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Using personalized teaching and learning to improve clinical performance
Author(s) -
John Sandars,
Rakesh Patel
Publication year - 2018
Publication title -
british journal of hospital medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.196
H-Index - 28
eISSN - 1759-7390
pISSN - 1750-8460
DOI - 10.12968/hmed.2018.79.2.102
Subject(s) - medicine , process (computing) , psychological intervention , component (thermodynamics) , personalized learning , personalized medicine , variety (cybernetics) , key (lock) , medical education , teaching method , human–computer interaction , computer science , artificial intelligence , bioinformatics , cooperative learning , open learning , nursing , mathematics education , psychology , physics , computer security , biology , thermodynamics , operating system
The intention of personalized teaching and learning to improve clinical performance is the optimization of individual performance across a variety of tasks in different environments. Educational interventions need to have a focus on the assessment and feedback of both outcome and process of performance. An essential component of the assessment and feedback on the process of performance is how 'the will' and 'the skill' are dynamically adapted by the individual through self-regulated learning processes. Microanalysis can identify the key self-regulated learning processes and the findings used to inform self-regulated learning enhanced feedback for personalized teaching and learning. The experience of the authors in using self-regulated learning enhanced feedback for optimizing performance in prescribing by junior doctors is discussed.

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