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Failing to learn: towards a unified design approach for failure-based learning

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Abstract

To date, many instructional systems are designed to support learners as they progress through a problem-solving task. Often these systems are designed in accordance with instructional design models that progress the learner efficiently through the problem-solving process. However, theories from various fields have discussed failure as a strategic way to engender learning. Although researchers suggest that failure may be an element of problem-solving, no models have discussed how to employ failure strategically within instructional design. Given this gap, we first present failure-based research from various theoretical frameworks. Based on the research, we proffer failure-based principles for learning systems design. Implications and future research are also discussed.

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References

  • Argote, L., & Miron-Spektor, E. (2011). Organizational learning: From experience to knowledge. Organization Science, 22(5), 1123–1137.

    Article  Google Scholar 

  • Bar-Anan, Y., Wilson, T. D., & Gilbert, D. T. (2009). The feeling of uncertainty intensifies affective reactions. Emotion, 9(1), 123–127. doi:10.1037/a0014607.

    Article  Google Scholar 

  • Bauer, J., & Mulder, R. (2007). Modelling learning from errors in daily work. Learning in Health and Social Care, 6(3), 121–133.

    Article  Google Scholar 

  • Blumberg, F. C., Rosenthal, S. F., & Randall, J. D. (2008). Impasse-driven learning in the context of video games. Computers in Human Behavior, 24(4), 1530–1541. doi:10.1016/j.chb.2007.05.010.

    Article  Google Scholar 

  • Boud, D., Keogh, R., & Walker, D. (2013). Reflection: Turning experience into learning. New York: Routledge.

    Google Scholar 

  • Brown, J. S., & VanLehn, K. (1980). Repair theory: A generative theory of bugs in procedural skills. Cognitive Science, 4(4), 379–426. doi:10.1207/s15516709cog0404_3.

    Article  Google Scholar 

  • Casale, M. B., Roeder, J. L., & Ashby, F. G. (2012). Analogical transfer in perceptual categorization. Memory & Cognition, 40(3), 434–449.

    Article  Google Scholar 

  • Cope, J. (2011). Entrepreneurial learning from failure: An interpretative phenomenological analysis. Journal of Business Venturing, 26(6), 604–623. doi:10.1016/j.jbusvent.2010.06.002.

    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. doi:10.1016/j.learninstruc.2012.05.003.

    Article  Google Scholar 

  • De Jong, T., & Lazonder, A. (2014). The guided discovery learning principle in multimedia learning. In R. E. Mayer (Ed.), The Cambridge handbook of multimedia learning (2nd ed., pp. 370–390). Cambridge University Press.

  • Dugas, M. J., Hedayati, M., Karavidas, A., Buhr, K., Francis, K., & Phillips, N. A. (2005). Intolerance of uncertainty and information processing: Evidence of biased recall and interpretations. Cognitive Therapy and Research, 29(1), 57–70. doi:10.1007/s10608-005-1648-9.

    Article  Google Scholar 

  • Ellis, S. (2011). Learning from errors: The role of after-event reviews. In J. Bauer & C. Harteis (Eds.), Human fallibility: The ambiguity of errors for work and learning (pp. 215–314). Dordrecht: Springer.

    Google Scholar 

  • Ellis, S., Mendel, R., & Davidi, I. (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. (2005). Teacher pedagogical beliefs: The final frontier in our quest for technology integration? Educational Technology Research and Development, 53(4), 25–39.

    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. doi:10.1007/s12186-008-9006-1.

    Article  Google Scholar 

  • Gartmeier, M., Bauer, J., Gruber, H., & Heid, H. (2010). Workplace errors and negative knowledge in elder care nursing. Human Resource Development International, 13(1), 5–25.

    Article  Google Scholar 

  • Ge, X., & Land, S. (2003). Scaffolding students’ problem-solving processes in an ill-structured task using question prompts and peer interactions. Educational Technology Research and Development, 51(1), 21–38.

    Article  Google Scholar 

  • Henry, H., Tawfik, A. A., Jonassen, D. H., Winholtz, R., & Khanna, S. (2012). “I know this is supposed to be more like the real world, but…”: Student perceptions of a PBL implementation in an undergraduate materials science course. Interdisciplinary Journal of Problem-Based Learning. doi:10.7771/1541-5015.1312.

    Google Scholar 

  • Herrington, J., Reeves, T. C., & Oliver, R. (2014). Authentic learning environments. In J. M. Spector, M. D. Merrill, J. Elen, & M. J. Bishop (Eds.), Handbook of research on educational communications and technology (4th ed., pp. 453–464). New York, NY: Springer.

    Google Scholar 

  • Hmelo-Silver, C. E., & Eberbach, C. (2012).Learning theories and problem-based learning.In Bridges, S., McGrath, C., & Whitehill, T. L. (Eds.), Problem-based learning in clinical education (pp. 3–17). Springer Netherlands. Retrieved from http://link.springer.com/chapter/10.1007/978-94-007-2515-7_1.

  • Hoeve, A., & Nieuwenhuis, L. F. (2006). Learning routines in innovation processes. Journal of Workplace Learning, 18(3), 171–185.

    Article  Google Scholar 

  • Holyoak, K., & Koh, K. (1987). Surface and structural similarity in analogical transfer. Memory & Cognition, 15(4), 332–340.

    Article  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(5), 687–710. doi:10.1007/s11423-011-9202-9.

    Article  Google Scholar 

  • Hung, W. (2011). Theory to reality: A few issues in implementing problem-based learning. Educational Technology Research & Development, 59(4), 529–552.

