Skip to main content

Advertisement

SpringerLink
Log in

Investigating the Role of Cognitive Feedback in Practice-Oriented Learning for Clinical Diagnostics

  • Original Paper
  • Published:
Vocations and Learning Aims and scope Submit manuscript

Abstract

Reflection plays an important role in medical students’ ability to develop diagnostic competence through practice with clinical cases. However, it is not easy for students to develop expert-like performance through self-reflection alone; conversely, seeking feedback from experts constantly in practice is impractical. This study investigates the design and effects of computer-based cognitive feedback in practice-oriented learning in an online system. The system allows learners to work with simulated cases and self-review and reflect on their diagnostic processes that the system captures visually. Moreover, the system provides learners with feedback about the gap between their performance and expert performance on a set of key components of the diagnostic task, i.e., selecting clinical examinations, making intermediate judgements, and reaching diagnostic conclusions. The findings show that cognitive feedback on task performance can reduce learners’ anxiety and frustration while working with complex tasks. Moreover, by providing feedback on learners’ performance on a set of key components of the task, the proposed approach has shown promising effects on improving learners’ diagnostic performance. Compared with its effects on learners’ diagnostic conclusions, the approach is more effective in enhancing learners’ performance when selecting clinical examinations and making intermediate judgements, both of which may improve learners’ understanding of the mechanism underlying the diagnostic process.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

References

  • Ajjawi, R., & Boud, D. (2018). Examining the nature and effects of feedback dialogue. Assessment & Evaluation in Higher Education, 43(7), 1106–1119.

    Article  Google Scholar 

  • Archer, J. C. (2010). State of the science in health professional education: Effective feedback. Medical Education, 44(1), 101–108.

    Article  Google Scholar 

  • Azevedo, R., & Bernard, R. M. (1995). A meta-analysis of the effects of feedback in computer-based instruction. Journal of Educational Computing Research, 13, 111–127.

    Article  Google Scholar 

  • Banning, M. (2008). The think aloud approach as an educational tool to develop and assess clinical reasoning in undergraduate students. Nurse Education Today, 28(1), 8–14.

    Article  Google Scholar 

  • Barrows, H. S. (1996). Problem-based learning in medicine and beyond: A brief overview. New Directions for Teaching and Learning, 68, 3–12.

    Article  Google Scholar 

  • Bing-You, R., Hayes, V., Varaklis, K., Trowbridge, R., Kemp, H., & McKelvy, D. (2017). Feedback for learners in medical education: What is known? A scoping review. Academic Medicine, 92(9), 1346–1354.

    Article  Google Scholar 

  • Bok, H. G. J., Teunissen, P. W., Spruijt, A., Fokkema, J. P. I., van Beukelen, P., Jaarsma, D. A. D. C., & van der Vleuten, C. P. M. (2013). Clarifying students’ feedback-seeking behaviour in clinical clerkships. Medical Education, 47(3), 282–291.

    Article  Google Scholar 

  • Boldrini, E., & Cattaneo, A. (2014). Scaffolding collaborative reflective writing in a VET curriculum. Vocations and Learning, 7, 145–165.

    Article  Google Scholar 

  • Bordage, G. (1999). Why did I miss the diagnosis? Some cognitive explanations and educational implications. Academic Medicine, 74(10), S138–S143.

    Article  Google Scholar 

  • Boud, D., & Molloy, E. (2013). Rethinking models of feedback for learning: The challenge of design. Assessment & Evaluation in Higher Education, 38(6), 698–712.

    Article  Google Scholar 

  • Boud, B., & Walker, D. (1990). Making the most of experience. Studies in Continuing Education, 12(2), 61–80.

    Article  Google Scholar 

  • Branch, W. T., & Paranjape, A. (2002). Feedback and reflection: Teaching methods for clinical settings. Academic Medicine, 77(12), 1185–1188.

    Article  Google Scholar 

  • Butler, D. L., & Winne, P. H. (1995). Feedback and self-regulated learning: A theoretical synthesis. Review of Educational Research, 65, 245–281.

    Article  Google Scholar 

  • Carless, D., & Boud, D. (2018). The development of student feedback literacy: Enabling uptake of feedback. Assessment & Evaluation in Higher Education, 43(8), 1315–1325.

    Article  Google Scholar 

  • Chiu, D. K. W., Lin, D. T. T., Kafeza, E., Wang, M., Hu, H., Hu, H., & Zhuang, Y. (2010). Alert-based disaster notification and resource allocation. Information Systems Frontiers, 12(1), 29–47.

