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Dimensionality analysis and modeling the structure of cognitive abilities by multidimensional item response theory based on local dependency indices

Document Type : Research Paper

Authors

1 Ph.D student in Educational Psychology, Shahid Chamran University of Ahvaz, Ahvaz, Iran.

2 Professor in Educational Psychology, Shahid Chamran University of Ahvaz

3 Assistant Professor in Educational Psychology, Shahid Chamran University of Ahvaz

4 Associate Professor in Educational Psychology, Shahid Chamran University of Ahvaz

Abstract

Dimensionality analysis or specify the number of latent traits that affect the data from the implementation of a scale or test and the study of local independency and monotonicity assumptions is of the important presuppositions to apply a item response theory model on a set of data. In this research, after a brief explanation of the local dependency indices and its models, In order to modeling the structure of cognitive abilities based on the data obtained from the implementation of the scale of cognitive abilities on a sample of 1105 students from the 9th grade students of Ahwaz selected by proportional stratified random sampling, after examining the hypothesis local independency through local dependency indices, monotonicity hypothesis and estimation of parameters of two one-dimensional and two-dimensional models and their comparison, The dimensionality of cognitive abilities was determined. The results showed that the dependency model observed between the data is perfectly locally dependent and Comparison of fitness indices of one-dimensional and two-dimensional model of Samejima graded response model showed that the two-dimensional model has better fit to the data than the one-dimensional model. In the following, using the concept of dimensionality factor space, a kind of comparison between the two classical test theories (CTT) and multidimensional item response theory (MIRT) was created and a kind of convergence in the results was obtained. The results showed that the fitness indices of classical theory alone were not able to characterize the structure of cognitive abilities, and methods based on item response theory in this field can be solved. The results of dimensionality analysis showed that the structure of cognitive abilities was two-dimensional; the first dimension of non-social cognition and the second dimension of social cognition were named and it was observed that these results converge with the results in the field of neuroscience.

