Research Article
BibTex RIS Cite

Investigation of The Measurement Invariance of Affective Characteristics Related to TIMSS 2019 Mathematics Achievement by Gender

Year 2023, Volume: 14 Issue: 3, 185 - 199, 30.09.2023
https://doi.org/10.21031/epod.1221365

Abstract

This research examines whether the affective characteristics of the TIMSS 2019 Turkey mathematics application provide measurement invariance according to gender. The research sample consists of 4048 8th-grade students participating in the TIMSS in 2019. Research data were downloaded from the international website of TIMSS. The research data collection tools are “Sense of School Belonging”, “Students Confident in Mathematics”, “Students Like Learning Mathematics”, and “Students Value Mathematics” scales. Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) were performed in the context of validity analyses to examine measurement invariance. In terms of reliability, the Cronbach Alfa internal consistency coefficient was calculated. Accordingly, out of the four scales in the study, only “Students Confident in Mathematics” scale could not be confirmed in confirmatory factor analysis. Therefore, while “Students Confident in Mathematics” scale was not examined for measurement invariance, the other three scales were examined within the scope of measurement invariance. For measurement invariance, research data were tested with Multiple Group Confirmatory Factor Analysis (MG-CFA), one of the Structural Equation Modeling (SEM) techniques. As a result of the analyses, while the strict invariance model was provided in “Students Like Learning Mathematics” scale and “Students Value Mathematics” scale, strong invariance/scale invariance model was provided in “Sense of School Belonging” scale. It was concluded that there was no gender bias in the three scales for which MG-CFA was performed, and the mean scores were comparable according to gender. In this context, it can be said that “Sense of School Belonging”, “Students Like Learning Mathematics”, and “Students Value Mathematics” scales are valid in determining the differences according to gender.

