3.8 Article

Measuring the Master Adaptive Learner: Development and Internal Structure Validity Evidence for a New Instrument

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MEDICAL SCIENCE EDUCATOR
卷 32, 期 1, 页码 183-193

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SPRINGERNATURE
DOI: 10.1007/s40670-021-01491-9

关键词

Medical students; Self-regulated learning; Goal setting; Survey

资金

  1. AMA Accelerating Change Innovation Grant
  2. AMA Accelerating Change in Medical Education

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This study aimed to develop an instrument for measuring the master adaptive learning (MAL) process in medical students and evaluate its psychometric properties. The findings revealed that the original 67 items were reduced to 28 items that loaded onto four factors: Planning, Learning, Resilience, and Motivation. These findings serve as a starting point for future research to identify and support adaptive learners.
Background The master adaptive learner (MAL) uses self-regulated learning skills to develop adaptive, efficient, and accurate skills in practice. Given rapid changes in healthcare, it is essential that medical students develop into MALs. There is a need for an instrument that can capture MAL behaviors and characteristics. The objective of this study was to develop an instrument for measuring the MAL process in medical students and evaluate its psychometric properties. Methods As part of curriculum evaluation, 818 students completed previously developed instruments with validity evidence including the Self-Regulated Learning Perception Scale, Brief Resilience Scale, Goal Orientation Scale, and Jefferson Scale of Physician Lifelong Learning. The authors performed exploratory factor analysis to examine underlying relationships between items. Items with high factor loadings were retained. Cronbach's alpha was computed. In parallel, the multi-institutional research team rated the same items to provide content validity evidence of the items to MAL model. Results The original 67 items were reduced to 28 items loading onto four factors: Planning, Learning, Resilience, and Motivation. Each subscale included the following number of items and Cronbach's alpha: Planning (10 items, alpha = 0.88), Learning (6 items, alpha = 0.81), Resilience (6 items, alpha = 0.89), and Motivation (6 items, alpha = 0.81). The findings from the factor analyses aligned with the research team ratings of linkage to the components of MAL. Conclusion These findings serve as a starting point for future work measuring master adaptive learning to identify and support learners. To fully measure the MAL construct, additional items may need to be developed.

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