#9090. A Short Note on Optimizing Cost-Generalizability via a Machine-Learning Approach

October 2026publication date
Proposal available till 05-06-2025
4 total number of authors per manuscript4500 $

The title of the journal is available only for the authors who have already paid for
Journal’s subject area:
Education;
Applied Mathematics;
Developmental and Educational Psychology;
Applied Psychology;
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Abstract:
The costs of an objective structured clinical examination (OSCE) are of concern to health profession educators globally. As OSCEs are usually designed under generalizability theory (G-theory) framework, this article proposes a machine-learning-based approach to optimize the costs, while maintaining the minimum required generalizability coefficient, a reliability-like index in G-theory.
Keywords:
cost; generalizability theory; optimization; OSCE; reliability

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