Skip to main content
Log in

An Exploration of Cognitive Diagnosis in Medical Education: Constructing Comprehensive Feedback for Enhanced Student Learning

  • Monograph
  • Published:
Medical Science Educator Aims and scope Submit manuscript

Abstract

Feedback stands as a cornerstone in facilitating knowledge and skill acquisition, particularly in the realm of self-directed learning. Drawing from Vygotskian theory, which posits learning as an apprenticeship process within the zone of proximal development (ZPD), effective feedback becomes a crucial scaffold for students navigating their educational journey. This article delves into the significance of feedback, guided by Hattie and Timperley’s three pivotal questions. While clinical environments recognize the importance of feedback in patient care, its application during the formative preclerkship years often remains overlooked.

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

Access this article

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

Instant access to the full article PDF.

Fig. 1

Similar content being viewed by others

References

  1. Hattie J. Visible learning: a synthesis of over 800 meta-analyses relating to achievement. London and New York: Routledge; 2009.

    Google Scholar 

  2. Vygotsky LS. Mind in society. Cambridge, MA: Harvard University Press; 1978.

    Google Scholar 

  3. Shute V. Focus on formative feedback. Rev Educ Res. 2008;2008(78):153–89.

    Article  Google Scholar 

  4. Hattie J, Timperley H. The power of feedback. Rev Educ Res. 2007;77:81–112.

    Article  Google Scholar 

  5. Wood D, Bruner JS, Ross G. Role of tutoring in problem-solving. J Child Psychol Psychiatry. 2013;17:89–100.

    Article  Google Scholar 

  6. van den Bergh L, Ros A, Beijaard D. Teacher feedback during active learning: Current practices in primary schools. Br J Educ Psychol. 2013;83(Pt 2):341–62. https://doi.org/10.1111/j.2044-8279.2012.02073.x.

    Article  Google Scholar 

  7. Kelly E, Richards JB. Medical education: Giving feedback to doctors in training. BMJ. 2019;366:l4523. https://doi.org/10.1136/bmj.l4523.

    Article  Google Scholar 

  8. Ramani S, Krackov SK. Twelve tips for giving feedback effectively in the clinical environment. Med Teach. 2012;34(10):787–91. https://doi.org/10.3109/0142159X.2012.684916.

    Article  Google Scholar 

  9. Bangeranye C, Lim YS. How to use cognitively diagnostic assessments of student performance as a method for monitoring and managing the instructional quality in undergraduate medical education. Acad Med. 2020;95(1):145–50. https://doi.org/10.1097/ACM.0000000000002954.

    Article  Google Scholar 

  10. Rupp AA, Templin JL, Henson RA. Diagnostic measurement. Theory, methods, and applications. New York: Guilford; 2010.

  11. de la Torre J, van der Ark A, Rossi G. Analysis of clinical data from a cognitive diagnosis modeling framework. Meas Eval Couns Dev. 2018;51(4):281–96. https://doi.org/10.1080/07481756.2017.1327286.

    Article  Google Scholar 

  12. Sessoms J, Henson RA. Applications of diagnostic classification models: a literature review and critical commentary. Measure: Interdisc Res Perspect. 2018;16(1):1–17.

  13. Lim YS, Drasgow F. Nonparametric calibration of item by attribute matrix in cognitive diagnosis. Multivar Behav Res. 2017;52:562–75.

    Article  Google Scholar 

  14. Chen Y, Culpepper SA, Chen Y, Douglas J. Bayesian estimation of DINA Q matrix. Psychometrika. 2018;83:89–108.

    Article  Google Scholar 

  15. Tatsuoka KK. A probabilistic model for diagnosing misconception in the pattern classification approach. J Educ Behav Stat. 1985;12:55–73.

    Article  Google Scholar 

  16. Junker BW, Sijtsma K. Cognitive assessment models with few assumptions, and connections with nonparametric item response theory. Appl Psychol Meas. 2001;25:258–72.

    Article  Google Scholar 

  17. Liu R, Huggins-Manley AC, Bulut O. Retrofitting diagnostic classification models to responses from IRT-based assessment forms. Educ Psychol Measur. 2018;78(3):357–83. https://doi.org/10.1177/0013164416685599.

    Article  Google Scholar 

  18. Chen J, de la Torre J, Zhang Z. Relative and absolute fit evaluation in cognitive diagnosis modeling. J Educ Meas. 2013;50(2):123–40.

    Article  Google Scholar 

  19. Robitzsch A, Kiefer T, George AC, Uenlue A. CDM: cognitive diagnosis modeling [R package]. Version 7.5-15. 2020. https://cran.r-project.org/package=CDM. Accessed 1 Mar 2021.

  20. Ma W, de la Torre J. GDINA: the generalized DINA model framework [R Package]. Version 2.7.9. 2020. https://cran.r-project.org/package=GDINA. Accessed 1 Mar 2021.

Download references

Funding

None.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Youn Seon Lim.

Ethics declarations

Ethics Approval

This study was deemed exempt by the Hofstra University Internal Review Board.

Informed Consent

N/A.

Conflict of Interest

The authors declare no competing interests.

Additional information

Publisher's Note

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

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lim, Y.S., Willey, J.M. & Bangeranye, C. An Exploration of Cognitive Diagnosis in Medical Education: Constructing Comprehensive Feedback for Enhanced Student Learning. Med.Sci.Educ. (2024). https://doi.org/10.1007/s40670-024-02064-2

Download citation

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s40670-024-02064-2

Keywords

Navigation