  • Colvin, G. (2008). Talent is overrated: What really separates world-class performers from everybody else. New York, NY: Portfolio.

    Google Scholar 

  • Cook, D. A., & Triola, M. M. (2009). Virtual patients: A critical literature review and proposed next steps. Medical Education, 43(4), 303–311.

    Article  Google Scholar 

  • Corbalan, G., Kester, L., & Van Merriënboer, J. J. G. (2009). Dynamic task selection: Effects of feedback and learner control on efficiency and motivation. Learning and Instruction, 19(6), 455–465.

    Article  Google Scholar 

  • Delany, C., & Golding, C. (2014). Teaching clinical reasoning by making thinking visible: An action research project with allied health educators. BMC Medical Education, 14, 20.

    Article  Google Scholar 

  • Dewey, J. (1938). Experience and education. New York, NY: Simon & Schuster.

    Google Scholar 

  • D'Mello, S., & Graesser, A. (2012). Dynamics of affective states during complex learning. Learning and Instruction, 22(2), 145–157.

    Article  Google Scholar 

  • Durning, S., Artino Jr., A. R., Pangaro, L., van der Vleuten, C. P. M., & Schuwirth, L. (2011). Context and clinical reasoning: Understanding the perspective of the expert’s voice. Medical Education, 45(9), 927–938.

    Article  Google Scholar 

  • Elstein, S. A., Shulman, L. S., & Sprafka, S. A. (1978). Medical problem solving: An analysis of clinical reasoning. Cambridge, MA: Harvard University Press.

    Book  Google Scholar 

  • Ericsson, K. A. (2008). Deliberate practice and acquisition of expert performance: A general overview. Academic Emergency Medicine, 15(11), 988–994.

    Article  Google Scholar 

  • Eva, K. W. (2005). What every teacher needs to know about clinical reasoning. Medical Education, 39(1), 98–106.

    Article  Google Scholar 

  • Eva, K. W., & Regehr, G. (2005). Self-assessment in the health professions: A reformulation and research agenda. Academic Medicine, 80(10), S46–S54.

    Article  Google Scholar 

  • Evans, C. (2013). Making sense of assessment feedback in higher education. Review of Educational Research, 83(1), 70–120.

    Article  Google Scholar 

  • Henderson, A. J., Alexander, H., Haywood, A., Stapleton, P., Cooke, M., Patterson, E., et al. (2010). Promoting and providing expert guidance in work-intensive clinical settings. Vocations and Learning, 3, 141–156.

    Article  Google Scholar 

  • Kassirer, J. P. (2010). Teaching clinical reasoning: Case-based and coached. Academic Medicine, 85(7), 1118–1124.

    Article  Google Scholar 

  • Keller, J. M. (2010). Motivational design for learning and performance: The ARCS model approach. Boston, MA: Springer.

    Book  Google Scholar 

  • Keller, J. M. (1983). Motivational design of instruction. In C. M. Reigeluth (Ed.), Instructional theories and models: An overview of their current status (pp. 383–434). Hillsdale, NJ: Erlbaum.

    Google Scholar 

  • Kolb, D. (1984). Experiential learning. Experience as the source of learning and development. Englewood Cliffs, NJ: Prentice Hall.

    Google Scholar 

  • Krathwohl, D. R. (1998). Methods of educational and social science research: An integrated approach (2nd ed.). New York: Longman.

    Google Scholar 

  • Kuhn, G. J. (2002). Diagnostic errors. Academic Emergency Medicine, 9(7), 740–750.

    Article  Google Scholar 

  • Lajoie, S. P., Lavigne, N. C., Guerrera, C., & Munsie, S. D. (2001). Constructing knowledge in the context of BioWorld. Instructional Science, 29(2), 155–186.

    Article  Google Scholar 

  • Mamede, S., Van Gog, T., Moura, A. S., de Faria, R. M. D., Peixoto, J. M., Rikers, R., M, J. P., & Schmidt, H. G. (2012). Reflection as a strategy to foster medical students’ acquisition of diagnostic competence. Medical Education, 46(5), 464–472.

    Article  Google Scholar 

  • Mamede, S., & Schmidt, H. G. (2004). The structure of reflective practice in medicine. Medical Education, 38(12), 1302–1308.

    Article  Google Scholar 

  • Mamede, S., Schmidt, H. G., & Penaforte, J. C. (2008). Effects of reflective practice on the accuracy of medical diagnoses. Medical Education, 42(5), 468–475.

    Article  Google Scholar 

  • Mann, K., Gordon, J., & MacLeod, A. (2009). Reflection and reflective practice in health professions education: A systematic review. Advances in Health Sciences Education, 14(4), 595–621.

