اللاتغاير الكلي والجزئي لبنية مقياس الاتجاهات نحو تعلم العلوم باستخدام التحليل العاملي التوكيدي: دراسة مقارنة بين السعودية وسنغافورة لبيانات الدراسة الدولية للرياضيات والعلوم TIMSS

Abu-Hilal, M. M. (2001). Correlates of achievement in the United Arab Emirates: A sociocultural study. In D. M. McInerney & S. Van Etten (Eds.), Research on sociocultural influences on motivation and learning (Vol. 1, pp. 205–230). Information Age.

Baumgartner, H., & Steenkamp, J. B. E. M. (1998). Multi-group latent variable models for varying numbers of items and factors with cross-national and longitudinal applications. Marketing Letters, 9(1), 21-35. https://doi.org/10.1023/A:1007911903032

Becker, M., McElvany, N., & Kortenbruck, M. (2010). Intrinsic and extrinsic reading motivation as predictors of reading literacy: A longitudinal study. Journal of Educational Psychology, 102(4), 773–785. https://doi.org/10.1037/a0020084

Bollen, K. A. (1989). Structural equations with latent variables. Wiley.

Brown, T. A. (2015). Confirmatory factor analysis for applied research (2nd ed.). The Guilford Press.

Byrne, B. M., Shavelson, R. J., & Muthen, B. (1989). Testing for the equivalence of factor covariance and mean structures: The issue of partial measurement invariance. Psychological Bulletin, 105, 456–466. https://doi.org/10.1037/0033-2909.105.3.456

Byrne, B. M. (2012). Structural equation modeling with Mplus: Basic concepts, applications, and programming (2nd ed.). Routledge. https://doi.org/10.4324/9780203807644

de Ayala, R. J. (2022). The theory and practice of item response theory. Guilford Press.

Dawis, R. V. (1987). Scale construction. Journal of Counseling Psychology, 34(4), 481–489. https://doi.org/10.1037/0022-0167.34.4.481

Edwards, J. R., & Bagozzi, R. P. (2000). On the nature and direction of relationships between constructs and measures. Psychological Methods, 5(2). https://doi.org/10.1037/1082-989X.5.2

Chen, F. F. (2007). Sensitivity of goodness of fit indexes to lack of measurement invariance. Structural Equation Modeling, 14(3), 464–504. https://doi.org/10.1080/10705510701301834

Cheung, G. W., & Rensvold, R. B. (2002). Evaluating goodness-of-fit indexes for testing measurement invariance. Structural Equation Modeling, 9(2), 233–255. https://doi.org/10.1207/S15328007SEM0902_5

Ghasemi, E., & Burley, H. (2019). Gender, affect, and math: A cross-national meta-analysis of Trends in International Mathematics and Science Study 2015 outcomes. Large-scale Assessments in Education, 7, 10. https://doi.org/10.1186/s40536-019-0078-1

Gottfried, A. E. (1990). Academic intrinsic motivation in young elementary school children. Journal of Educational Psychology, 82(3), 525–538. https://doi.org/10.1037/0022-0663.82.3.525

LaRoche, S., & Foy, P. (2020). Sample implementation in TIMSS 2019. In M. O. Martin, M. von Davier, & I. V. S. Mullis (Eds.), Methods and Procedures: TIMSS 2019 Technical Report (pp. 9.1-9.261). Retrieved from Boston College, TIMSS & PIRLS International Study Center. https://timssandpirls.bc.edu/timss2019/methods/chapter-9.html

Li, C. H. (2016). Confirmatory factor analysis with ordinal data: Comparing robust maximum likelihood and diagonally weighted least squares. Behavioral Research, 48, 936–949. https://doi.org/10.3758/s13428-015-0619-7

Liou, P.-Y., & Lin, J. J. H. (2021). Comparisons of science motivational beliefs of adolescents in Taiwan, Australia, and the United States: Assessing the measurement invariance across countries and genders. Frontiers in Psychology, 12, 674902. https://doi.org/10.3389/fpsyg.2021.674902

Lord, F. M., & Novick, M. R. (1968). Statistical theories of mental test scores. Addison-Wesley.

