An Application of Cognitive Diagnosis Modeling in TIMSS: A Comparison of Intuitive Definitions of Q-Matrices

Derya Evran

Abstract


Detection of students’ ability levels is one of the common aims in educational studies. Cognitive Diagnosis Modeling approach has been used recently for the purpose of ability level detection by defined Q-matrices. This paper aims to use Cognitive Diagnosis Modeling (CDM) in order to investigate the definition of a Q-matrix across the cognitive skills of different years and countries in TIMSS. There is a subjective way in defining Q-matrices; for this purpose, an application of building Q-matrices under specific CDMs, from a set of expert proposed attributes is examined. The proposed attributes are used to build Q-matrices for TIMSS mathematics questions across its cycles, and across different nations.

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References


American Federation of Teachers (AFT). (1999). What TIMSS tells us about mathematics achievement, curriculum, and instruction. In Educational Issues Policy Brief, 10, 2-10.Washington, DC: AFT Educational Issues Department.

Birenbaum, M., Nasser, F., & Tatsuoka, C. (2007). Effects of gender and ethnicity on fourth graders’ knowledge states in mathematics. International Journal of Mathematical Education in Science and Technology, 38, 301-319.

Birenbaum, M., Tatsuoka, C., & Yamada, T. (2004). Diagnostic assessment in TIMSS-R: Between countries and within-country comparisons of eighth graders’ mathematics performance. Studies in Educational Evaluation, 30, 151-173.

Chen, Y., Thompson, M., Gorin, J. S., & Tatsuoka K. K. (2008). Cross-Cultural validity of the TIMSS-1999 mathematics test: Verification of a Cognitive Model. International Journal of Testing, 8, 251-271.

de la Torre, J. (2008). An empirically-based method of Q-matrix validation for the DINA model: Development and applications. Journal of Educational Measurement, 45, 343-362.

de la Torre, J. (2009). DINA model and parameter estimation: A didactic. Journal of Educational and Behavioral Statistics, 34, 115-130.

de la Torre, J. (2011). The generalized DINA model framework. Psychometrika, 76, 179-199.

Dogan, E., & Tatsuoka, K. K. (2008). An international comparison using a diagnostic testing model: Turkish students’ profile of mathematical skills on TIMSS-R. Educational Studies in Mathematics, 68, 263-272.

Doornik, J. A. (2002). Object-Oriented Matrix Programming Using Ox (Version 3.1) [Computer software]. London: Timberlake Consultants Press.

Foy, P., & Olson, J. F. (2009). TIMSS 2007 user guide for the international database. Chestnut Hill, MA: IEA.

Haertel, E. H. (1989). Using restricted latent class models to map the skill structure of achievement items. Journal of Educational Measurement, 26, 333-352.

Hambleton, R. K. (2005). Issues, designs, and technical guidelines for adapting tests in multiple languages. In R. K. Hambleton, P. Merenda, & C. D. Spielberger (Eds.). Hillsdale, NJ: Lawrence Erlbaum.

Junker, B.W., & Sijtsma, K. (2001). Cognitive assessment models with few assumptions, and connections with nonparametric item response theory. Applied Psychological Measurement, 25, 258–272.

Lee, Park, & Taylan (2011). Cognitive diagnostic modeling of attribute mastery in Massachusetts, Minnesota, and the U.S. national sample using the TIMSS 2007. International Journal of Testing, 11, 144-177.

Olson, J. F., Martin,M. O., & Mullis, I. V. S. (2009). TIMSS 2007 technical report. Chestnut Hill, MA: IEA.

Tatsuoka, K. K. (1983). Rule-space: An approach for dealing with misconceptions based on item response theory. Journal of Educational Measurement, 20, 345-354.

Mullis, I.V.S., Martin, M.O., Foy, P., & Arora, A. (2012). TIMSS 2011 International Results in Mathematics. Chestnut Hill, MA: IEA.




DOI: https://doi.org/10.51383/ijonmes.2019.33

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