mehdi molaei yasavoli; ali delavar; mohammad asgari; jalil Younesi; vahid rezaei tabar
Abstract
Efficiency and bias of parameter estimation is one of the most important psychometric issues in behavioral science measurements. The existence of various algorithms such as MHRM and their application in tests with missing data is one of the challenges in the field of item-response theory models. The ...
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Efficiency and bias of parameter estimation is one of the most important psychometric issues in behavioral science measurements. The existence of various algorithms such as MHRM and their application in tests with missing data is one of the challenges in the field of item-response theory models. The purpose of this study was to investigate the risk of MHRM algorithm in multidimensional models of item-response theory in multi-valued data by considering the mechanism and the amount of missing data. The research method was experimental using a multi-group post-test design. The study sample was created based on simulation studies under different conditions of independent variables in 27 cases with 100 replications for each. The model used was a multidimensional scaled response model and the studied parameters were the slope and threshold of the questions. R statistical software was used to generate and analyze the data. The results showed that MHRM algorithm has less estimated risk compared to EM and MCEM algorithms. The results also showed that there is a significant difference in the risk of slope and threshold parameters between three different mechanisms of missing data, but no significant difference was observed in relation to the independent variable of missing data. There was also a significant interaction between the type of algorithm and the missing mechanism, which indicated the optimal performance of the MHRM algorithm. Thus when this algorithm is used, the mean and variance of the MSE slope and threshold parameters in all three loss mechanisms also converge as they decrease. As a result, it can be said that the application of MHRM algorithm is essential in data with high data missing and types of missing. Therefore, researchers are advised to use the MHRM algorithm in data analysis with complex structure such as high data missing and various missing mechanisms
Reyhane Rahimi; jalil Younesi; Ali Moghadamzade; Mohammad Asgari
Abstract
Using different methods and techniques to achieve the best results and create synergies between them can be helpful in many issues. Educational data mining is one of the relatively new fields that can be used to solve educational problems, especially problems in the field of measurement. But before using ...
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Using different methods and techniques to achieve the best results and create synergies between them can be helpful in many issues. Educational data mining is one of the relatively new fields that can be used to solve educational problems, especially problems in the field of measurement. But before using these methods, it should be as familiar as possible and its problems, disadvantages and advantages should be examined. In this study, the aim is to investigate the technique of nonnegative matrix factorizations and how to determine the number of clusters before implementing the model. The research method is descriptive and the study population is all those present at the entrance exam for mathematics and technical sciences in 1398, of which 5,000 people were randomly selected by the country's assessment and education organization and provided to the researcher. The research tool is math questions and entrance exam geometry. The results of this analysis showed that there is a difference in estimating the number of clusters of math questions, but in the case of geometry questions, the results of all methods were the same. Due to the observed differences, it is suggested that in future research with the help of data simulation, this issue will be examined in more detail.
mohammad asgari; Azam Kalaee; maryam pourmoosavi
Abstract
The purpose of this study was to validate the online narcissism personality inventory (ONPI) in the Iranian sample. This research is an applied and methodologically was descriptive survey research. The statistical population included all individuals aged 18-50 years old active in cyberspace residing ...
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The purpose of this study was to validate the online narcissism personality inventory (ONPI) in the Iranian sample. This research is an applied and methodologically was descriptive survey research. The statistical population included all individuals aged 18-50 years old active in cyberspace residing in Tehran. 400 individuals (200 females and 200 males) were selected using available sampling method. First, the online narcissism personality inventory (ONPI) was translated into Persian and its content validity was confirmed by psychology and counseling professors. After collecting the required samples, reliability of this tool was determined by SPSS-23 software using Cronbach's alpha for the components of Authority (α = 0.758), Self-Sufficiency (α = 0.767), Superiority (α = 0.712), Exhibitionism (α = 0.764), Exploitativeness (α = 0.754), Vanity (α = 0.705), Entitlement (α = 0.714) and for the whole inventory (α = 0.838). The construct validity of this tool using exploratory factor analysis also showed that the data obtained with the 7-factor model were goodness of fit. Then, the validity and reliability of the inventori's standard scores for each range of scores were assessed by Jmetrik-4.1.1 software. Behaviors that people display in the Cyberspaceare different from the real world, this tool can be used as a convenient tool for measuring narcissism.
Mohamad Asgari; Fatemeh Amoamoha
Abstract
The purpose of this study was to determine the effect of using the portfolio evaluating on the motivation and academic achievement of students in the third grade elementary school in the city of Nahavand in the academic year 2012-2013. For this purpose, a sample of 100 individuals (2 girls and 2 boy's ...
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The purpose of this study was to determine the effect of using the portfolio evaluating on the motivation and academic achievement of students in the third grade elementary school in the city of Nahavand in the academic year 2012-2013. For this purpose, a sample of 100 individuals (2 girls and 2 boy's classes) was selected randomly in a multi-stage method; then, a class (male and female) as an experimental group and a class (male and female) Was selected as the control group. The experimental groups received a course in a portfolio evaluating, but control groups received standardized measurements. For data collection in pre-test and post-test, Hermann's motivation questionnaire and researcher-made academic achievement test were used. Data analysis using multivariate analysis of variance (MANOVA) for differential scores showed that there is a significant difference between motivation and academic achievement in two groups of measurement and portfolio assessment. That is, students who had received a portfolio assessment had a higher degree of motivation and academic achievement than control groups who received standardized measurements. In addition, the portfolio assessment on the motivation and academic achievement of elementary school-boy students has a significant effect; and on the motivation achievement of female students in the third elementary school has a significant effect, but on the academic achievement of female hasn't a significant effect. Measurement-gender interaction was also significant.
