A critical issue in COGNITIVE DIAGNOSTIC ASSESSMENT (CDA) lies in the dearth of research in developing tests for COGNITIVE DIAGNOSTIC purposes. CDA of formative language ASSESSMENT that aims to inform instruction has not been conducted in foreign language learning contexts. During recent years, researchers have attempted to provide more practical results beyond a simple average grade in order to improve learning. This study explored how developing a reading comprehension test based on a COGNITIVE framework could be used for DIAGNOSTIC purposes. To validate the developed test items, a Q-matrix that specified the relationships between test items and target attributes was theoretically developed. Student think-aloud verbal protocols and content rater judgment were used to help construct the Q-matrix. Finally, to diagnose the participants’ strengths and weaknesses, the test was administered to 1986 students of a GE course at the University of Tehran and Fusion Model analysis was used to obtain learners' skill mastery profiles. The obtained results can be very beneficial for formative DIAGNOSTIC feedback.

COGNITIVE DIAGNOSTIC Models (CDMs), are confirmative multidimensional latent variable models, with complex structure. In this study, COGNITIVE DIAGNOSTIC Models (CDMs) were used to check the status of first grade high school students in mathematics. COGNITIVE DIAGNOSTIC ASSESSMENT was administered based on eight main characters, consisting of 32 questions on a sample of 509 students, selected from students of Tehran based on a multi-stage cluster sampling. IRT models where used to determine the psychometric properties of the questions. Data analysis by using the DINA model in mathematics, showed that eight attribute explain the mathematics performance of first grade high school students. Results showed that the subjects were only mastered in one of the attributes and the least proportion of mastery was related to definition comprehension skills (0.494), mathematics advanced operations ( 0.498) and using learning in real problems.

In the response phase the most important step is to assess disaster after occurrence. By disaster ASSESSMENT, we can obtain all the needed information for controlling, decision-making and also disaster planning. Lack of disaster ASSESSMENT causes you to make unsuitable decisions based on limited or inadequate data which leads to imperfect disaster response. According to IFRC, disaster response operation will have an unsuitable function without disaster ASSESSMENT. This paper presents the principles and concepts of disaster ASSESSMENT.

Objective: COGNITIVE DIAGNOSTIC ASSESSMENT has been introduced as a new issue in educational measurement. In this approach, more information was examined about how people learn and master COGNITIVE attributes in school. There are several data modeling issues in COGNITIVE DIAGNOSTIC ASSESSMENT due to differences with another statistical modeling.Methods: In the present study, science data of grade eight in TIMSS was analyzed by COGNITIVE DIAGNOSTIC ASSESSMENT, as an empirical example, and the problems were entitled as modeling challenges. Each challenge has been explained in order to highlight differences from the usual statistical modeling.Results: The challenges included; unidimensionality versus multidimensionality, number of attributes, correlation between attributes, number of items in each attribute, operationalization of attribute, reliability of attribute, validity, item parameters, fit of the model, identification and specification, convergence, and complex sampling.Conclusion: Each topic was discussed in the context of modeling TIMSS data in a science course and the experience of solving these challenges was shared.

Background: Geographical/geometric indicators like azimuth provide a real-time and low-cost method of measuring spatial performance during navigation, especially in view of their accessibility on mobile phones in the form of a compass or GPS. This study aimed to investigate azimuth-based ASSESSMENT of spatial orientation performance and its potential in diagnosing COGNITIVE problems. Methods: This was an applied research, and included multivariate logistic regression and multi-layer neural network analysis. We measured the spatial orientation performance of participants using an azimuth-based compass. Their demographic data, including age, gender, years of driving experience, field of study, and COGNITIVE health status were collected. The statistical population consisted of 52 females and 48 males, 18 of whom had experienced COGNITIVE problems in their lives. The participants were from different ethnic backgrounds living in the US, and in the age range of 20-85. The census method was then applied. Multivariate data analysis was conducted to illustrate the effectiveness of each feature variable on spatial orientation performance. Logistic regression was run by fitting a logit function, and multi-layer neural network analysis was developed and evaluated to predict the risk of COGNITIVE problems based on spatial orientation performance and four other features under study. Results: Multivariate analysis showed that participants’ age (P=0. 005), years of driving experience (P<0. 001), and COGNITIVE problems (P<0. 001) contributed to predicting spatial orientation performance. Those who had experienced COGNITIVE problems deviated 13. 50 degrees from the destination with increasing age. The accuracy of the fitted logit model by NN analysis over training process was 0. 8, indicating that the model can predict 8 out of 10 cases accurately. Conclusion: According to the findings, azimuth-based ASSESSMENT of performance and other demographic data could be an appropriate means of determining individuals’ spatial orientation ability, especially when performed on larger and more homogeneous groups.