References

  • Akyüz-Aru, S. (2020). 4. sınıf öğrencilerinin fen ve matematik başarısına etki eden değişkenlerin incelenmesi “TIMSS 2015 durum analizi” [Investigation of variables affecting science and mathematics success of grade 4 students "TIMSS 2015 status analysis"] [Unpublished doctoral dissertation]. Gazi Üniversitesi. https://tez.yok.gov.tr/UlusalTezMerkezi/
  • Akyüz, G., & Pala, N. M. (2010). PISA 2003 sonuçlarına göre öğrenci ve sınıf özelliklerinin matematik okuryazarlığına ve problem çözme becerilerine etkisi [The effect of student and class characteristics on mathematics literacy and problem solving in PISA 2003]. İlköğretim Online, 9(2), 668-678.
  • Akyüz, G., & Satıcı, K. (2013). PISA 2003 verilerine göre matematik okuryazarlığının çeşitli değişkenler açısından incelenmesi: Türkiye ve Hong Kong-Çin modelleri [Investigation of the factors affecting mathematics literacy using PISA 2003 results: Turkey and Hong Kong-China]. Kastamonu Üniversitesi Kastamonu Eğitim Dergisi, 21(2), 503 - 522.
  • Atar, B. (2011). Tanımlayıcı ve Açıklayıcı Madde Tepki Modellerinin TIMSS 2007 Türkiye Matematik Verisine Uyarlanması [An application of descriptive and explanatory ıtem response models to TIMSS 2007 Turkey mathematics data]. Eğitim ve Bilim, 36(159), 255 - 269.
  • Aydın, M. (2015). Öğrenci ve okul kaynaklı faktörlerin TIMSS matematik başarısına etkisi [The effects of student-level and school-level factors on middle school students' mathematics achievement] [Unpublished doctoral dissertation]. Necmettin Erbakan Üniversitesi. https://tez.yok.gov.tr/UlusalTezMerkezi/
  • Başusta, N. B., & Gelbal, S. (2015). Gruplar arası karşılaştırmalarda ölçme değişmezliğinin test edilmesi: PISA öğrenci anketi örneği [Examination of Measurement Invariance at Groups’ Comparisons: A Study on PISA Student Questionnaire]. Hacettepe Üniversitesi Eğitim Fakültesi Dergisi, 30(4), 80-90.
  • Bloom, B. S. (2012). İnsan nitelikleri ve okulda öğrenme [Human characteristics and school learning] (D. A. Özçelik, Trans.). Pegem Akademi.
  • Bofah, E.At., & Hannula, M.S. (2015). TIMSS data in an African comparative perspective: Investigating the factors influencing achievement in mathematics and their psychometric properties. Large-scale Assessments in Education, 3(4), 1-36. https://doi.org/10.1186/s40536-015-0014-y
  • Byrne, B. M. (1998). Structural equation modeling with LISREL, PRELIS and SIMPLIS: Basic concepts, application and programming. Lawrence Erlbaum.
  • Byrne, B. M., Shavelson, R. J., & Muthén, B. (1989). Testing for the equivalence of factor covariance and mean structures: The issue of partial measurement invariance. Psychological Bulletin, 105(3), 456–466. https://doi.org/10.1037/0033-2909.105.3.456 Byrne, B. M. & Watkins, D. (2003). The issue of measurement invariance revisited. Journal of Cross-Cultural Psychology, 34(2), 155–175. https://doi.org/10.1177/0022022102250225
  • Cakici-Eser, D. (2021). Investigation of measurement ınvariance according to home resources: TIMSS 2015 mathematical affective characteristics questionnaire. International Journal of Assessment Tools in Education, 8(3), 633-648. https://doi.org/10.21449/ijate.817168
  • Chen, F. F. (2007). Sensitivity of goodness of fit indexes to lack of measurement invariance. Structural Equation Modeling: A Multidisciplinary Journal, 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.
  • Cheung, G., W., & Rensvold, R. B. (2000). Assessing extreme and acquiescence response sets in cross-cultural research using structural equations modeling. Journal of Cross-cultural Psychology, 31(2), 188–213. https://doi.org/10.1177/0022022100031002003
  • Çokluk, Ö., Şekercioğlu, G., & Büyüköztürk, Ş. (2016). Sosyal bilimler için çok değişkenli istatistik SPSS ve LISREL uygulamaları (5. Baskı) [Multivariate statistics SPSS and LISREL applications for social sciences (5th ed.)]. Pegem Akademi.
  • Demir, E. (2017). Testing measurement invariance of the students’ affective characteristics model across gender sub-groups. Educational Sciences:Theory and Practice, 17(1), 47–62. https://doi.org/10.12738/estp.2017.1.0223
  • Demir, İ., Kılıç, S., & Ünal, H. (2010). Effects of students' and schools' characteristics on mathematics achievement: Findings from PISA 2006. Procedia - Social and Behavioral Sciences, 2(2), 3099-3103. https://doi.org/10.1016/j.sbspro.2010.03.472
  • Demir, M. C. (2020). TIMSS 2015 fen duyuşsal özelliklerinin cinsiyet ve bölgelere göre incelenmesi [An examination of TIMMS 2015 science affective factors with regard to gender and regions] [Unpublished master's dissertation]. Hacettepe Üniversitesi. https://tez.yok.gov.tr/UlusalTezMerkezi/
  • Doğan, N., & Barış, F. (2010). Tutum, değer ve özyeterlik değişkenlerinin TIMSS-1999 ve TIMSS-2007 Sınavlarında öğrencilerin matematik başarılarını yordama düzeyleri [Prediction levels of attitude, value and self-efficacy variables for students' mathematics achievement in TIMSS-1999 and TIMSS-2007 Exams]. Eğitimde ve Psikolojide Ölçme ve Değerlendirme Dergisi, 1(1), 44-50.
  • Ercikan, K., & Koh, K. (2005). Examining the construct comparability of the English and French versions of TIMSS. International Journal of Testing, 5(1), 23-35. https://doi.org/10.1207/s15327574ijt0501_3
  • Erşan, Ö. (2016). TIMSS 2011 sekizinci sınıf öğrencilerinin matematik başarılarını etkileyen faktörlerin çok düzeyli yapısal eşitlik modeliyle incelenmesi [Investigation of the factors affecting mathematics achievement of TIMSS 2011 eighth grade students with multilevel structural equation modeling] [Unpublished master's dissertation]. Hacettepe Üniversitesi. https://tez.yok.gov.tr/UlusalTezMerkezi/
  • Ertürk, Z., & Erdinç-Akan, O. (2018a). TIMSS 2015 matematik başarısını etkileyen değişkenlerin yapısal eşitlik modeli ile incelenmesi [The Investigation of the Variables Effecting TIMSS 2015 Mathematics Achievement with SEM]. Ulusal Eğitim Akademisi Dergisi (UEAD), 2(2), 14-34. https://doi.org/10.32960/uead.407078
  • Ertürk, Z., & Erdinç-Akan, O. (2018b). TIMSS 2015 matematik başarısı ile ilgili bazı değişkenlerin cinsiyete göre ölçme değişmezliğinin incelenmesi [The Investigation of Measurement Invariance of the Variables Related to TIMSS 2015 Mathematics Achievement in terms of Gender]. Kuramsal Eğitimbilim Dergisi [Journal of Theoretical Educational Science], UBEK-2018, 204-226. https://doi.org/10.30831/akukeg.412604
  • Fraenkel, J. R., & Wallen, N.E. (2006). How to design and evaluate research in education. McGraw-Hill.
  • French, B. F., & Finch, W. H. (2006). Confirmatory factor analytic procedures for the determination of measurement ınvariance. Structural Equation Modeling: A Multidisciplinary Journal, 13(3), 378–402. https://doi.org/10.1207/s15328007sem1303_3
  • Gregorich, S. E. (2006). Do self-report instruments allow meaningful comparisons across diverse population groups?: Testing measurement invariance using the confirmatory factor analysis framework. Medical Care, 44(11), 78-94. https://doi.org/10.1097/01.mlr.0000245454.12228.8f
  • Gungor, M., & Atalay-Kabasakal, K. (2020). Investigation of measurement ınvariance of science motivation and self-efficacy model: PISA 2015 Turkey sample. International Journal of Assessment Tools in Education, 7 (2), 207-222. https://doi.org/10.21449/ijate.730481
  • Gülleroğlu, H. D. (2017). PISA 2012 matematik uygulamasına katılan Türk öğrencilerin duyuşsal özeliklerinin cinsiyete göre ölçme değişmezliğinin incelenmesi [An investigation of measurement invariance by gender for the Turkish students’ affective characteristics who took the PISA 2012 math test]. Gazi Eğitim Fakültesi Dergisi, 37(1), 151-175.
  • Hair Jr, J. F., Black, C. W., Babin, B. J., & Anderson, R. E. (2014). Multivariate data analysis (7th ed.). Pearson Education.
