Mohammad Hossien Zarghami; Ali Delavar; Mohammsd Reza Falsafinezhad; Fariborz Dortaj; Akram Khoshsokhan
Volume 4, Issue 16 , July 2014, , Pages 1-29
Abstract
The foundation of network data analysis in psychology rests on particular theory, special ontological assumptions and particular methodology. Therefore it is possible to call network analysis as an independent paradigm with given techniques for data gathering and data analysis. This method can be used ...
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The foundation of network data analysis in psychology rests on particular theory, special ontological assumptions and particular methodology. Therefore it is possible to call network analysis as an independent paradigm with given techniques for data gathering and data analysis. This method can be used for studying psychological constructs with network entities (e.g. comorbidity phenomenon). Applying network data analysis in studying relationships of generalized anxiety disorder and major depression disorder symptoms (according to The US National Comorbidity Survey Replication (NCS-R)) shows that it is not possible to distinguish between them and we should consider symptoms relationships in studying, diagnosis and therapy for both of them
asghar minaei; Ali Delavar; Mohammad Reza Falsafinezhad; Ali Reza Kiamanesh; Yahya mohajer
Volume 4, Issue 16 , July 2014, , Pages 138-170
Abstract
Studies of internationalmathematics achievement such as the Trends in Mathematicsand Science Study (TIMSS) have employed classical test theory and item responsetheory to rank individuals within a latent ability continuum. Although these approacheshave provided insights into comparisons between countries, ...
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Studies of internationalmathematics achievement such as the Trends in Mathematicsand Science Study (TIMSS) have employed classical test theory and item responsetheory to rank individuals within a latent ability continuum. Although these approacheshave provided insights into comparisons between countries, they have yet toexamine howspecific attributemastery affects student performance and howthey canprovide information for curricular instruction. In the 2007 administration of TIMSS,two benchmark participants—Massachusetts andMinnesota—were tested followingthe same procedural methods, providing an opportunity for comparison within andacross the United States. Overall comparison of their performance showed Massachusettsand Minnesota to significantly outperform the United States. However,this article shows that there is a greater wealth of fine-grained information that canbe translated directly for classroom application at the attribute level when a cognitivediagnostic model (CDM) such as the deterministic, inputs, noisy, “and” gate (Junker& Sijtsma, 2001) model is used. Results showed a significant disparity betweenproportions of correctly answering and mastering skills required to solve an item.Advantages ofCDMsare discussed aswell as a CDM-basedmethod to filter distractorresponse categories that can aid instructors to diagnose a student’s attribute mastery.
jalil Younesi; farzad Eskandari; Ali Delavar; Mohammad Reza Falsafinezhad; Noor Ali Farokhi
Volume 4, Issue 15 , April 2014, , Pages 166-186
Abstract
Background: Validity of the multilevel analyses with a focus on differences in learning theories (with both classis approach toward measurement and new approach toward measurement (IRT)) by means of various data has recently been studied. Aim: This study is aimed at determining the level of impact of ...
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Background: Validity of the multilevel analyses with a focus on differences in learning theories (with both classis approach toward measurement and new approach toward measurement (IRT)) by means of various data has recently been studied. Aim: This study is aimed at determining the level of impact of schools on the scores gained by students involved in advanced TIMSS’s 2008 test. Methodology: In order to achieve the chief goal of the study, the researchers adopted the data relating to administration of advanced TIMSS’s 2008 physics test, which assesses the course of teaching advanced physics to the high school seniors (pre-university students). The population and sample group of this study comprise the pre-university candidates of mathematics and physics taking advanced TIMSS physics test administered in the academic year 2007-2008. The sample size of Iranian students involved in this measurement equaled 2556 subjects. Findings: Results of the analyses generally suggest that firstly multilevel IRT (MLIRT) analyses are more powerful than multilevel true scores (MLTS) analyses in clarifying school differences. Secondly, the level of difference in the schools involved in advanced TIMSS math test reflected in intraclass correlation (ICC) is high in MLIRT analyses. Discussion and Conclusion: First, considering measurement error of each item in analyses within Bayesian framework and by means of Gibbs sampling can remarkably improve the power of multilevel analyses and lead to a significant rise in the ratio of the explicated variance. Second, there is too much educational difference and discrimination among schools which is largely due to school-level variables (such as those relating to teacher or school-related variables).
