 

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  1. UMass Medical School, 55 North Lake Avenue, Worcester, MA, USA

    Hui Rong

  2. The University of Georgia, 850 College Station Road, Athens, GA, 30602, USA

    Ikseon Choi

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Rong, H., Choi, I. Integrating failure in case-based learning: a conceptual framework for failure classification and its instructional implications. Education Tech Research Dev 67, 617–637 (2019). https://doi.org/10.1007/s11423-018-9629-3

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