  • Hanci, A. (2015). 8. sınıf öğrencilerinin öğrenme stilleri ve TIMSS matematik başarılarının farklı değişkenler açısından incelenmesi: Bayburt ili örneği [Investigation of 8th grade students' learning styles and TIMSS matematics achivements from the aspect of different variable: Bayburt sample] [Unpublished master's dissertation]. Bayburt Üniversitesi. https://tez.yok.gov.tr/UlusalTezMerkezi/
  • Harrington, D. (2009). Confirmatory factor analysis. Oxforda University Press, Inc.
  • Işlak, O. (2020). TIMSS 2015 uygulamasına katılan öğrencilerin matematik başarılarının öğrenci, aile ve okul değişkenlerine göre yordanma [Prediction of mathematics achievement of students attending TIMSS 2015 according to student, family and school variables] [Unpublished doctoral dissertation]. Burdur Mehmet Akif Ersoy Üniversitesi. https://tez.yok.gov.tr/UlusalTezMerkezi/
  • İlhan, M., & Öner-Sünkür, M. (2012). Matematik kaygısı ile olumlu ve olumsuz mükemmeliyetçiliğin matematik başarısını yordama gücü [The predictive power of mathematics anxiety and positive and negative perfectionism on math achievement]. Mersin Üniversitesi Eğitim Fakültesi Dergisi, 8(1), 178-188.
  • Jorgensen, T. D., Pornprasertmanit, S., Schoemann, A. M., & Rosseel, Y. (2021). semTools: Useful tools for structural equation modeling. R package version 0.5-5. Retrieved from https://CRAN.R-project.org/package=semTools
  • Jung, J. Y. (2019). A Comparison of CFA and ESEM approaches using TIMSS science attitudes items: Evidence from factor structure and measurement invariance [Unpublished master's dissertation]. Purdue University.
  • Karakoc-Alatli, B., Ayan, C., Polat-Demir, B., & Uzun, G. (2016). Examination of the TIMSS 2011 fourth grade mathematics test in terms of cross-cultural measurement invariance. Eurasian Journal of Educational Research, 66, 389-406. https://doi.org/10.14689/ejer.2016.66.22
  • Karasar, N (2011). Bilimsel Araştırma Yöntemi [Scientific Research Method]. Nobel Yayıncılık.
  • Kesici, A. (2018). Lise öğrencilerinin matematik motivasyonunun matematik başarısına etkisinin incelenmesi. OMÜ Eğitim Fakültesi Dergisi, 37(2), 177-194. https://doi.org/10.7822/omuefd.438550
  • Kesici, A., & Aşılıoğlu, B. (2017). Ortaokul öğrencilerinin matematiğe yönelik duyuşsal özellikleri ile temel eğitimden ortaöğretime geçiş (TEOG) sınavları öncesi yaşadıkları stresin matematik başarısına etkisi [The Effect of Secondary Students' Affective Features Towards Mathematics and The Stress They Experience Before The TEOG Exam (The Exam For Accessing to Various Types of High Schools) on Their Mathematical Success]. Kırşehir Eğitim Fakültesi Dergisi, 18(3), 394-414.
  • Khine, M. S., Al-Mutawah, M., & Afari, E. (2015). Determinants of affective factors in mathematics achievement: Structural equation modeling approach. Journal of Studies in Education, 5(2), 199–211.
  • Kıbrıslıoğlu, N. (2015). PISA 2012 matematik öğrenme modelinin kültürlere ve cinsiyete göre ölçme değişmezliğinin incelenmesi: Türkiye – Çin (Şangay) – Endonezya örneği [The investigation of measurement invariance PISA 2012 mathematics learning model according to culture and gender: Turkey - China (Shangai) - Indonesia] [Unpublished master's dissertation]. Hacettepe Üniversitesi. https://tez.yok.gov.tr/UlusalTezMerkezi/
  • Kilic, S. & Askin, Ö. E. (2013). Parental influence on students’ mathematics achievement: the comparative study of Turkey and best performer countries in TIMSS 2011. Procedia - Social and Behavioral Sciences, 106, 2000-2007. https://doi.org/10.1016/j.sbspro.2013.12.228
  • Kline, R. B. (2015). Principles and practices of structural equation modeling (4th ed.). The Guilford Press.
  • Koç, O. (2019). 4. ve 8. sınıf öğrencilerinin TIMSS 2015 matematik başarısını yordayan değişkenlerin belirlenmesi [Determination of predictive variables of 4th and 8th grade students' on TIMSS 2015 mathematics achievement] [Unpublished master's dissertation]. Akdeniz Üniversitesi. https://tez.yok.gov.tr/UlusalTezMerkezi/
  • Lay, Y. F., Ng, K. T., & Chong, P. S. (2015). Analyzing affective factors related to eighth grade learners’ science and mathematics achievement in TIMSS 2007. Asia-Pacific Education Researcher, 24(1), 103–110. https://doi.org/10.1007/s40299-013-0163-0
  • Louis, R.A., & Mistele, J.M. (2012). The differences in scores and self-efficacy by student gender in mathematics and science. International Journal of Science and Mathematics Education, 10, 1163–1190. https://doi.org/10.1007/s10763-011-9325-9
  • Ma, Y., & Qin, X. (2021). Measurement invariance of information, communication and technology (ICT) engagement and its relationship with student academic literacy: Evidence from PISA 2018. Studies in Educational Evaluation, 68, 1–15. https://doi.org/10.1016/j.stueduc.2021.100982
  • Meade, A. W., Johnson, E. C., & Braddy, P. W. (2008). Power and sensitivity of alternative fit indices in tests of measurement invariance. Journal of Applied Psychology, 93(3), 568–592. https://doi.org/10.1037/0021-9010.93.3.568
  • Ministry of National Education (MoNE) (2020). TIMSS 2019 Türkiye ön raporu [TIMSS 2019 Turkey preliminary report]. Ankara: Ölçme, Değerlendirme ve Sınav Hizmetleri Genel Müdürlüğü.
  • Ministry of National Education (MoNE). (2016). TIMSS 2015 ulusal matematik ve fen ön raporu: 4. ve 8. sınıflar [TIMSS 2015 national math and science preliminary report: 4th and 8th grades]. Ankara.
  • Meng, L., Qiu, C., & Boyd-Wilson, B. (2019). Measurement invariance of the ICT engagement construct and its association with students’ performance in China and Germany: Evidence from PISA 2015 data. British Journal of Educational Technology, 50(6), 3233–3251. https://doi.org/10.1111/bjet.12729
  • Millsap, R. E., & Olivera-Aguilar, M. (2012). Investigating measurement invariance using confirmatory factor analysis. In R. H. Hoyle (Ed.), Handbook of structural equation modeling (pp. 380–392). The Guilford Press.
  • Mindrila, D. (2010). Maximum likelihood (ML) and diagonally weighted least squares (DWLS) estimation procedures: A comparison of estimation bias with ordinal and multivariate non-normal data. International Journal of Digital Society, 1(1), 60–66. https://doi.org/10.20533/ijds.2040.2570.2010.0010
  • Mohammadpour, E. (2012). Factors accounting for mathematics achievement of singaporean eighth-graders. The Asia-Pacific Education Researcher, 21(3), 507-518.
  • Mulaik, S. A. (2007). There is a place for approximate fit in structural equation modelling. Personality and Individual Differences, 42(5), 883-891. https://doi.org/10.1016/j.paid.2006.10.024
  • Mullis, I. V. S., Martin, M. O., Foy, P., & Hooper, M. (2016). TIMSS 2015 international results in mathematics. Boston, US.
  • Oral, I., & McGivney, E. (2013). Türkiye’de matematik ve fen bilimleri alanlarında öğrenci performansı ve başarının belirleyicileri: TIMSS 2011 analizi [Student performance and determinants of success in mathematics and science in Turkey: TIMSS 2011 analysis]. İstanbul: Eğitim Reformu Girişimi Raporu.
  • Öğretmen, T. (2006). Uluslararası okuma becerilerinde gelişim projesi (PIRLS) 2001 testinin psikometrik özelliklerinin incelenmesi: Türkiye-Amerika Birleşik Devletleri örneği [The investigation of psychometric properties of the test of progress in international reading literacy (PIRLS) 2001: The model of Turkey-United States of America] [Unpublished doctoral dissertation]. Hacettepe Üniversitesi. https://tez.yok.gov.tr/UlusalTezMerkezi/
  • Ölçüoğlu, R., & Çetin, S. (2016). TIMSS 2011 sekizinci sınıf öğrencilerinin matematik başarısını etkileyen değişkenlerinin bölgelere göre incelenmesi [The investigation of the variables that affecting eight grade students’ TIMSS 2011 math achievement according to regions]. Eğitimde ve Psikolojide Ölçme ve Değerlendirme Dergisi, 7(1), 202-220. https://doi.org/10.21031/epod.34424
