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Cognitive Task Analysis for Expert-Based Instruction in Healthcare

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Handbook of Research on Educational Communications and Technology

Abstract

This chapter presents an overview of the rationale and evidence for the use of cognitive task analysis (CTA) in healthcare including the following: It presents a brief history and definition of CTA, the reason it is being adopted for healthcare education, evidence for its learning benefits when used in evidence-based instructional design and medical simulators, an example of how one of the evidence-based CTA methods was implemented in healthcare, and suggestions for future research. The point is made that when evidence-based CTA methods are used, learning from CTA-based healthcare instruction increases an average of 45 % when compared with current task analysis methods.

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Notes

  1. 1.

    For a more detailed history of CTA, consult Hoffman and Militello (2009).

References

  • Besnard, D. (2000). Expert error: The case of trouble-shooting in electronics. Lecture notes in computer science, 2000 (pp. 74–85). Rotterdam: Springer.

    Google Scholar 

  • Campbell, J., Tiraplle, L., Yates, K., Clark, R. E., Inaba, K., Green, D., et al. (2011). The effectiveness of cognitive task analysis informed curriculum to increase self-efficacy and improve performance for an open cricothyrotomy. Journal of Surgical Education, 68(5), 403–407.

    Article  Google Scholar 

  • Cen, H., Koedinger, K. R., & Junker, B. (2007). Is over practice necessary? Improving learning efficiency with educational data mining. In R. Luckin, K. R. Koedinger, & J. Greer (Eds.), Proceedings of the 2007 conference on artificial intelligence in education: Building technology rich learning contexts that work (pp. 511–518). Amsterdam: Ios Press.

    Google Scholar 

  • Chao, C.-J., & Salvende, G. (1994). Percentage of procedural knowledge acquired as a function of the number of experts from whom knowledge is acquired for diagnosis, debugging and interpretation tasks. International Journal of Human Computer Interaction, 6(3), 221–233.

    Article  Google Scholar 

  • Clark, R. E. (2004). Design document for a guided experiential learning course. Final report on TRADOC contract DAAD 19-99-D-0046-0004. Los Angeles, CA: Institute for Creative Technology and the Rossier School of Education. Retrieved from http://www.cogtech.usc.edu/publications/clark_gel.pdf.

  • Clark, R. E. (2006). Not knowing what we don’t know: Reframing the importance of automated knowledge for educational research. In G. Clarebout & J. Elen (Eds.), Avoiding simplicity, confronting complexity: Advances in studying and designing powerful learning environments (pp. 3–15). Rotterdam: Sense Publishers.

    Google Scholar 

  • Clark, R. E., & Elen, J. (2006). When less is more: Research and theory insights about instruction for complex learning. In J. Elen & R. E. Clark (Eds.), Handling complexity in learning environments: Research and theory (pp. 283–297). Oxford: Elsevier Science Limited.

    Google Scholar 

  • *Clark, R. E., & Estes, F. (1996) Cognitive task analysis. International Journal of Educational Research, 25(5), 403–417.

    Google Scholar 

  • *Clark, R. E., Feldon, D., vanMerrienboer, J., Yates, K., & Early, S. (2008). Cognitive task analysis. In J. M. Spector, M. D. Merrill, J. J. G. van Merrienboër, & M. P. Driscoll (Eds.), Handbook of research on educational communications and technology (3rd ed., pp. 577–593). Mahwah, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  • Clark, R. E., Yates, K., Early, S., & Moulton, K. (2010). An analysis of the failure of electronic media and discovery-based learning: Evidence for the performance benefits of guided training methods. In K. H. Silber & R. Foshay (Eds.), Handbook of training and improving workplace performance (Instructional design and training delivery, Vol. I, pp. 263–297). New York, NY: John Wiley and Sons.

    Google Scholar 

  • Crandall, B., & Gamblian, V. (1991). Guide to early sepsis assessment in the NICU. Fairborn, OH: Klein Associates.

    Google Scholar 

  • Crandall, B., & Gretchell-Leiter, K. (1993). Critical decision method: A technique for eliciting concrete assessment indicators from the “intuition” of NICU nurses. Advances in Nursing Science, 16(1), 42–51.

    Google Scholar 

  • Ericsson, K. A. (2004). Deliberate practice and the acquisition and maintenance of expert performance in medicine and related domains. Academic Medicine, 79(10), S70–S81.

    Article  Google Scholar 

  • Ericsson, K. A., & Charness, N. (1994). Expert performance: Its structure and acquisition. American Psychologist, 49(8), 725–747.

    Article  Google Scholar 

  • Feldon, D. F. (2004). Inaccuracies in expert self-report: Errors in the description of strategies for designing psychology experiments. Unpublished doctoral dissertation presented. Faculty of the Rossier School of Education, University of Southern California, Los Angeles.

    Google Scholar 

  • Gilbreth, F. B., & Gilbreth, L. M. (1919). Fatigue study. New York, NY: Macmillan.

    Google Scholar 

  • Gladwell, M. (2005). Blink: The power of thinking without thinking. New York, NY: Little Brown and Company.

    Google Scholar 

  • Glaser, R., Lesgold, A., Lajoie, S., Eastman, R., Greenberg, L., Logan, D., et al., (1985). Cognitive task analysis to enhance technical skills training and assessment. (Final Report to the Air Force Human Resources Laboratory on Contract No. F41689-8v3-C-0029.) Pittsburgh, PA: Learning Research and Development Center, University of Pittsburgh.

    Google Scholar 

  • Halfer, D., & Graf, E. (2008). Graduate nurse perceptions of the work experience. Nursing Economics, 24(3), 150–155.