    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. (2011). Supporting problem solving in PBL. Interdisciplinary Journal of Problem-Based Learning. doi:10.7771/1541-5015.1256.

    Google Scholar 

  • Jonassen, D. H., & Hung, W. (2008). All problems are not equal: Implications for problem-based learning. Interdisciplinary Journal of Problem-Based Learning, 2(2), 6–28.

    Article  Google Scholar 

  • Jones, R. M., & Vanlehn, K. (1994). Acquisition of children’s addition strategies: A model of impasse-free, knowledge-level learning. Machine Learning, 16(1–2), 11–36. doi:10.1007/BF00993172.

    Google Scholar 

  • Kapur, M. (2008). Productive failure. Cognition and Instruction, 38(6), 523–550.

    Google Scholar 

  • Kapur, M. (2010). Productive failure in mathematical problem solving. Instructional Science, 26(3), 379–424.

    Google Scholar 

  • Kapur, M. (2011). A further study of productive failure in mathematical problem solving: Unpacking the design components. Instructional Science, 39(4), 561–579. doi:10.1007/s11251-010-9144-3.

    Article  Google Scholar 

  • Kapur, M. (2012). Productive failure in learning the concept of variance. Instructional Science, 40(4), 651–672. doi:10.1007/s11251-012-9209-6.

    Article  Google Scholar 

  • Kolb, D. A. (2014). Experiential learning: Experience as the source of learning and development (2nd ed.). Indianapolis: Pearson FT Press.

    Google Scholar 

  • Kolodner, J. L., Owensby, J., & Guzdial, M. (2004). Case-based learning aids. In D. H. Jonassen (Ed.), Handbook of research on educational communications and technology: A project of the Association for Educational Communications and Technology (2nd ed., pp. 829–861). Mahwah: LEA.

    Google Scholar 

  • Lannin, J., Barker, D., & Townsend, B. (2007). How students view the general nature of their errors. Educational Studies in Mathematics, 66(1), 43–59. doi:10.1007/s10649-006-9067-8.

    Article  Google Scholar 

  • Lazonder, A. (2014). Inquiry learning. In J. M. Spector, M. D. Merrill, J. Elen, & M. J. Bishop (Eds.), Handbook of research on educational communications and technology (4th ed., pp. 453–464). New York, NY: Springer.

    Chapter  Google Scholar 

  • Lorch, R. F, Jr, Lorch, E. P., Calderhead, W., Dunlap, E., Hodell, E., & Freer, B. (2010). Learning the control of variables strategy in higher and lower achieving classrooms: Contributions of explicit instruction and experimentation. Journal of Educational Psychology, 102(1), 90–101.

    Article  Google Scholar 

  • Mathan, S., & Koedinger, K. (2005). Fostering the intelligent novice: Learning from errors with metacognitive tutoring. Educational Psychologist, 40(4), 257–265.

    Article  Google Scholar 

  • Parviainen, J., & Eriksson, M. (2006). Negative knowledge, expertise and organisations. International Journal of Management Concepts and Philosophy, 2(2), 140–153.

    Article  Google Scholar 

  • Piaget, J. (1952). The origins of intelligence in children. New York: W W Norton & Co.

    Book  Google Scholar 

  • Piaget, J. (1977). The development of thought: equilibration of cognitive structures (Vol. viii). Oxford: Viking.

    Google Scholar 

  • Piaget, J., Brown, T., & Thampy, K. J. (1985). The equilibration of cognitive structures: the central problem of intellectual development (Vol. 985). Chicago: University of Chicago Press.

    Google Scholar 

  • Reiser, B. (2004). Scaffolding complex learning: the mechanisms of structuring and problematizing student work. Journal of the Learning Sciences, 13(3), 273–304.

    Article  Google Scholar 

  • Renner, J. W., Stafford, D. G., Lawson, A. E., McKinnon, J. W., Friot, F. E., & Kellogg, D. H. (1976). Research, teaching, and learning with the Piaget model. Norman: University of Oklahoma Press.

    Google Scholar 

  • Schank, R. (1982). Dynamic memory. Cambridge: Cambridge University Press.

    Google Scholar 

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

    Book  Google Scholar 

  • Schmidt, H. G., & Rikers, R. M. J. P. (2007). How expertise develops in medicine: knowledge encapsulation and illness script formation. Medical Education, 41(12), 1133–1139. doi:10.1111/j.1365-2923.2007.02915.x.

    Google Scholar 

  • Schon, D. A. (1984). The reflective practitioner: How professionals think in action (1st ed.). New York: Basic Books.

    Google Scholar 

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

    Google Scholar 

  • Spiro, R., Coulson, R. L., Feltovich, P., & Anderson, D. K. (1998). Cognitive flexibility theory: advanced knowledge acquisition in ill-structured domains.

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

    Article  Google Scholar 

  • Tudge, J. (1993). Vygotsky, Piaget, and Bandura: Perspectives on the relations between the social world and cognitive development. Human Development, 36(2), 61–81.

    Article  Google Scholar 

  • VanLehn, K. (1988). Toward a theory of impasse-driven learning. In Mandl, D. H. & Lesgold, D. A. (Eds.) Learning Issues for Intelligent Tutoring Systems (pp. 19–41). Springer US. Retrieved from http://link.springer.com/chapter/10.1007/978-1-4684-6350-7_2.

  • 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. doi:10.1207/S1532690XCI2103_01.

    Article  Google Scholar 

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Tawfik, A.A., Rong, H. & Choi, I. Failing to learn: towards a unified design approach for failure-based learning. Education Tech Research Dev 63, 975–994 (2015). https://doi.org/10.1007/s11423-015-9399-0

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