  • Öncü, Ö. (2019). TIMSS 2015 sekizinci sınıf matematik başarı testinin oecd ülkelerine göre ölçme değişmezliğinin incelenmesi [An investication into the measurement invariance according to OECD countries of TIMSS 2015 eight grade math achievement test] [Unpublished master's dissertation]. Akdeniz Üniversitesi. https://tez.yok.gov.tr/UlusalTezMerkezi/
  • Patterson, M., Perry, E., Decker, C., Eckert, R., Klaus, S., Wendling, L., & Papanastasiou, E. (2003). Factors associated with high school mathematics performance in the United States. Studies in Educational Evaluation, 29(2), 91-108. https://doi.org/10.1016/S0191-491X(03)00017-8
  • Pituch, K. A., & Stevens, J. P. (2016). Applied multivariate statistics for the social sciences: Analyses with SAS and IBM’s SPSS (6th Ed.). Routledge.
  • Polat, M. (2019). TIMSS-2015 matematik ve fen duyuşsal özellik modellerinin kültürlere, cinsiyete ve bölgelere göre ölçme değişmezliğinin incelenmesi [The investigation of measurement invariance of TIMSS-2015 mathematics and science affective characteristics models according to culture, gender and statistical region] [Unpublished master's dissertation]. Hacettepe Üniversitesi. https://tez.yok.gov.tr/UlusalTezMerkezi/
  • Raykov, T., & Marcoulides, G. A. (2006). A first course in structural equation modeling (2nd ed.). Lawrence Erlbaum Associates, Publishers.
  • Rosseel, Y. (2012). lavaan: An R package for structural equation modeling. Journal of Statistical Software, 48(2), 1–36. https://doi.org/10.18637/jss.v048.i02
  • Rutkowski, D., & Rutkowski, L. (2013). Measuring socioeconomic background in PISA: One size might not fit all. Research in Comparative and International Education, 8(3), 259–278. https://doi.org/10.2304/rcie.2013.8.3.259
  • Salzberger, T., Sinkovics, R., R., & Schlegelmilch, B. B. (1999). Data equivalence in cross-cultural research: a comparison of classical test theory and latent trait theory based approaches. Australasian Marketing Journal, 7(2), 23-38. https://doi.org/10.1016/S1441-3582(99)70213-2
  • Sarı, M. H., & Ekici, G. (2018). İlkokul 4. sınıf öğrencilerinin matematik başarıları ile aritmetik performanslarını etkileyen duyuşsal değişkenlerin belirlenmesi [Determination of affective variables affecting mathematical achievement and arithmetic performance of primary school 4th grade students]. OPUS International Journal of Society Researches, 8(15), 1562-1594. https://doi.org/10.26466/opus.451025
  • Sarı, M. H., Arıkan, S., & Yıldızlı, H. (2017). 8. sınıf matematik akademik başarısını yordayan faktörler-TIMSS 2015 [Factors predicting mathematics achievement of 8th graders in TIMSS 2015 ]. Eğitimde ve Psikolojide Ölçme ve Değerlendirme Dergisi, 8(3), 246-265.
  • Sarıer, Y. (2020). TIMSS uygulamalarında Türkiye’nin performansı ve akademik başarıyı yordayan değişkenler [Turkey's performance in TIMSS applications and variables predicting academic achievement]. Temel Eğitim Dergisi, 2(2), 6-27.
  • Scherer, R., Nilsen, T., & Jansen, M. (2016). Evaluating individual students’ perceptions of instructional quality: An investigation of their factor structure, measurement invariance, and relations to educational outcomes. Frontiers in Psychology, 7(110), 1-16. https://doi.org/10.3389/fpsyg.2016.00110
  • Schumacker, R. E., & Beyerlein, S. T. (2000). Confirmatory factor analysis with different correlation types and estimation methods. Structural Equation Modeling, 7(4), 629–636. https://doi.org/10.1207/S15328007SEM0704_6
  • Shukla, K., & Konold, T. (2014). Fondness of math and science as measured by the TIMSS student questionnaire: Invariance across U.S. ethnic groups. Paper presented at the 2014 Annual Meeting of the American Educational Research Association, Philadelphia, USA
  • Stark, S., Chernyshenko, O. S., & Drasgow, F. (2006). Detecting differential item functioning with comfirmatory factor analysis and ıtem response theory: Toward a unified strategy. Journal of Applied Psychology, 91(6), 1292–1306. https://doi.org/10.1037/0021-9010.91.6.1292
  • Tabachnick, B. G., & Fidell, L. S. (2013). Using multivariate statistics (6th ed.). Pearson Education.
  • Tavlıca, A. (2019). TIMSS 2015 dördüncü sınıf matematik testinin ölçme değişmezliğinin ülkelere göre incelemesi [An investigation of measurement invariance for TIMSS 2015 fourth grade mathematics test according to countries] [Unpublished master's dissertation]. Akdeniz Üniversitesi. https://tez.yok.gov.tr/UlusalTezMerkezi/
  • Usta, H. G., & Demirtaşlı, R. N. (2018). PISA 2012 matematik okuryazarlığı üzerine uluslararası bir karşılaştırma: Türkiye ve Finlandiya [An international comparison according to PISA 2012 mathematical literacy Turkey and Finland]. Turkish Studies (Elektronik), 13(11), 1389 - 1420. https://doi.org/10.7827/TurkishStudies.13377
  • Uyar, S. (2021). Factor structure and measurement invariance of the TIMSS 2015 mathematics attitude questionnaire: Exploratory structural equation modelling approach. International Journal of Assessment Tools in Education, 8(4), 855–871. https://doi.org/10.21449/ijate.796862
  • Uzun, B., & Öğretmen, T. (2010). Fen başarısı ile ilgili bazı değişkenlerin TIMSS-R Türkiye örnekleminde cinsiyete göre ölçme değişmezliğinin değerlendirilmesi [Assessing the measurement ınvariance of factors that are related to students’ science achievement across gender in TIMSS-R Turkey sample]. Eğitim ve Bilim, 35(155), 26–35.
  • Vandenberg, R. J., & Lance, C. E. (2000). A review and synthesis of the MI literature: Suggestions, practices, and recommendations for organizational research. Organizational Research Methods, 3(1), 4–69. https://doi.org/10.1177/109442810031002
  • Wang, Z., Osterlind, S., & Bergin, D. A. (2012). Building mathematics achievement models in four countries using TIMSS 2003. International Journal of Science and Mathematics Education, 10(5), 1-28. https://doi.org/10.1007/s10763-011-9328-6
  • Webster, B. J., & Fisher, D. L. (2000). Accounting for variation in science and mathematics achievement: A multilevel analysis of Australian data third international mathematics and science study (TIMSS). School Effectiveness and School Improvement, 11(3), 339–360. https://doi.org/10.1076/0924-3453(200009)11:3;1-G;FT339
  • Wicherts, J. M. (2007). Group differences in intelligence test performance [Unpublished doctoral dissertation]. University of Amsterdam.
  • Widaman, K. F., & Reise, S. P. (1997). Exploring the measurement invariance of psychological instruments: Applications in the substance use domain. In K. J. Bryant, M. Windle, & S. G. West (Eds.), The science of prevention: Methodological advances from alcohol and substance abuse research (pp. 281–324). American Psychological Association.
  • Wu, A.D., Li, Z., & Zumbo, B.D. (2007). Decoding the meaning of factorial invariance and updating the practice of multi-group confirmatory factor analysis: A demonstration with TIMSS data. Practical Assessment, Research and Evaluation, 12, 1-26. https://doi.org/10.7275/mhqa-cd89
  • Yandı, A., Köse, İ. A., & Uysal, Ö. (2017). Farklı yöntemlerle ölçme değişmezliğinin incelenmesi: PISA 2012 örneği [Examining measurement invariance with different methods: Example of PISA 2012]. Mersin Üniversitesi Eğitim Bilimleri Dergisi, 13(1), 243-253. https://doi.org/10.17860/mersinefd.305952
  • Yin, L., & Fishbein, B. (2020). Creating and interpreting the TIMSS 2019 context questionnaire scales. In M. O. Martin, M. von Davier, & I. V. S. Mullis (Eds.), Methods and procedures: TIMSS 2019 technical report (pp. 16.1-16.331). Boston College, TIMSS & PIRLS International Study Center. https://timssandpirls.bc.edu/timss2019/methods/chapter-16.html
  • Yücel, Z., & Koç, M. (2011). İlköğretim öğrencilerinin matematik dersine karşı tutumlarının başarı düzeylerini yordama gücü ile cinsiyet arasındaki ilişki [The relationship between the prediction level of elementary school students’ math achievement by their math attitudes and gender]. İlköğretim Online, 10(1), 133-143.
Year 2023, Volume: 14 Issue: 3, 185 - 199, 30.09.2023
https://doi.org/10.21031/epod.1221365