Keywords

References
احمدی ده­قطب­الدینی، محمد.، خدایی، ابراهیم.، فرزاد، ولی الله.، مقدم زاد، علی.، و کبیری، مسعود. (1396). کاربرد مدل دوعاملی چند بُعدی نظریّه سؤال-پاسخ جهت تحلیل بُعدیّت و کارکرد افتراقی سؤال، سؤال­های مبتنی بر متن، فصلنامه اندازه گیری تربیتی، 7 (28)، 153-121.
امبرتسون، سوزان.­ای. و رایس استیون، پی. (2000). نظریّه­های جدید روان­سنجی برای روان­شناسان (IRT). ترجمة حسن­پاشا شریفی، ولی­الله فرزاد، مجتبی حبیبی عسگرآباد و بلال­ایزانلو. (1388). چاپ اوّل، تهران، انتشارات رشد.
ایزانلو، بلال.، بازرگان، عباس.، فرزاد، ولی­الله.، صادقی، ناهید.، و کاووسی، امیر. (1393). تفکیک خوشه­های سؤال از ابعاد متعامد بر اساس هشت روش تعیین بُعد در داده­های دوارزشی: مورد آزمون ریاضی رشته ریاضی فیزیک کنکور 92-91. فصلنامه اندازه گیری تربیتی، 5 (24)، 218-207.
کرلینجر، فردریک نیکلز. (1986). مبانی پژوهش در علوم رفتاری. ترجمة حسن پاشا شریفی و جعفر نجفی زند. (1388). چاپ سوم، تهران: انتشارات آوای نور.
جهانی تابش، عذرا. (1396). شناخت اجتماعی. در خرازی، کمال با همکاری جمعی از استادان، مقدمه­ای بر علوم و فناوری­های شناختی و کاربرد­های آن. (1396). چاپ اوّل. تهران: انتشارات سمت. 192-162.
فرخی، نور علی.، حرفه دوست، منصور.، محمدجانی، هیوا.، جباری، ثریا و رعایی، فرزانه. (1393). ویژگی­های روان­سنجی باورهای کارآمدی در تدریس ریاضی با استفاده از مدل اعتبار پاره­ای تعمیم یافته. فصلنامه اندازه گیری تربیتی، 5 (18)، 157-178.
مینایی، اصغر. (1393). کاربرد مدل اندازه­گیری راش در ارزشیابی ویژگی­های اندازه­گیری آزمون مهارت­های دیداری-حرکتی (TVSM-R). فصلنامه اندازه گیری تربیتی، 5 (18)، 113-77.
نجاتی، وحید. (1392). پرسشنامه توانایی­های شناختی: طراحی و بررسی خصوصیات روانسنجی. فصلنامه تازه­های علوم شناختی، 15 (2)، 19-11.
یونسی، جلیل.، دلاور، علی و فلسفی نژاد، محمد رضا. (1389). بررسی ویژگی­های روان‌سنجی سؤال­های تخصصی آزمون­های فراگیر رشته روانشناسی دانشگاه پیام نور در سال 1385. فصلنامه اندازه گیری تربیتی، 1 (2)، 161-131.
Alloway, T. P. (2009). Working memory, but not IQ, predicts subsequent learning in children with learning difficulties. European Journal of Psychological Assessment, 25, 8-92.
Bishop, Y. M. ML., Fienberg, S. E., & Holland, P. W. (1975). Discrete multivariate analysis.Cambridge, MA: MIT Press.
Bock, R. D., & Aitkin, M. (1981). Marginal maximum likelihood estimation of item parameters: Application of an EM algorithm. Psychometrika, 46(4), 443-459.
Cai, L., Du Toit, S. H. C., & Thissen, D. (2011). IRTPRO: User guide. Lincolnwood, IL: Scientific Software International.
Carroll, J. B. (1993). Human cognitive abilities: A survey of factor-analytic studies. New York: Cambridge University Press.
Chalmers, R. P. (2012). Mirt: A multidimensional item response theory package for the R environment, Journal of Statistical Software, 48(6), 1-29.
Chen, W. H., & Thissen, D. (1997). Local dependence indices for item pairs using item response theory. Journal of Educational and Behavioral Statistics, 22, 265-289.
 Cheng, Y. L. (2016). The dimensionality of cognitive structure: A MIRT approach and the use of subscores. (Doctoral dissertation), Michigan State University. Retrieved from https://etd.lib.msu.edu/.
Edwards, M. C., Houts, C. R., & Cai, L. (2018). A diagnostic procedure to detect departures from local independence in item response theory models. Psychological Methods, 23(1), 138-149.
Gibbons, R. D., & Cai, L. (2018). Dimensionality analysis. In W. J. Van der Linden (Eds.), Handbook of item response theory models.Vol. 3, Published in the Taylor & Francis e-Library.
Hambleton, R. K., Van der Linden, W. J., & Wells, C. S. (2010). IRT models for the analysis of polytomously scored data: Brief and selected history of model building advances. In M. L. Nering & R. Ostini (Eds.), Handbook of polytomous item response theory models. Published in the Taylor & Francis e-Library.
Harris, J., Hirsh-Pasek, K., & Newcombe, N. S. (2013). Understanding spatial transformations: Similarities and differences between mental rotation and mental folding. Cognitive Processing, 14(2), 105-115.
Hubbard, E. M., Piazza, M., Pinel, P., & Dehaene, S. (2005). Interactions between number and space in parietal cortex. Nature Reviews/Neuroscience, 6, 435-448.
Houts, C. R., & Edwards, M. C. (2013). The performance of local dependence measures with psychological data. Applied Psychological Measurement,37, 541-562.
Jiang, S., Wang, C., & Weiss, D. (2016). The sample size requirements for estimation of item parameters in the multidimensional graded response model. Frontiers in Psychology , 7, 109, doi.org/10.3389/fpsyg.2016.00109 .
Kihlstrom, J. F. (2010). Social neuroscience: The footprints of phineas gage. Social Cognition, 28(6), 757-783.