    Article  Google Scholar 

  • Molloy, E. (2009). Time to pause: Giving and receiving feedback in clinical education. In C. Delany & E. Molloy (Eds.), Clinical education in the health professions (pp. 128–145). Chatswood, NSW: Elsevier.

    Google Scholar 

  • Moon, J. A. (1999). Reflection in learning and professional development: Theory and practice. London, UK: Kogan Page.

    Google Scholar 

  • Mory, E. H. (2003). Feedback research revisited. In D. H. Jonassen (Ed.), Handbook of research on educational communications and technology (pp. 745–783). Mahwah, NJ: Erlbaum.

    Google Scholar 

  • Nelson, M. M., & Schunn, C. D. (2009). The nature of feedback: How different types of peer feedback affect writing performance. Instructional Science, 37(4), 375–401.

    Article  Google Scholar 

  • Norman, G. (2005). Research in clinical history: Past history and current trends. Medical Education, 39, 418–427.

    Article  Google Scholar 

  • Pekrun, R., Goetz, T., Frenzel, A. C., Barchfeld, P., & Perry, R. P. (2011). Measuring emotions in students' learning and performance: The achievement emotions questionnaire (AEQ). Contemporary Educational Psychology, 36(1), 36–48.

    Article  Google Scholar 

  • Peng, J., Wang, M., Sampson, D., & van Merrienboer, J. (2019). Using a visualization-based and progressive learning environment as a cognitive tool for learning computer programming. Australasian Journal of Educational Technology, 35(2), 52–68.

    Article  Google Scholar 

  • Phelps, E. A. (2006). Emotion and cognition: Insights from studies of the human amygdala. Annual Review of Psychology, 57, 27–53.

    Article  Google Scholar 

  • Postma, T. C., & White, J. G. (2015). Developing clinical reasoning in the classroom – Analysis of the 4C/ID model. European Journal of Dental Education, 19(2), 74–80.

    Article  Google Scholar 

  • Ruiz, J. G., Mintzer, M. J., & Leipzig, R. M. (2006). The impact of e-learning in medical education. Academic Medicine, 81(3), 207–212.

    Article  Google Scholar 

  • Schmidt, H. G., & Mamede, S. (2015). How to improve the teaching of clinical reasoning: A narrative review and proposal. Medical Education, 49(10), 961–973.

    Article  Google Scholar 

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

    Google Scholar 

  • Schraw, G., Crippen, K. J., & Hartley, K. (2006). Promoting self-regulation in science education: Metacognition as part of a broader perspective on learning. Research in Science Education, 36(1/2), 111–139.

    Article  Google Scholar 

  • Schutz, P. A., & DeCuir, J. T. (2002). Inquiry on emotions in education. Educational Psychologist, 37(2), 125–134.

    Article  Google Scholar 

  • Shute, V. J. (2008). Focus on formative feedback. Review of Educational Research, 78, 153–189.

    Article  Google Scholar 

  • Sutton, P. (2012). Conceptualizing feedback literacy: Knowing, being, and acting. Innovations in Education and Teaching International, 49(1), 31–40.

    Article  Google Scholar 

  • Telio, S., Ajjawi, R., & Regehr, G. (2015). The "educational Alliance" as a framework for Reconceptualizing feedback in medical education. Academic Medicine, 90(5), 609–614.

    Article  Google Scholar 

  • Tversky, A. (1977). Features of similarity. Psychological Review, 84(4), 327–352.

    Article  Google Scholar 

  • Van de Wiel, M. W. J., Boshuizen, H. P. A., Schmidt, H. G., & Schaper, N. C. (1999). The explanation of clinical concepts by expert physicians, clerks, and advanced students. Teaching and Learning in Medicine, 11(3), 153–163.

    Article  Google Scholar 

  • Van Merrienboer, J. J. G., & Kirschner, P. A. (2018). Ten steps to complex learning: A systematic approach to four-component instructional design. New York, NY: Routledge.

    Google Scholar 

  • Van Merriënboer, J. J. G., & Sweller, J. (2010). Cognitive load theory in health professional education: Design principles and strategies. Medical Education, 44(1), 85–93.

    Article  Google Scholar 

  • Vollmeyer, R., & Rheinberg, F. (2005). A surprising effect of feedback on learning. Learning and Instruction, 15, 589–602.

    Article  Google Scholar 

  • Wang, M. (2018). E-learning in the workplace: A performance-oriented approach beyond technology. Switzerland: Springer.