Abstract

References

  • Akyüz-Aru, S. (2020). 4. sınıf öğrencilerinin fen ve matematik başarısına etki eden değişkenlerin incelenmesi “TIMSS 2015 durum analizi” [Investigation of variables affecting science and mathematics success of grade 4 students "TIMSS 2015 status analysis"] [Unpublished doctoral dissertation]. Gazi Üniversitesi. https://tez.yok.gov.tr/UlusalTezMerkezi/
  • Akyüz, G., & Pala, N. M. (2010). PISA 2003 sonuçlarına göre öğrenci ve sınıf özelliklerinin matematik okuryazarlığına ve problem çözme becerilerine etkisi [The effect of student and class characteristics on mathematics literacy and problem solving in PISA 2003]. İlköğretim Online, 9(2), 668-678.
  • Akyüz, G., & Satıcı, K. (2013). PISA 2003 verilerine göre matematik okuryazarlığının çeşitli değişkenler açısından incelenmesi: Türkiye ve Hong Kong-Çin modelleri [Investigation of the factors affecting mathematics literacy using PISA 2003 results: Turkey and Hong Kong-China]. Kastamonu Üniversitesi Kastamonu Eğitim Dergisi, 21(2), 503 - 522.
  • Atar, B. (2011). Tanımlayıcı ve Açıklayıcı Madde Tepki Modellerinin TIMSS 2007 Türkiye Matematik Verisine Uyarlanması [An application of descriptive and explanatory ıtem response models to TIMSS 2007 Turkey mathematics data]. Eğitim ve Bilim, 36(159), 255 - 269.
  • Aydın, M. (2015). Öğrenci ve okul kaynaklı faktörlerin TIMSS matematik başarısına etkisi [The effects of student-level and school-level factors on middle school students' mathematics achievement] [Unpublished doctoral dissertation]. Necmettin Erbakan Üniversitesi. https://tez.yok.gov.tr/UlusalTezMerkezi/
  • Başusta, N. B., & Gelbal, S. (2015). Gruplar arası karşılaştırmalarda ölçme değişmezliğinin test edilmesi: PISA öğrenci anketi örneği [Examination of Measurement Invariance at Groups’ Comparisons: A Study on PISA Student Questionnaire]. Hacettepe Üniversitesi Eğitim Fakültesi Dergisi, 30(4), 80-90.
  • Bloom, B. S. (2012). İnsan nitelikleri ve okulda öğrenme [Human characteristics and school learning] (D. A. Özçelik, Trans.). Pegem Akademi.
  • Bofah, E.At., & Hannula, M.S. (2015). TIMSS data in an African comparative perspective: Investigating the factors influencing achievement in mathematics and their psychometric properties. Large-scale Assessments in Education, 3(4), 1-36. https://doi.org/10.1186/s40536-015-0014-y
  • Byrne, B. M. (1998). Structural equation modeling with LISREL, PRELIS and SIMPLIS: Basic concepts, application and programming. Lawrence Erlbaum.
  • Byrne, B. M., Shavelson, R. J., & Muthén, B. (1989). Testing for the equivalence of factor covariance and mean structures: The issue of partial measurement invariance. Psychological Bulletin, 105(3), 456–466. https://doi.org/10.1037/0033-2909.105.3.456 Byrne, B. M. & Watkins, D. (2003). The issue of measurement invariance revisited. Journal of Cross-Cultural Psychology, 34(2), 155–175. https://doi.org/10.1177/0022022102250225
  • Cakici-Eser, D. (2021). Investigation of measurement ınvariance according to home resources: TIMSS 2015 mathematical affective characteristics questionnaire. International Journal of Assessment Tools in Education, 8(3), 633-648. https://doi.org/10.21449/ijate.817168
  • Chen, F. F. (2007). Sensitivity of goodness of fit indexes to lack of measurement invariance. Structural Equation Modeling: A Multidisciplinary Journal, 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.
  • Cheung, G., W., & Rensvold, R. B. (2000). Assessing extreme and acquiescence response sets in cross-cultural research using structural equations modeling. Journal of Cross-cultural Psychology, 31(2), 188–213. https://doi.org/10.1177/0022022100031002003
  • Çokluk, Ö., Şekercioğlu, G., & Büyüköztürk, Ş. (2016). Sosyal bilimler için çok değişkenli istatistik SPSS ve LISREL uygulamaları (5. Baskı) [Multivariate statistics SPSS and LISREL applications for social sciences (5th ed.)]. Pegem Akademi.
  • Demir, E. (2017). Testing measurement invariance of the students’ affective characteristics model across gender sub-groups. Educational Sciences:Theory and Practice, 17(1), 47–62. https://doi.org/10.12738/estp.2017.1.0223
  • Demir, İ., Kılıç, S., & Ünal, H. (2010). Effects of students' and schools' characteristics on mathematics achievement: Findings from PISA 2006. Procedia - Social and Behavioral Sciences, 2(2), 3099-3103. https://doi.org/10.1016/j.sbspro.2010.03.472
  • Demir, M. C. (2020). TIMSS 2015 fen duyuşsal özelliklerinin cinsiyet ve bölgelere göre incelenmesi [An examination of TIMMS 2015 science affective factors with regard to gender and regions] [Unpublished master's dissertation]. Hacettepe Üniversitesi. https://tez.yok.gov.tr/UlusalTezMerkezi/
  • Doğan, N., & Barış, F. (2010). Tutum, değer ve özyeterlik değişkenlerinin TIMSS-1999 ve TIMSS-2007 Sınavlarında öğrencilerin matematik başarılarını yordama düzeyleri [Prediction levels of attitude, value and self-efficacy variables for students' mathematics achievement in TIMSS-1999 and TIMSS-2007 Exams]. Eğitimde ve Psikolojide Ölçme ve Değerlendirme Dergisi, 1(1), 44-50.
  • Ercikan, K., & Koh, K. (2005). Examining the construct comparability of the English and French versions of TIMSS. International Journal of Testing, 5(1), 23-35. https://doi.org/10.1207/s15327574ijt0501_3
  • Erşan, Ö. (2016). TIMSS 2011 sekizinci sınıf öğrencilerinin matematik başarılarını etkileyen faktörlerin çok düzeyli yapısal eşitlik modeliyle incelenmesi [Investigation of the factors affecting mathematics achievement of TIMSS 2011 eighth grade students with multilevel structural equation modeling] [Unpublished master's dissertation]. Hacettepe Üniversitesi. https://tez.yok.gov.tr/UlusalTezMerkezi/
  • Ertürk, Z., & Erdinç-Akan, O. (2018a). TIMSS 2015 matematik başarısını etkileyen değişkenlerin yapısal eşitlik modeli ile incelenmesi [The Investigation of the Variables Effecting TIMSS 2015 Mathematics Achievement with SEM]. Ulusal Eğitim Akademisi Dergisi (UEAD), 2(2), 14-34. https://doi.org/10.32960/uead.407078
