Statistics
| Number of Journals | 22 |
| Number of Issues | 501 |
| Number of Articles | 5,252 |
| Article View | 9,906,545 |
| PDF Download | 6,602,423 |
Investigating the Dimensional-Factorial Structure of Cognitive Abilities of the 9th Grade Students | ||
| راهبردهای شناختی در یادگیری | ||
| Article 5, Volume 7, Issue 13, 2020, Pages 91-118 PDF (985.75 K) | ||
| Document Type: Research Article | ||
| DOI: 10.22084/j.psychogy.2019.17145.1823 | ||
| Authors | ||
| Mohsen Yazdanfar* 1; Manijeh Shehni Yailagh2; Ali Reza Haji Yakhchali3; Sirous Alipour Birigani4 | ||
| 1Ph.D student in Educational Psychology, Shahid Chamran University of Ahvaz, Ahvaz, Iran. | ||
| 2Professor in Educational Psychology, Shahid Chamran University of Ahvaz, Ahvaz, Iran. | ||
| 3Assistant Professor in Educational Psychology, Shahid Chamran University of Ahvaz, Ahvaz, Iran. | ||
| 4Associate Professor in Educational Psychology, Shahid Chamran University of Ahvaz, Ahvaz, Iran. | ||
| Abstract | ||
| Objective: Investigating the dimensional-factorial structure of cognitive abilities is an important issue for measuring, interfering and developing these abilities as evidence of its structure's validity from the aspects of content and cognitive processes. This research was conducted with the aim of investigating the dimensional-factorial structure of cognitive abilities and providing a model for this structure in comparison with the presented structures of cognitive abilities such as general intelligence theory (factor g). Method: The research method was descriptive-analytic and modeling the relationship between items and responses. The sample size of the study consisted of 1105 ninth grade students (578 boys and 527 girls) selected by stratified random sampling from among 32 high schools in Ahwaz. Data analysis was performed using cluster analysis methods based on the conditional covariance proximity (HAC/CCPROX) and PolyDETECT, Structural Equation Modeling (SEM) and Monte Carlo simulation. Results: The results of the analysis showed that the structure of cognitive abilities of students is two-dimensional. The first dimension was named non-social cognition and includes six factors namely retrospective memory, prospective memory, inhibitory control, decision-making, planning, and sustain attention. The second dimension was called social cognition, which included only social cognition factor. Also, the validity and reliability of the dimensions and the obtained factors were confirmed. Discussion and Conclusion: The results of this study showed that the unidimensional theory of general intelligence (factor g) is not a complete theory for the structure of cognitive abilities and the factor g can not explain the variance of social cognition. Thus, the theory underlying the present study was called "Thetwo dimensionaltheory of social-nonsocialcognitive abilities". Also, the results of this study confirmed the findings of some studies that non-social cognition and social cognition form two different dimensions of cognitive abilities. | ||
| Keywords | ||
| The two dimensional theory of social-nonsocial cognitive abilities; Two-dimensional scale of social-nonsocial cognitive abilities; dimensionality; mathematical performance; hierarchical cluster analysis; Monte Carlo simulation; PolyDETECT index | ||
| References | ||
|
صفرخانی، مریم و کیامنش، علیرضا. (1394). «بررسی روند عملکرد ریاضی دانشآموزان پایه هشتم در فاصله زمانی معادل 1390-1374». فصلنامه اندازهگیری تربیتی، 19(5)، 1-24. نجاتی، وحید. (1392). «پرسشنامه تواناییهای شناختی: طراحی و بررسی خصوصیات روانسنجی». فصلنامه تازههای علوم شناختی، 15(2)، 11-19. Alloway, T. P., & Passolunghi, M. C. (2011). “The relationship between working memory, IQ, and mathematical skills in children”. Learning and Individual Differences, 21, 133-137.
Ashkenazi, S., Rosenberg-Lee, M., Metcalfe, A. W. S., Swigart, A. G., & Menon, V. (2013). “Visual-spatial working memory is an important source of domain-general vulnerability in the development of arithmetic cognition”. Neuropsychologia, 51, 2305-2317.
Balkemore, S. J., & Mills, K. L. (2014). “Is adolescence a sensitive period for sociocultural processing?”. Annual Review of Psychology, 65, 187-207.
Bickley, P. G., Keith, T. Z., & Wolfle, L. M. (1995). “The three-stratum theory of cognitive abilities: Test of the structure of intelligence across the life span”. Intelligence, 20, 309-328.
Bonifay, W. E., Reise, S. P., Scheines, R., & Meijer, R. R. (2015). “When are multidimensional data unidimensional enough for structural equation modeling? An evaluation of the DETECT multidimensionality index”. Structural Equation Modeling, 22, 504-516.
Bulut, O., & Sunbul. O. (2017). “Monte carlo simulation studies in item response theory with the R programming language”. Measurement and Evaluation in Education and Psychology, 8(3), 266-287.
