Validation of the motivated strategies for learning questionnaire and instructional materials motivation survey.

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...

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Publicado en:Medical Teacher Vol. 47; no. 4; pp. 635 - 646
Autores principales: Cook, David A., Skrupky, Lee P.
Formato: research tables/charts Journal Article
Publicado: Taylor & Francis Ltd Apr2025
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Apr2025
      vid: 47
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      pub: Taylor & Francis Ltd
      place: Philadelphia, Pennsylvania
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        10.1080/0142159X.2024.2357278
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        atl: Validation of the motivated strategies for learning questionnaire and instructional materials motivation survey.
      aug:
        au:
          Cook, David A.
          Skrupky, Lee P.
        affil: Mayo Clinic College of Medicine and Science, and General Internal Medicine, Mayo Clinic, Rochester, MN, USA
      sug:
        subj:
          Instrument Validation
          Motivation Evaluation
          Learning
          Questionnaires
          Models, Educational
          Funding Source
          Human
          Male
          Female
          Pharmacists
          Physicians
          Random Sample
          Factor Analysis
          Coefficient alpha
          P-Value
          Data Analysis Software
          Descriptive Statistics
          Male
          Female
      ab: 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.
      pubtype: Academic Journal
      doctype:
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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