International Association of Educators   |  ISSN: 2834-7919   |  e-ISSN: 1554-5210

Original article | International Journal of Progressive Education 2020, Vol. 16(2) 205-217

Identification of Differential Item Functioning on Mathematics Achievement According to the Interactions of Gender and Affective Characteristics By Rasch Tree Method

Münevver Başman & Ömer Kutlu

pp. 205 - 217   |  DOI: https://doi.org/10.29329/ijpe.2020.241.14   |  Manu. Number: MANU-1909-02-0002

Published online: April 02, 2020  |   Number of Views: 280  |  Number of Download: 879


Abstract

Mathematical knowledge and skills are needed to find solutions to the problems encountered in daily life. Although individuals are given the opportunity to receive equal education, it is seen that there are differences in the achievement of individuals. Individual-based factors can affect the achievement of individuals. One of the most important of these individual-based factors is the gender factor. It is important to examine the reasons behind the items of mathematics test showing the Differential Item Functioning (DIF) by gender. In this research, the interaction of gender and intrinsic motivation, instrumental motivation, self-efficacy, and anxiety variables on mathematics test items was examined in terms of DIF to understand the reasons of gender differences in the mathematical achievement of students who participated in PISA 2012. The study group of this research constituted 1084 students who participated in the application in Turkey, who answered booklets 3, 5 and 11 in the PISA 2012 mathematics literacy test. The data was analyzed by Iterative Hybrid Ordinal Logistic Regression (IHOLR) in the Lordif package program and Rasch Tree Method (RTM) in Psychotree package program and items showing DIF according to gender were determined. According to the findings, some mathematics test items showed DIF according to gender. It was found that items also showed DIF according to gender and intrinsic motivation interaction, and gender and self-efficacy interaction. It was observed that status of items showing DIF changed according to a certain threshold value of the girls' intrinsic motivation and self-efficacy score. It was found that mathematics items did not show DIF according to gender and instrumental motivation interaction, and gender and anxiety interaction. As a result, it was observed that status of items showing DIF according to gender could change according to gender and affective characteristics interaction.

Keywords: Differential Item Functioning, Mathematical Literacy, PISA, Rasch Tree Method


How to Cite this Article?

APA 6th edition
Basman, M. & Kutlu, O. (2020). Identification of Differential Item Functioning on Mathematics Achievement According to the Interactions of Gender and Affective Characteristics By Rasch Tree Method . International Journal of Progressive Education, 16(2), 205-217. doi: 10.29329/ijpe.2020.241.14

Harvard
Basman, M. and Kutlu, O. (2020). Identification of Differential Item Functioning on Mathematics Achievement According to the Interactions of Gender and Affective Characteristics By Rasch Tree Method . International Journal of Progressive Education, 16(2), pp. 205-217.

Chicago 16th edition
Basman, Munevver and Omer Kutlu (2020). "Identification of Differential Item Functioning on Mathematics Achievement According to the Interactions of Gender and Affective Characteristics By Rasch Tree Method ". International Journal of Progressive Education 16 (2):205-217. doi:10.29329/ijpe.2020.241.14.