Carroll, J. B. (1992). “Cognitive abilities: The state of the art”. Psychological Science, 3, 266-270.
Carroll, J. B. (1993). Human cognitive abilities: A survey of factor-analytic studies. Cambridge,UK: Cambridge University Press.
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/.
Creswell, J. W. (2012). Educational research: Planning, conducting, and evaluating quantitative and qualitative research (4th. ed.). New York: Edwards Brothers, Inc.
Eysenck, M. W. & Keane, M. T. (2010). Cognitive psychology : A student’s handbook (4th. ed.). USA and Canada: Psychology Press.
Gaemmerer, J. M., Maddocks, D. L. S., Keith, T. S., & Reynolds, M. R. (2018). “Effects of cognitive abilities on child and youth academic achievement: Evidence from the WISC-V and WIAT-III”. Intelligence, 68, 6-20.
Gottfredson, L. S. (1997). “Mainstream science on intelligence: An editorial with 52 signatories, history, and bibliography”. Intelligence, 24, 13-23.
Horn, J. L., & Cattell, R. B. (1966). “Refinement and test of the theory of fluid and crystallized general intelligence”. Journal of Educational Psychology, 57, 253-270.
Horn, J. L. (1991). Measurement of intellectual capabilities: A review of theory. In K. S. McGrew, J. K. Werder, & R.W. Woodcock (Eds.), WJ-R technical manuul. Allen, TX: DLM.
Ismatullina, V., & Voronin, I. (2017). “Individual differences in the relationship between temperament and planning ability in adolescents”. Procedia -Social and Behavioral Sciences, 237, 1455-1461.
Ispas, D., & Borman, W. C. (2015). “Personnel selection, psychology of”. International Encyclopedia of the Social & Behavioral Sciences, 936-940. Retrieved from doi:10.1016/b978-0-08-097086-8.22014-x.
Kerlizer, J. H., & Keith, T. Z. (1999). “Independent confirmatory factor analysis of the cognitive assessment system (CAS): What does the CAS measure?”. School Psychology Review, 28(1), 117-144.
Kihlstrom, J. F. (2010). “Social neuroscience: The footprints of Phineas”. 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.
Naglieri, J. A., & Otero, T. M. (2018). Redefining intelligence with the planning, attention, simultaneous, and successive theory of neurocognitive processes. In D. P. Flanagan & E. M., McDonough (Eds.), Contemporary intellectual assessment theories, tests, and issues (4th. ed.). New York: The Guilford Press.
Nishanimut, S. P., & Padakannaya, P. (2014). “Cognitive Assessment System (CAS): A review”. Psychol Stud. Retrieved from doi: 10.1007/s12646-014-0253-y.
Osburn, H. K., & Mumford, M. D. (2006). “Creativity and planning: Training interventions to develop creative problem-solving skills”. Creativity Research Journal, 18, 173-190.
Pino Escobar, G., Kalashnikova, M., & Escudero, P. (2018). “Vocabulary matters! The relationship between verbal fluency and measures of inhibitory control in monolingual and bilingual children”. Journal of Experimental Child Psychology, 170, 177-189.
Reckase, M. D. (2009). Multidimensional item response theory. New York, NY: Springer.
Reynolds, M. R., & Keith, T. S. (2017). “Multi-group and hierarchical confirmatory factor analysis of the Wechsler Intelligence Scale for Children-Fifth Edition: What does it measure?”. Intelligence, 62, 31-47.
Roussos, L., Stout, W., & Marden, J. (1998). “Using new proximity measures with hierarchical cluster analysis to detect multidimensionality”. Journal of Educational Measurement, 35, 1-30.
Schneider, W. J., & McGrew, K. S. (2018). The Cattell–Horn–Carroll theory of cognitive abilities. In D. P. Flanagan & E. M., McDonough (Eds.), Contemporary intellectual assessment theories, tests, and issues (4th. ed.). New York: The Guilford Press.
Simmons, F. R., Willis C., & Adams A. M. (2012). “Different components of working memory have different relationships with different mathematical skills. Journal of Experimental Child Psychology, 111, 139-155.
Stout, W. F. (1990). “A new item response theory modeling approach with applications to unidimensional assessment and ability estimation”. Psychometrika, 55, 293-326.
Van Abswoude, A. A. H., Van der Ark, L. A., & Sijtsma, K. (2004). “A comparative study on test dimensionality assessment procedures under nonparametric IRT models”. Applied Psychological Measurement, 28, 3-24.
Zhang, J., & Stout, W. (1999). “The theoretical DETECT index of dimensionality and its application to approximate simple structure”. Psychometrika, 64, 213-249.
Zhang, J. (2007). “Conditional covariance theory and DETECT for polytomous items”. Psychometrika, 72, 69-91.
Zhang, J. (2013). “A procedure for dimensionality analyses of response data from various test designs”. Psychometrika, 78, 37-58. | ||
|
Statistics Article View: 741 PDF Download: 619 |
||