  • Wang, M., Jia, H., Sugumaran, V., Ran, W., & Liao, J. (2011). A web-based learning system for software test professionals. IEEE Transactions on Education, 54(2), 263–272.

  • Wang, M., Yuan, B., Kirschner, P. A., Kushniruk, A., & Peng, J. (2018). Reflective learning with complex problems in a visualization-based learning environment with expert support. Computers in Human Behavior, 87, 406–415.

    Article  Google Scholar 

  • Williams, R. G., Klamen, D. L., White, C. B., Petrusa, E., Fincher, R. M. E., Whitfield, C. F., et al. (2011). Tracking development of clinical reasoning ability across five medical schools using a progress test. Academic Medicine, 86(9), 1148–1154.

    Article  Google Scholar 

  • Wu, B., & Wang, M. (2012). Integrating problem solving and knowledge construction through dual mapping. Knowledge Management & E-Learning, 4(3), 248–257.

  • Wu, B., Wang, M., Grotzer, T. A., Liu, J., & Johnson, J. M. (2016). Visualizing complex processes using a cognitive-mapping tool to support the learning of clinical reasoning. BMC Medical Education, 16, 216.

    Article  Google Scholar 

  • Wigton, R. S., Poses, R. M., Collins, M., & Cebul, R. D. (1990). Teaching old dogs new tricks: Using cognitive feedback to improve physicians' diagnostic judgments on simulated cases. Academic Medicine, 65(9), S5–S6.

    Article  Google Scholar 

  • Yuan, B., Wang, M., Kushniruk, S. W., & Peng, J. (2016). Design of a computer-based learning environment to support diagnostic problem solving towards expertise development. Knowledge Management & E-Learning, 8(4), 540–549.

Download references

Acknowledgement

This research is supported by the General Research Fund from the Research Grants Council of the Hong Kong SAR Government (Project No. 17201415) and the Seeding Fund for Basic Research from the University of Hong Kong (Project No. 201811159019). The authors would thank Professor David Carless for his advice on the review of the feedback literacy.

Author information

Authors and Affiliations

  1. Zhongshan Teachers Education Institute, Zhongshan, China

    Bei Yuan

  2. KM&EL Lab, Faculty of Education, The University of Hong Kong, Hong Kong, China

    Bei Yuan, Minhong Wang & Jun Peng

  3. Department of Educational Information Technology, East China Normal University, Shanghai, China

    Minhong Wang

  4. Graduate School of Health Professions Education, Maastricht University, Maastricht, The Netherlands

    Jeroen van Merriënboer

  5. Department of Ear, Nose and Throat, Xiangtan Central Hospital, Xiangtan, China

    Xu Tao

  6. School of Health Information Science, University of Victoria, Victoria, Canada

    Andre Kushniruk

  7. School of Education, City University of Macau, Macau, China

    Jun Peng

Authors
  1. Bei Yuan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Minhong Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jeroen van Merriënboer
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Xu Tao
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Andre Kushniruk
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Jun Peng
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Minhong Wang.

Additional information

Publisher’s Note

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

Appendix. Survey instruments

Appendix. Survey instruments

Perceived Enjoyment

I really enjoyed learning with this programme. (Pekrun et al. 2011 & Keller 2010).

I got excited about learning a lot from this course. (Pekrun et al. 2011 & Keller 2010).

I am satisfied with what I have learnt from this programme. (Pekrun et al. 2011 & Keller 2010).

Perceived Confidence

I felt confident when working on the learning tasks. (Pekrun et al. 2011 & Keller 2010).

I felt that I was able to complete the tasks without extra help. (Pekrun et al. 2011 & Keller 2010).

I am confident that my performance in these tasks was good. (Pekrun et al. 2011 & Keller 2010).

Perceived Frustration

I felt so helpless during the learning process that I didn’t want to continue. (Pekrun et al. 2011)

I felt discouraged during the learning process. (Pekrun et al. 2011)

I felt frustrated because I was unable to cope with the tasks. (Pekrun et al. 2011)

Perceived Anxiety

I was often worried about whether I could accomplish the learning task. (Pekrun et al. 2011)

I felt anxious while working on the tasks. (Pekrun et al. 2011)

The learning programme made me sweat. (Pekrun et al. 2011)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yuan, B., Wang, M., van Merriënboer, J. et al. Investigating the Role of Cognitive Feedback in Practice-Oriented Learning for Clinical Diagnostics. Vocations and Learning 13, 159–177 (2020). https://doi.org/10.1007/s12186-019-09234-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12186-019-09234-z

Keywords

Search

Navigation