  • Ertürk, Z., & Erdinç-Akan, O. (2018b). TIMSS 2015 matematik başarısı ile ilgili bazı değişkenlerin cinsiyete göre ölçme değişmezliğinin incelenmesi [The Investigation of Measurement Invariance of the Variables Related to TIMSS 2015 Mathematics Achievement in terms of Gender]. Kuramsal Eğitimbilim Dergisi [Journal of Theoretical Educational Science], UBEK-2018, 204-226. https://doi.org/10.30831/akukeg.412604
  • Fraenkel, J. R., & Wallen, N.E. (2006). How to design and evaluate research in education. McGraw-Hill.
  • French, B. F., & Finch, W. H. (2006). Confirmatory factor analytic procedures for the determination of measurement ınvariance. Structural Equation Modeling: A Multidisciplinary Journal, 13(3), 378–402. https://doi.org/10.1207/s15328007sem1303_3
  • Gregorich, S. E. (2006). Do self-report instruments allow meaningful comparisons across diverse population groups?: Testing measurement invariance using the confirmatory factor analysis framework. Medical Care, 44(11), 78-94. https://doi.org/10.1097/01.mlr.0000245454.12228.8f
  • Gungor, M., & Atalay-Kabasakal, K. (2020). Investigation of measurement ınvariance of science motivation and self-efficacy model: PISA 2015 Turkey sample. International Journal of Assessment Tools in Education, 7 (2), 207-222. https://doi.org/10.21449/ijate.730481
  • Gülleroğlu, H. D. (2017). PISA 2012 matematik uygulamasına katılan Türk öğrencilerin duyuşsal özeliklerinin cinsiyete göre ölçme değişmezliğinin incelenmesi [An investigation of measurement invariance by gender for the Turkish students’ affective characteristics who took the PISA 2012 math test]. Gazi Eğitim Fakültesi Dergisi, 37(1), 151-175.
  • Hair Jr, J. F., Black, C. W., Babin, B. J., & Anderson, R. E. (2014). Multivariate data analysis (7th ed.). Pearson Education.
  • Hanci, A. (2015). 8. sınıf öğrencilerinin öğrenme stilleri ve TIMSS matematik başarılarının farklı değişkenler açısından incelenmesi: Bayburt ili örneği [Investigation of 8th grade students' learning styles and TIMSS matematics achivements from the aspect of different variable: Bayburt sample] [Unpublished master's dissertation]. Bayburt Üniversitesi. https://tez.yok.gov.tr/UlusalTezMerkezi/
  • Harrington, D. (2009). Confirmatory factor analysis. Oxforda University Press, Inc.
  • Işlak, O. (2020). TIMSS 2015 uygulamasına katılan öğrencilerin matematik başarılarının öğrenci, aile ve okul değişkenlerine göre yordanma [Prediction of mathematics achievement of students attending TIMSS 2015 according to student, family and school variables] [Unpublished doctoral dissertation]. Burdur Mehmet Akif Ersoy Üniversitesi. https://tez.yok.gov.tr/UlusalTezMerkezi/
  • İlhan, M., & Öner-Sünkür, M. (2012). Matematik kaygısı ile olumlu ve olumsuz mükemmeliyetçiliğin matematik başarısını yordama gücü [The predictive power of mathematics anxiety and positive and negative perfectionism on math achievement]. Mersin Üniversitesi Eğitim Fakültesi Dergisi, 8(1), 178-188.
  • Jorgensen, T. D., Pornprasertmanit, S., Schoemann, A. M., & Rosseel, Y. (2021). semTools: Useful tools for structural equation modeling. R package version 0.5-5. Retrieved from https://CRAN.R-project.org/package=semTools
  • Jung, J. Y. (2019). A Comparison of CFA and ESEM approaches using TIMSS science attitudes items: Evidence from factor structure and measurement invariance [Unpublished master's dissertation]. Purdue University.
  • Karakoc-Alatli, B., Ayan, C., Polat-Demir, B., & Uzun, G. (2016). Examination of the TIMSS 2011 fourth grade mathematics test in terms of cross-cultural measurement invariance. Eurasian Journal of Educational Research, 66, 389-406. https://doi.org/10.14689/ejer.2016.66.22
  • Karasar, N (2011). Bilimsel Araştırma Yöntemi [Scientific Research Method]. Nobel Yayıncılık.
  • Kesici, A. (2018). Lise öğrencilerinin matematik motivasyonunun matematik başarısına etkisinin incelenmesi. OMÜ Eğitim Fakültesi Dergisi, 37(2), 177-194. https://doi.org/10.7822/omuefd.438550
  • Kesici, A., & Aşılıoğlu, B. (2017). Ortaokul öğrencilerinin matematiğe yönelik duyuşsal özellikleri ile temel eğitimden ortaöğretime geçiş (TEOG) sınavları öncesi yaşadıkları stresin matematik başarısına etkisi [The Effect of Secondary Students' Affective Features Towards Mathematics and The Stress They Experience Before The TEOG Exam (The Exam For Accessing to Various Types of High Schools) on Their Mathematical Success]. Kırşehir Eğitim Fakültesi Dergisi, 18(3), 394-414.
  • Khine, M. S., Al-Mutawah, M., & Afari, E. (2015). Determinants of affective factors in mathematics achievement: Structural equation modeling approach. Journal of Studies in Education, 5(2), 199–211.
  • Kıbrıslıoğlu, N. (2015). PISA 2012 matematik öğrenme modelinin kültürlere ve cinsiyete göre ölçme değişmezliğinin incelenmesi: Türkiye – Çin (Şangay) – Endonezya örneği [The investigation of measurement invariance PISA 2012 mathematics learning model according to culture and gender: Turkey - China (Shangai) - Indonesia] [Unpublished master's dissertation]. Hacettepe Üniversitesi. https://tez.yok.gov.tr/UlusalTezMerkezi/
  • Kilic, S. & Askin, Ö. E. (2013). Parental influence on students’ mathematics achievement: the comparative study of Turkey and best performer countries in TIMSS 2011. Procedia - Social and Behavioral Sciences, 106, 2000-2007. https://doi.org/10.1016/j.sbspro.2013.12.228
  • Kline, R. B. (2015). Principles and practices of structural equation modeling (4th ed.). The Guilford Press.
  • Koç, O. (2019). 4. ve 8. sınıf öğrencilerinin TIMSS 2015 matematik başarısını yordayan değişkenlerin belirlenmesi [Determination of predictive variables of 4th and 8th grade students' on TIMSS 2015 mathematics achievement] [Unpublished master's dissertation]. Akdeniz Üniversitesi. https://tez.yok.gov.tr/UlusalTezMerkezi/
  • Lay, Y. F., Ng, K. T., & Chong, P. S. (2015). Analyzing affective factors related to eighth grade learners’ science and mathematics achievement in TIMSS 2007. Asia-Pacific Education Researcher, 24(1), 103–110. https://doi.org/10.1007/s40299-013-0163-0