References
  1. Bell, R. C., & Hay, J. A. (1987). Differences and biases in English language examination formats. British Journal of Educational Psychology, 57, 212-220. [Google Scholar]
  2. Ben-shakar, G., & Sinai, Y. (1991). Gender differences in multiple-choice tests: the role of differential guessing tendencies. Journal of Educational Measurement, 28, 77-92. [Google Scholar]
  3. Bolger, N., & Kellaghan, T. (1990). Method of measurement and gender differences in scholastic achievement. Journal of Educational Measurement, 27, 165-174.  [Google Scholar]
  4. DeMars, C. E. (2000). Test stakes and item format interactions. Applied Measurement in Education, 13(1), 55-77. [Google Scholar]
  5. Eid, G. K. (2002). Gender, ethnicity, and language influences on differential item functioning in the SAT. Unpublished Ph.D. thesis, Ohio University, United States. [Google Scholar]
  6. Ellis, B. B., & Raju, N. S. (2003). Test and item bias: What they are, what they aren’t, and how to detect them. Educational Resources information center (ERIC). [Google Scholar]
  7. ERI. (2014). Türkiye PISA2012 analizi: Matematikte öğrenci motivasyonu, özyeterlik, kaygı ve başarısızlık algısı. Eğitim Reformu Girişimi, Araştırma Notu, Sabancı Üniversitesi. [Google Scholar]
  8. Garner, M., & Engelhard, G. (2009). Gender differences in performance on multiple-choice and constructed response mathematics items. Applied measurement in education, 12(1), 29-51. [Google Scholar]
  9. Gipps, C., & Murphy, P. (1994). A fair test: Assessment, achievement and equity. Buckingham: Open University Press. [Google Scholar]
  10. Hanna, G. (1986). Sex differences in the mathematics achievement of eighth graders in Ontario. Journal for Research in Mathematics Education, 17, 231-237. [Google Scholar]
  11. Jodoin, M. G., & Gierl, M. J. (2001). Evaluating type I error and power rates using an effect size measure with the logistic regression procedure for DIF detection. Applied Measurement in Education, 14, 329-349. [Google Scholar]
  12. Karasar, N. (2010). Bilimsel araştırma yöntemleri. 21. Baskı. Ankara: Nobel Yayın Dağıtım. [Google Scholar]
  13. Kopf, J. (2013). Model-based recursive partitioning meets item response theory: New statistical methods for the detection of differential item functioning and appropriate anchor selection. Unpublished doctoral dissertation, LMU München: Faculty of Mathematics, Computer Science and Statistics. [Google Scholar]
  14. Lane, S., Wang, N., & Magone, M. (1996). Gender-related differential item functioning on a middle-school mathematics performance assessment. Educational Measurement: Issues and Practice, 15(4), 21-27, 31. [Google Scholar]
  15. Liu, O. L., & Wilson, M. (2009a) Gender differences and similarities in PISA 2003 mathematics: A comparison between the United States and Hong Kong. International Journal of Testing, 9(1), 20-40. [Google Scholar]
  16. Liu, O. L., & Wilson, M. (2009b). Gender differences in large scale math [Google Scholar]
  17. assessments: PISA trend 2000 and 2003. Applied Measurement in [Google Scholar]
  18. Education, 22, 164-184. [Google Scholar]
  19. MEB. (2015). PISA 2012 araştırması ulusal nihai rapor. Milli Eğitim Bakanlığı, Ölçme, Değerlendirme ve Sınav Hizmetleri Genel Müdürlüğü. Ankara: İŞKUR Matbaacılık. [Google Scholar]
  20. National Council of Teachers of Mathematics. (1995). Assessment Standards for School Mathematics. Reston, VA: NCTM. [Google Scholar]
  21. OECD. (2000). Knowledge and Skills for Life: First Results from PISA 2000. OECD Publishing.  [Google Scholar]
  22. OECD. (2004). Learning for Tomorrow’s World: First results from PISA 2003. OECD Publishing. [Google Scholar]
  23. OECD. (2014) PISA 2012 results: what students know and can do—student performance in mathematics, reading and science, vol. I, OECD Publishing. [Google Scholar]
  24. OECD. (2015). The ABC of Gender Equality in Education: Aptitude, Behaviour, Confidence, OECD Publishing. [Google Scholar]
  25. OECD. (2016). Data base PISA-2012. Retrieved from Web: https://www.oecd.org/pisa/pisaproducts/pisa2012database-downloadabledata.htm [Google Scholar]
  26. Simpkins, S. D., Fredricks, J., Eccles, J. S., & Simpkins-Chaput, S. (2012). Charting the Eccles’ Expectancy-Value Model from parents’ beliefs in childhood to youths’ activities in adolescence. Developmental Psychology, 48, 1019-1032. [Google Scholar]
  27. Strobl, C., Kopf, J., & Zeileis, A. (2015). Rasch trees: A new method for detecting differential item functioning in the Rasch model. Psychometrika, 80(2), 289-316. [Google Scholar]
  28. Vi-Nhuan, L. (1999). Identifying Differential item functioning on the NELS:88 History Achievement Tests. CSE Technical Report 511. Stanford University, CA: National Center for Research & Evaluation. [Google Scholar]
  29. Zimmerman, B. J. (2000). Self-efficacy: An essential motive to learn. Contemporary Educational Psychology, 25, 82-91. [Google Scholar]