Using multidimensional Rasch analysis to validate the Chinese version of the Motivated Strategies for Learning Questionnaire (MSLQ-CV)

Chi Kin John LEE, Zhonghua ZHANG, Hongbiao YIN

Research output: Contribution to journalArticles

10 Citations (Scopus)

Abstract

This article used the multidimensional random coefficients multinomial logit model to examine the construct validity and detect the substantial differential item functioning (DIF) of the Chinese version of motivated strategies for learning questionnaire (MSLQ-CV). A total of 1,354 Hong Kong junior high school students were administered the MSLQ-CV. Partial credit model was suggested to have a better goodness of fit than that of the rating scale model. Five items with substantial gender or grade DIF were removed from the questionnaire, and the correlations between the subscales indicated that factors of cognitive strategy use and self-regulation had a very high correlation which resulted in a possible combination of the two factors. The test reliability analysis showed that the subscale of test anxiety had a lower reliability compared with the other factors. Finally, the item difficulty and step parameters for the modified 39-item questionnaire were displayed. The order of the step difficulty estimates for some items implied that some grouping of categories might be required in the case of overlapping. Based on these findings, the directions for future research were discussed. Copyright © 2010 Instituto Superior de Psicologia Aplicada, Lisboa, Portugal and Springer Science+Business Media.
Original languageEnglish
Pages (from-to)141-155
JournalEuropean Journal of Psychology of Education
Volume25
Issue number1
DOIs
Publication statusPublished - Mar 2010

Citation

Lee, J. C.-K., Zhang, Z., & Yin, H. (2010). Using multidimensional Rasch analysis to validate the Chinese version of the Motivated Strategies for Learning Questionnaire (MSLQ-CV). European Journal of Psychology of Education, 25(1), 141-155. doi: 10.1007/s10212-009-0009-6

Keywords

  • Chinese version
  • Motivated strategies for learning
  • MSLQ-CV
  • Multidimensional Rasch model
  • MRCMLM
  • DIF

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