    Google Scholar 

  • Hall, E. M., Gott, S., & Pokorny, R. A. (1995). A procedural guide to cognitive task analysis: The PARI methodology. Brooks Air Force Base, TX: Manpower and Personnel Division, U.S. Air Force.

    Google Scholar 

  • *Hoffman, R. R., & Militello, L. G. (2009). Perspectives on cognitive task analysis: Historical origins and modern communities of practice. New York, NY: Psychology Press.

    Google Scholar 

  • Hunt, E., & Joslyn, S. (2000). A functional task analysis of time-pressured decision-making. In J. M. Schraagen, S. F. Chipman, & V. L. Shalin (Eds.), Cognitive task analysis (pp. 119–132). Mahwah, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  • Klein, G. A., Calderwood, R., & Macgregor, D. (1989). Critical decision method for eliciting knowledge. IEEE Transactions on Systems, Man, and Cybernetics, 19(3), 462–472.

    Article  Google Scholar 

  • Lee, R. L. (2004). The impact of cognitive task analysis on performance: A meta-analysis of comparative studies. Unpublished doctoral dissertation. University of Southern California, Los Angeles.

    Google Scholar 

  • Maupin, F. G. (2004). Comparing cognitive task analysis to behavior task analysis in training first year interns to place central venous catheters. Unpublished doctoral dissertation. Rossier School of Education, University of Southern California, Los Angeles.

    Google Scholar 

  • Merrill, M. D. (2002a). First principles of instruction. Educational Technology Research and Development, 50(3), 43–59.

    Article  Google Scholar 

  • Merrill, M. D. (2002b). A pebble-in-the-pond model for instructional design. Performance Improvement, 41(7), 39–44.

    Article  Google Scholar 

  • Merrill, M. D. (2006). Hypothesized performance on complex tasks as a function of scaled instructional strategies. In J. Elen & R. E. Clark (Eds.), Handling complexity in learning environments: Research and theory (pp. 265–281). Oxford: Elsevier Science Limited.

    Google Scholar 

  • Mislevy, R. J., Breyer, F. J., Almond, R. G., & Johnson, L. (1998). A cognitive task analysis with implications for designing simulation-based performance assessment. National Center for Research on Evaluation, Standards and Student Testing (CRESST). Los Angeles: University of California, Los Angeles.

    Google Scholar 

  • Schneider, W., & Shiffrin, R. M. (1977). Controlled and automatic human information processing: 1. Detection, search, and attention. Psychological Review, 84, 1–66.

    Article  Google Scholar 

  • *Schraagen, J. M., Chipman, S. F., & Shalin, V, L. (2000). Cognitive task analysis. Mahwah, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  • Tofel-Grehl, C., & Feldon, D. F. (2013). Cognitive task analysis-based training: A meta-analysis of studies. Journal of Cognitive Engineering and Decision Making, 7(2).

    Google Scholar 

  • *Velmahos, G. C., Toutouzas, K. G., Sillin, L. F., Chan, L., Clark, R. E., & Theodorou, D., et al. (2004). Cognitive task analysis for teaching technical skills in an inanimate surgical skills laboratory. The American Journal of Surgery, 18, 114–119.

    Google Scholar 

  • Wegner, D. M. (2002). The illusion of conscious will. Cambridge, MA: MIT Press.

    Google Scholar 

  • Wei, J., & Salvendy, G. (2004). The cognitive task analysis methods for job and task design: Review and reappraisal. Behaviour and Information Technology, 23(4), 273–299.

    Article  Google Scholar 

  • Wheatley, T., & Wegner, D. M. (2001). Automaticity in action. In N. J. Smelser & P. B. Baltes (Eds.), International encyclopedia of the social and behavioral sciences (pp. 991–993). London: Pergamon.

    Chapter  Google Scholar 

  • Workforce Connections Inc. (2011) Business Survey Outcomes. Retrieved from http://www.workforceconnections.org/Business%20Survey%20Outcome%20REPORT%20Final.pdf

  • Yates, K. A. & Feldon, D. F. (2007). Towards a Taxonomy of Cognitive Task Analysis Methods: A search for cognition and task analysis interactions. Unpublished doctoral dissertation. Rossier School of Education, University of Southern California, Los Angeles.

    Google Scholar 

  • *Yates, K. A., & Feldon, D. F. (2008, April). Towards a taxonomy of cognitive task analysis methods for instructional design: Interactions with cognition. Paper presented at the Annual Meeting of the American Educational Research Association, New York City, New York.

    Google Scholar 

  • Yates, K. A., & Feldon, D. F. (2011). Advancing the practice of cognitive task analysis: A call for taxonomic research. Theoretical Issues in Ergonomics Science, 12(6), 472–495.

    Google Scholar 

  • Yates, K. A., Sullivan, M., & Clark, R. E. (2012). Integrated studies in the use of cognitive task analysis to capture surgical expertise for central venous catheter placement and open cricothyrotomy. American Journal of Surgery, 1–5.

    Google Scholar 

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Acknowledgements

The author wishes to acknowledge the many ­colleagues who have contributed to the CTA research reported in this chapter including Drs Fredric Maupin, Kenneth Yates, Maura Sullivan, and David Feldon. The project or the effort described here has been partially sponsored by the US Army Research, Development, and Engineering Command (RDECOM). Statements and opinions expressed do not necessarily reflect the position or the policy of the United States Government, and no official endorsement should be inferred.

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Correspondence to Richard Clark .

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Clark, R. (2014). Cognitive Task Analysis for Expert-Based Instruction in Healthcare. In: Spector, J., Merrill, M., Elen, J., Bishop, M. (eds) Handbook of Research on Educational Communications and Technology. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-3185-5_42

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