The present research aimed at the construction and validation of a reading test based on COGNITIVE DIAGNOSTIC ASSESSMENT model (CDM). In order to construct the test, the most important reading attributes were identified by classifying the attributes relevant to reading in national and international research and documents. Subsequently, the test was designed by considering the viewpoints of experts in the field of Persian language and literature and primary school teachers. After pilot and preliminary analysis and eliminating inappropriate items, the final test was designed with 27 items, which measured four attributes of comprehension of explicit information in the text, inference, integration and interpretation, and vocabulary. In this research, the construction stages of the test were elaborated. Using a cluster sampling method, the test was performed on a sample consisting of 816 sixth grade students in Qom. The statistical analyses were carried out via additive CDM. The relative and absolute indices of fitness indicated that the model is sufficiently fit. Moreover, use of classification consistency and accuracy indices indicated that the test is capable of classifying students with proper consistency and accuracy. The research results illustrated that this test can identify students’ reading attributes using cogniti e DIAGNOSTIC ASSESSMENT model.

The purpose of this study was to determine the basic skills of reading and comprehension and analyze the test questions, and finally, strengths and weaknesses of subjects through COGNITIVE DIAGNOSTIC ASSESSMENT models were fitted with retrofit analysis. The data examined in this study included responses from 3, 000 participants in the graduate entrance examination for English language field, which were selected from among 16044 people randomly. At first, with the help of experts, a matrix Q, consisting of the relationship between 20 questions of reading test with 7 basic skills was formed and then, using the G-DINA model, last analysis was performed. Finally, using a posteriori expected method within the framework of the G-DINA model, probability of domination of every single person on each skill was calculated by CDM package skills in software R, and by determining the cut-off point 0. 6 for dominance, investigated participants in each skill, divided into two dominant and non-dominant groups. The results showed that in each of the skills, most people have not reached to dominance, Although the situation in the SUM skill (Analyzing and evaluating the relative importance of the information contained in the text, by differentiating between the main idea and details) was better than other skills, and about half of those got dominant in the skill. The final result suggests that, in general, the participant's situation in the application of COGNITIVE strategies to achieve the correct answer is unsatisfactory and these strategies must be included in the curriculum of reading skills and comprehension.

Among the language skills, writing is one of the most important communication skills that is planned for its education in all educational systems from the elementary school. The ever-increasing advances in educational ASSESSMENT provide the context for the DIAGNOSTIC information needed to determine the strengths and weaknesses of students. This study intends to explore the possibility of using COGNITIVE DIAGNOSTIC ASSESSMENT to assess the writing attributes of elementary school students. For this purpose, the check list, which was proposed by Kim (2015) for evaluating academic writing in English and the initial Q-matrix, was reviewed. 816 sixth grade elementary school students, answered three writing assignments. Estimation of the model parameters were performed using Reduced Reparametrized Unified Model (R-RUM). The relative and absolute indices indicate that the model is sufficiently fit. The result showed that 17 indicator can be used to assess the writing attitudes with appropriate accuracy in assignments requiring students to write a long text. But for assignments that require writing a short text, the 9 indicator can be used to assess the writing attitudes with appropriate accuracy.