Madrigal, R. (2008). Hot vs. cold cognitions and consumers reactions to sporting event outcomes. Consumer Psychology, 18(4), 304-319.
Maydeu-Olivares, A., & Joe, H. (2005). Limited- and full-information estimation and goodness-of-fit testing in 2n contingency tables. Journal of the American Statistical Association, 100(471), 1009-1020.
Maydeu-Olivares, A., & Joe, H. (2006). Limited information goodness-of-fit testing in multidimensional contingency tables. Psychometrika, 71(4), 713-732.
Maydeu-Olivares, A. (2013). Goodness-of-fit assessment of item response theory models. Measurement, 11, 71-101.
 Mumford, M. D., Schultz, R. A., & Osburn, H. K. (2002). Planning in organizations: Performance as a multi-level phenomenon. In J. Francis & F. Yammarino (Eds.), The many faces of multi-level issues (pp. 3-65). Emerald Group Publishing Limited.
Muraki, E., & Carlson, J. E. (1995). Full-information factor analysis for polytomous item responses. Applied Psychological Measurement, 19(1),73-90.
Naglieri, J. A., & Otero, T. (2011). Cognitive assessment system: Redefining intelligence from a neuropsychological perspective. In A. S. Davis (Eds.), Handbook of Pediatric Neuropsychology (pp. 320-333). Springer Publishing Company.
Otoole, A. J., Jiang, F., Abdi, H., Pénard, N., Dunlop, J. P., & Parent, M. A. (2007). Theoretical, statistical, and practical perspectives on pattern-based classification approaches to the analysis of functional neuroimaging data. Journal of Cognitive Neuroscience, 19(11), 1735-1752.
Pashler, H. (1994). Dual-task interference in simple tasks: Data and theory, PsychologicalBulletin, 116(2), 220.
Reese, L. M. (1995). The impact of local dependencies on some LSAT outcomes (Statistical Report 95-02), Newtown, PA: Law School Admission Council.
Reckase, M. D. (2009). Multidimensional item response theory. New York: Springer.
Reckase, M. D. (2018). Logistic multidimensional models. In W. J. Van der Linden (Eds.), Handbook of Item Response Theory Models,vol.1. Published in the Taylor & Francis e-Library.
Reckase, M. D., & McKinley, R. L. (1991). The discriminating power of items that measure more than one dimension. Applied Psychological Measurement, 15, 361–373.
Reise, S. P., Waller, N. G., & Comrey, A. L. (2000). Factor analysis and scale revision. Psychological Assessment, 12(3), 287-297.
Rindermann, H. (2018). Cognitive capitalism: human capital and the wellbeing of nations, Cambridge, United Kingdom; New York.
Samejima, F. (1969). Estimation of latent ability using a response pattern of graded scores. Psychometrika, Monograph 17, 34.
Samejima, F. (1972). A general model for free-response data. Psychometrika, Monograph 18, 37.
Sen, S., & Bradshaw, L. (2017). Comparison of relative fit indices for diagnostic model selection. Applied Psychological Measurement, 41(6), 422-438.
Sen, S., Cohen, A. S., & Kim, S. H. (2013). A comparison of algorithms for dimensionality analysis. New Developments in Quantitative Psychology, Springer Proceedings in Mathematics & Statistics, 66.
Shaw, P., Greenstein, D., Lerch, J., Clasen, L., Lenroot, R., Gogtay, N., Evans, A., Rapoport, J., & Giedd, J. (2006). Intellectual ability and cortical development in children and adolescents. Nature, 440 (7084), 676-679.
Svetina, D., & Levy, R. (2014). A framework for dimensionality assessment for multidimensional item response models. Educational Assessment, 19, 35-57.
Stout, W. F. (1990). A new item response theory modeling approach with applications to unidimensional assessment and ability estimation. Psychometrika, 55, 293-326.
Tate, R. (2003). A comparison of selected empirical methods for assessing the structure of responses to test items. Applied Psychological Measurement, 27, 159-203.
Tatsuoka, K. K. (1990). Toward an integration of item response theory and cognitive error diagnosis. In N. Frederiksen, R. Glaser, A. Lesgold, & M. G. Shafto (Eds.). Diagnostic monitoring of skill and knowledge acquisition (pp. 453-488). Hillsdale, NJ: Lawrence Erlbaum.
Van der Linden, W. J. (2018). Unidimensional logistic response models. In W. J. Van der Linden (Eds.), Handbook of Item Response Theory Models,Vol.3. Published in the Taylor & Francis e-Library.
Yen, W. M. (1993). Scaling performance assessments: Strategies for managing local item dependence. Journal of Educational Measurement, 30, 187-213.
Yen, W. M. (1984). Effect of local item dependence on the fit and equating performance of the three-parameter logistic model. Applied Psychological Measurement,8, 125-145.
Quarterly of Educational Measurement
Volume 9, Issue 32
July 2018
Pages 163-219
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