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Meta-Analyzing the Factor Structure of the Learning and Study Strategies Inventory (Journal Article)

By: Material type: TextTextSeries: The Journal of Experimental Education, Volume 91,2023 number 2Publication details: USA :Taylor and Francis Group and Routledge ,March 2023Description: 380-400 pISSN:
  • 0022-0973
Subject(s): DDC classification:
  • 370.5
Online resources:
Contents:
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Summary: Abstract- The Learning and Study Strategies Inventory (LASSI; Weinstein et al., Learning and study strategies inventory. H&H Publishing, 1987) is a prominent instrument used in thousands of institutions worldwide as an educational and research tool. Despite its widespread prevalence, there are inconsistencies regarding the underlying latent structure of the instrument’s 10 subscales. Although there are theoretical conceptions of the latent factors, prior empirical work has challenged the originally proposed factor structure. Using meta-analytic SEM (MASEM) on 86 studies, we tested four factor structure models derived from theory and prior studies and found one model indicating good fit and a parsimonious factor structure. Our study highlights the use of MASEM technique in psychometric applications to test the factor structure of multidimensional instruments and help drive theoretical development in the learning sciences. Implications from our study include the categorizations of learning strategies and how they might be taught in learning strategy courses.
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Item type Current library Call number Status Date due Barcode
Periodicals Periodicals RIE BPL Library 370.5 (Browse shelf(Opens below)) Not for loan

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Abstract-

The Learning and Study Strategies Inventory (LASSI; Weinstein et al., Learning and study strategies inventory. H&H Publishing, 1987) is a prominent instrument used in thousands of institutions worldwide as an educational and research tool. Despite its widespread prevalence, there are inconsistencies regarding the underlying latent structure of the instrument’s 10 subscales. Although there are theoretical conceptions of the latent factors, prior empirical work has challenged the originally proposed factor structure. Using meta-analytic SEM (MASEM) on 86 studies, we tested four factor structure models derived from theory and prior studies and found one model indicating good fit and a parsimonious factor structure. Our study highlights the use of MASEM technique in psychometric applications to test the factor structure of multidimensional instruments and help drive theoretical development in the learning sciences. Implications from our study include the categorizations of learning strategies and how they might be taught in learning strategy courses.













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