In some learning situations, the learning curve begins in a spectacularly flat fashion. At least in the terms of the y-axis competency metric, no learning appears to be happening. However, invisible to the y-axis metric, a great deal of learning is actually happening. This latent phase is seen when considerable foundational and/or procedural knowledge is required before one can even register on a performance metric.
Compound Interest Metaphor for how good early learning begets later accelerated learning.
Of particular relevance to CBME in this early latent phase is learning how to learn. This is the notion of Preparation for Future Learning in which early learning in a domain is partly devoted to learning the subject matter while part is devoted to the mechanics of downstream (later) learning (Mylopoulos et al 2016). For example, the radiology resident described earlier can learn foundational anatomy in the early stages AND they can learn how look up anatomy knowledge in future cases where they have the need. Another good example is learning the skills of Evidence Based Practice and Critical Appraisal of Research Literature. Learning these general skills displaces specific radiology learning (why do I need to know what an Odds Ratio is?) and yet will be repaid many times over when personal development depends on extracting knowledge from the research literature.
Figure 3 – Preparation for Future Learning
In summary, the latent phase of the learning curve is a general phenomenon in the non-linear path to learning. It can mark a transition to the learning to come, in terms of the desired knowledge, skill or attitude. The opportunity lies in the downstream potential of what is laid down at this early stage. Careful attention to not only the immediate subject matter, but also to how the individual will augment and adapt their knowledge and skill base in the future will be repaid many times over.
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Previous Blog Posts in this Series: Part 1: Overture – Click here to read
Future Blog Posts in this Series: Part 3: The nonlinearity of learning(coming Nov 24) Part 4: Standard setting and the learning curve(coming Dec 1) Part 5: Inter-Individual variability of learning curves(coming Dec 15) Part 6: Summary(coming Dec 22)
About the authors: Martin Pusic MD PhD is Associate Professor of Pediatrics and Emergency Medicine at Harvard Medical School, Senior Associate Faculty at Boston Children\’s Hospital and Scholar-In-Residence at the Brigham Education Institute. Kathy Boutis MD FRCPC MScis Staff Emergency Physician, Senior Associate Scientist, Research Institute at The Hospital for Sick Children and Professor of Pediatrics at the University of Toronto.
2. Pusic M, W Cutrer, SA Santen. How does Master Adaptive Learning advance expertise development? Chapter 2, pp 10-17. In: Cutrer W, Pusic MV, eds. The Master Adaptive Learner, Amsterdam, NL. Elsevier Publishing Group. Nov 2019. Available online at https://bit.ly/3Dugc5k
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