  • Louis, R.A., & Mistele, J.M. (2012). The differences in scores and self-efficacy by student gender in mathematics and science. International Journal of Science and Mathematics Education, 10, 1163–1190. https://doi.org/10.1007/s10763-011-9325-9
  • Ma, Y., & Qin, X. (2021). Measurement invariance of information, communication and technology (ICT) engagement and its relationship with student academic literacy: Evidence from PISA 2018. Studies in Educational Evaluation, 68, 1–15. https://doi.org/10.1016/j.stueduc.2021.100982
  • Meade, A. W., Johnson, E. C., & Braddy, P. W. (2008). Power and sensitivity of alternative fit indices in tests of measurement invariance. Journal of Applied Psychology, 93(3), 568–592. https://doi.org/10.1037/0021-9010.93.3.568
  • Ministry of National Education (MoNE) (2020). TIMSS 2019 Türkiye ön raporu [TIMSS 2019 Turkey preliminary report]. Ankara: Ölçme, Değerlendirme ve Sınav Hizmetleri Genel Müdürlüğü.
  • Ministry of National Education (MoNE). (2016). TIMSS 2015 ulusal matematik ve fen ön raporu: 4. ve 8. sınıflar [TIMSS 2015 national math and science preliminary report: 4th and 8th grades]. Ankara.
  • Meng, L., Qiu, C., & Boyd-Wilson, B. (2019). Measurement invariance of the ICT engagement construct and its association with students’ performance in China and Germany: Evidence from PISA 2015 data. British Journal of Educational Technology, 50(6), 3233–3251. https://doi.org/10.1111/bjet.12729
  • Millsap, R. E., & Olivera-Aguilar, M. (2012). Investigating measurement invariance using confirmatory factor analysis. In R. H. Hoyle (Ed.), Handbook of structural equation modeling (pp. 380–392). The Guilford Press.
  • Mindrila, D. (2010). Maximum likelihood (ML) and diagonally weighted least squares (DWLS) estimation procedures: A comparison of estimation bias with ordinal and multivariate non-normal data. International Journal of Digital Society, 1(1), 60–66. https://doi.org/10.20533/ijds.2040.2570.2010.0010
  • Mohammadpour, E. (2012). Factors accounting for mathematics achievement of singaporean eighth-graders. The Asia-Pacific Education Researcher, 21(3), 507-518.
  • Mulaik, S. A. (2007). There is a place for approximate fit in structural equation modelling. Personality and Individual Differences, 42(5), 883-891. https://doi.org/10.1016/j.paid.2006.10.024
  • Mullis, I. V. S., Martin, M. O., Foy, P., & Hooper, M. (2016). TIMSS 2015 international results in mathematics. Boston, US.
  • Oral, I., & McGivney, E. (2013). Türkiye’de matematik ve fen bilimleri alanlarında öğrenci performansı ve başarının belirleyicileri: TIMSS 2011 analizi [Student performance and determinants of success in mathematics and science in Turkey: TIMSS 2011 analysis]. İstanbul: Eğitim Reformu Girişimi Raporu.
  • Öğretmen, T. (2006). Uluslararası okuma becerilerinde gelişim projesi (PIRLS) 2001 testinin psikometrik özelliklerinin incelenmesi: Türkiye-Amerika Birleşik Devletleri örneği [The investigation of psychometric properties of the test of progress in international reading literacy (PIRLS) 2001: The model of Turkey-United States of America] [Unpublished doctoral dissertation]. Hacettepe Üniversitesi. https://tez.yok.gov.tr/UlusalTezMerkezi/
  • Ölçüoğlu, R., & Çetin, S. (2016). TIMSS 2011 sekizinci sınıf öğrencilerinin matematik başarısını etkileyen değişkenlerinin bölgelere göre incelenmesi [The investigation of the variables that affecting eight grade students’ TIMSS 2011 math achievement according to regions]. Eğitimde ve Psikolojide Ölçme ve Değerlendirme Dergisi, 7(1), 202-220. https://doi.org/10.21031/epod.34424
  • Öncü, Ö. (2019). TIMSS 2015 sekizinci sınıf matematik başarı testinin oecd ülkelerine göre ölçme değişmezliğinin incelenmesi [An investication into the measurement invariance according to OECD countries of TIMSS 2015 eight grade math achievement test] [Unpublished master's dissertation]. Akdeniz Üniversitesi. https://tez.yok.gov.tr/UlusalTezMerkezi/
  • Patterson, M., Perry, E., Decker, C., Eckert, R., Klaus, S., Wendling, L., & Papanastasiou, E. (2003). Factors associated with high school mathematics performance in the United States. Studies in Educational Evaluation, 29(2), 91-108. https://doi.org/10.1016/S0191-491X(03)00017-8
  • Pituch, K. A., & Stevens, J. P. (2016). Applied multivariate statistics for the social sciences: Analyses with SAS and IBM’s SPSS (6th Ed.). Routledge.
  • Polat, M. (2019). TIMSS-2015 matematik ve fen duyuşsal özellik modellerinin kültürlere, cinsiyete ve bölgelere göre ölçme değişmezliğinin incelenmesi [The investigation of measurement invariance of TIMSS-2015 mathematics and science affective characteristics models according to culture, gender and statistical region] [Unpublished master's dissertation]. Hacettepe Üniversitesi. https://tez.yok.gov.tr/UlusalTezMerkezi/
  • Raykov, T., & Marcoulides, G. A. (2006). A first course in structural equation modeling (2nd ed.). Lawrence Erlbaum Associates, Publishers.
  • Rosseel, Y. (2012). lavaan: An R package for structural equation modeling. Journal of Statistical Software, 48(2), 1–36. https://doi.org/10.18637/jss.v048.i02
  • Rutkowski, D., & Rutkowski, L. (2013). Measuring socioeconomic background in PISA: One size might not fit all. Research in Comparative and International Education, 8(3), 259–278. https://doi.org/10.2304/rcie.2013.8.3.259
  • Salzberger, T., Sinkovics, R., R., & Schlegelmilch, B. B. (1999). Data equivalence in cross-cultural research: a comparison of classical test theory and latent trait theory based approaches. Australasian Marketing Journal, 7(2), 23-38. https://doi.org/10.1016/S1441-3582(99)70213-2
  • Sarı, M. H., & Ekici, G. (2018). İlkokul 4. sınıf öğrencilerinin matematik başarıları ile aritmetik performanslarını etkileyen duyuşsal değişkenlerin belirlenmesi [Determination of affective variables affecting mathematical achievement and arithmetic performance of primary school 4th grade students]. OPUS International Journal of Society Researches, 8(15), 1562-1594. https://doi.org/10.26466/opus.451025
