Your browser doesn't support javascript.
loading
Validation of the motivated strategies for learning questionnaire and instructional materials motivation survey.
Cook, David A; Skrupky, Lee P.
Afiliação
  • Cook DA; Mayo Clinic College of Medicine and Science, and General Internal Medicine, Mayo Clinic, Rochester, MN, USA.
  • Skrupky LP; University of Wisconsin Health Center for Clinic Knowledge Management, Madison, WI.
Med Teach ; : 1-11, 2024 May 28.
Article em En | MEDLINE | ID: mdl-38803296
ABSTRACT

PURPOSE:

To validate the Motivated Strategies for Learning Questionnaire (MSLQ), which measures learner motivations; and the Instructional Materials Motivation Survey (IMMS), which measures the motivational properties of educational activities.

METHODS:

Participants (333 pharmacists, physicians, and advanced practice providers) completed the MSLQ, IMMS, Congruence-Personalization Questionnaire (CPQ), and a knowledge test immediately following an online learning module (April 2021). We randomly divided data for split-sample analysis using confirmatory factor analysis (CFA), exploratory factor analysis (EFA), and the multitrait-multimethod matrix.

RESULTS:

Cronbach alpha was ≥0.70 for most domains. CFA using sample 1 demonstrated suboptimal fit for both instruments, including 3 negatively-worded IMMS items with particularly low loadings. Revised IMMS (RIMMS) scores (which omit negatively-worded items) demonstrated better fit. Guided by EFA, we identified a novel 3-domain, 11-item 'MSLQ-Short Form-Revised' (MSLQ-SFR, with domains Interest, Self-efficacy, and Attribution) and the 4-domain, 12-item RIMMS as the best models. CFA using sample 2 confirmed good fit. Correlations among MSLQ-SFR, RIMMS, and CPQ scores aligned with predictions; correlations with knowledge scores were small.

CONCLUSIONS:

Original MSLQ and IMMS scores show poor model fit, with negatively-worded items notably divergent. Revised, shorter models-the MSLQ-SFR and RIMMS-show satisfactory model fit (internal structure) and relations with other variables.
Palavras-chave

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article