Marsh, H. W., Abduljabbar, A. S., Abu-Hilal, M. M., Morin, A. J. S., Abdelfattah, F., Leung, K. C., Xu, M. K., Nagengast, B., & Parker, P. (2013). Factorial, convergent, and discriminant validity of TIMSS math and science motivation measures: A comparison of Arab and Anglo-Saxon countries. Journal of Educational Psychology, 105(1), 108–128. https://doi.org/10.1037/a0029907

Marsh, H. W., & Craven, R. G. (2006). Reciprocal effects of self-concept and performance from a multidimensional perspective: Beyond seductive pleasure and unidimensional perspectives. Perspectives on Psychological Science, 1(2), 133–163. https://doi.org/10.1111/j.1745-6916.2006.00010.x

Meade, A. W., & Lautenschlager, G. J. (2004). A comparison of item response theory and confirmatory factor analytic methodologies for establishing measurement equivalence/invariance. Organizational Research Methods, 7(4), 361–388. https://doi.org/10.1177/1094428104268027

Meyer, J., Fleckenstein, J., & Köller, O. (2019). Expectancy value interactions and academic achievement: Differential relationships with achievement measures. Contemporary Educational Psychology, 58, 58–74. https://doi.org/10.1016/j.cedpsych.2019.01.006

Millsap, R. E. (2011). Statistical approaches to measurement invariance. Routledge/Taylor & Francis Group.

Mullis, I. V. S., Martin, M. O., Foy, P., Kelly, D. L., & Fishbein, B. (2020). TIMSS 2019 International Results in Mathematics and Science. Boston College, TIMSS & PIRLS International Study Center. Available online at https://timssandpirls.bc.edu/timss2019/international-results/ (accessed February 10, 2021).

Mullis, I. V. S., & Martin, M. O. (Eds.). (2017). TIMSS 2019 assessment frameworks. Retrieved from Boston College, TIMSS & PIRLS International Study Center website: http://timssandpirls.bc.edu/timss2019/frameworks/

Muthén, L. K., & Muthén, B. O. (2017). Mplus: Statistical analysis with latent variables: User’s guide (Version 7). Los Angeles, CA: Authors.

Nagengast, B., & Marsh, H. (2014). Motivation and engagement in science around the globe: Testing measurement invariance with multigroup structural equation models across 57 countries using PISA 2006. In L. Rutkowski, M. von Davier, & D. Rutkowski (Eds.), Handbook of international large-scale assessment: Background, technical issues, and data analysis (pp. 317–344). Chapman & Hall/CRC Press.

O'Dea, R. E., Lagisz, M., Jennions, M. D., & Nakagawa, S. (2018). Gender differences in individual variation in academic grades fail to fit expected patterns for STEM. Nature Communications, 9(1), 3777. https://doi.org/10.1038/s41467-018-06292-0

Reise, S. P., Widaman, K. F., & Pugh, R. H. (1993). Confirmatory factor analysis and item response theory: Two approaches for exploring measurement invariance. Psychological Bulletin, 114(3), 552–566. https://doi.org/10.1037/0033-2909.114.3.552

Schmitt, N., & Kuljanin, G. (2008). Measurement invariance: Review of practice and implications. Human Resource Management Review, 18, 210–222. https://doi.org/10.1016/j.hrmr.2008.03.001

Shen, C., & Tam, H. P. (2006). The paradoxical relationship between students’ achievement and their self-perceptions: A cross-national analysis based on three waves of TIMSS data. In H. Wagemaker (Ed.), The Second IEA International Research Conference: Proceedings of the IRC-2006, Vol. 1: Trends in International Mathematics and Science Study (TIMSS) (pp. 43–60). International Association for the Evaluation of Educational Achievement.

Steinmetz, H., Schmidt, P., Tina-Booh, A., Wieczorek, S., & Schwartz, S. H. (2009). Testing measurement invariance using multigroup CFA: Differences between educational groups in human values measurement. Quality & Quantity: International Journal of Methodology, 43(4), 599–616. https://doi.org/10.1007/s11135-007-9143-x

Vandenberg, R. J., & Lance, C. E. (2000). A review and synthesis of the measurement invariance literature: Suggestions, practices, and recommendations for organizational research. Organizational Research Methods, 3(1), 4–69. https://doi.org/10.1177/109442810031002

Wang, J., & Wang, X. (2020). Structural equation modeling application using Mplus (2nd ed.). Wiley. https://onlinelibrary.wiley.com/doi/book/10.1002/9781119422730

Wells, C. S. (2021). Assessing measurement invariance for applied research. Cambridge University Press. https://doi.org/10.1017/9781108750561

West, S. G., Wu, W., McNeish, D., & Savord, A. (2023). Model fit in structural equation modeling. In R. H. Hoyle (Ed.), Handbook of structural equation modeling (2nd ed., pp. 184–205). Guilford Press.

World Economic Forum. (2020). The global gender gap report. Retrieved from http://www3.weforum.org/docs/WEF_GGGR_2020.pdf

Widaman, K. F., & Aguilar, M. O. (2023). Investigating measurement invariance using confirmatory factor analysis. In R. H. Roky (Ed.), Handbook of structural equation modeling (2nd ed., pp. 367–385). Guilford Press.