  • Sarı, M. H., Arıkan, S., & Yıldızlı, H. (2017). 8. sınıf matematik akademik başarısını yordayan faktörler-TIMSS 2015 [Factors predicting mathematics achievement of 8th graders in TIMSS 2015 ]. Eğitimde ve Psikolojide Ölçme ve Değerlendirme Dergisi, 8(3), 246-265.
  • Sarıer, Y. (2020). TIMSS uygulamalarında Türkiye’nin performansı ve akademik başarıyı yordayan değişkenler [Turkey's performance in TIMSS applications and variables predicting academic achievement]. Temel Eğitim Dergisi, 2(2), 6-27.
  • Scherer, R., Nilsen, T., & Jansen, M. (2016). Evaluating individual students’ perceptions of instructional quality: An investigation of their factor structure, measurement invariance, and relations to educational outcomes. Frontiers in Psychology, 7(110), 1-16. https://doi.org/10.3389/fpsyg.2016.00110
  • Schumacker, R. E., & Beyerlein, S. T. (2000). Confirmatory factor analysis with different correlation types and estimation methods. Structural Equation Modeling, 7(4), 629–636. https://doi.org/10.1207/S15328007SEM0704_6
  • Shukla, K., & Konold, T. (2014). Fondness of math and science as measured by the TIMSS student questionnaire: Invariance across U.S. ethnic groups. Paper presented at the 2014 Annual Meeting of the American Educational Research Association, Philadelphia, USA
  • Stark, S., Chernyshenko, O. S., & Drasgow, F. (2006). Detecting differential item functioning with comfirmatory factor analysis and ıtem response theory: Toward a unified strategy. Journal of Applied Psychology, 91(6), 1292–1306. https://doi.org/10.1037/0021-9010.91.6.1292
  • Tabachnick, B. G., & Fidell, L. S. (2013). Using multivariate statistics (6th ed.). Pearson Education.
  • Tavlıca, A. (2019). TIMSS 2015 dördüncü sınıf matematik testinin ölçme değişmezliğinin ülkelere göre incelemesi [An investigation of measurement invariance for TIMSS 2015 fourth grade mathematics test according to countries] [Unpublished master's dissertation]. Akdeniz Üniversitesi. https://tez.yok.gov.tr/UlusalTezMerkezi/
  • Usta, H. G., & Demirtaşlı, R. N. (2018). PISA 2012 matematik okuryazarlığı üzerine uluslararası bir karşılaştırma: Türkiye ve Finlandiya [An international comparison according to PISA 2012 mathematical literacy Turkey and Finland]. Turkish Studies (Elektronik), 13(11), 1389 - 1420. https://doi.org/10.7827/TurkishStudies.13377
  • Uyar, S. (2021). Factor structure and measurement invariance of the TIMSS 2015 mathematics attitude questionnaire: Exploratory structural equation modelling approach. International Journal of Assessment Tools in Education, 8(4), 855–871. https://doi.org/10.21449/ijate.796862
  • Uzun, B., & Öğretmen, T. (2010). Fen başarısı ile ilgili bazı değişkenlerin TIMSS-R Türkiye örnekleminde cinsiyete göre ölçme değişmezliğinin değerlendirilmesi [Assessing the measurement ınvariance of factors that are related to students’ science achievement across gender in TIMSS-R Turkey sample]. Eğitim ve Bilim, 35(155), 26–35.
  • Vandenberg, R. J., & Lance, C. E. (2000). A review and synthesis of the MI literature: Suggestions, practices, and recommendations for organizational research. Organizational Research Methods, 3(1), 4–69. https://doi.org/10.1177/109442810031002
  • Wang, Z., Osterlind, S., & Bergin, D. A. (2012). Building mathematics achievement models in four countries using TIMSS 2003. International Journal of Science and Mathematics Education, 10(5), 1-28. https://doi.org/10.1007/s10763-011-9328-6
  • Webster, B. J., & Fisher, D. L. (2000). Accounting for variation in science and mathematics achievement: A multilevel analysis of Australian data third international mathematics and science study (TIMSS). School Effectiveness and School Improvement, 11(3), 339–360. https://doi.org/10.1076/0924-3453(200009)11:3;1-G;FT339
  • Wicherts, J. M. (2007). Group differences in intelligence test performance [Unpublished doctoral dissertation]. University of Amsterdam.
  • Widaman, K. F., & Reise, S. P. (1997). Exploring the measurement invariance of psychological instruments: Applications in the substance use domain. In K. J. Bryant, M. Windle, & S. G. West (Eds.), The science of prevention: Methodological advances from alcohol and substance abuse research (pp. 281–324). American Psychological Association.
  • Wu, A.D., Li, Z., & Zumbo, B.D. (2007). Decoding the meaning of factorial invariance and updating the practice of multi-group confirmatory factor analysis: A demonstration with TIMSS data. Practical Assessment, Research and Evaluation, 12, 1-26. https://doi.org/10.7275/mhqa-cd89
  • Yandı, A., Köse, İ. A., & Uysal, Ö. (2017). Farklı yöntemlerle ölçme değişmezliğinin incelenmesi: PISA 2012 örneği [Examining measurement invariance with different methods: Example of PISA 2012]. Mersin Üniversitesi Eğitim Bilimleri Dergisi, 13(1), 243-253. https://doi.org/10.17860/mersinefd.305952
  • Yin, L., & Fishbein, B. (2020). Creating and interpreting the TIMSS 2019 context questionnaire scales. In M. O. Martin, M. von Davier, & I. V. S. Mullis (Eds.), Methods and procedures: TIMSS 2019 technical report (pp. 16.1-16.331). Boston College, TIMSS & PIRLS International Study Center. https://timssandpirls.bc.edu/timss2019/methods/chapter-16.html
  • Yücel, Z., & Koç, M. (2011). İlköğretim öğrencilerinin matematik dersine karşı tutumlarının başarı düzeylerini yordama gücü ile cinsiyet arasındaki ilişki [The relationship between the prediction level of elementary school students’ math achievement by their math attitudes and gender]. İlköğretim Online, 10(1), 133-143.
There are 88 citations in total.

Details

Primary Language English
Journal Section Articles
Authors

Mehmet Atılgan 0000-0003-1297-4630

Kaan Zulfikar Deniz 0000-0003-0920-538X

Publication Date September 30, 2023
Acceptance Date September 7, 2023
Published in Issue Year 2023 Volume: 14 Issue: 3

Cite

APA Atılgan, M., & Deniz, K. Z. (2023). Investigation of The Measurement Invariance of Affective Characteristics Related to TIMSS 2019 Mathematics Achievement by Gender. Journal of Measurement and Evaluation in Education and Psychology, 14(3), 185-199. https://doi.org/10.21031/epod.1221365