question analysis

Background: Network science as a new field in psychological measurement provides a good platform for test analysis, but in Iran, research on the analysis of test questions using network data analysis has been neglected. Aims: The aim of this study was to introduce network data analysis as a psychometric-mathematical technique and its use in the questionnaire analysis process. Methods: This research is descriptive-analytical, the statistical population of all language learners was the top ten language teaching institutes in Tehran in 2020, from which 1556 language learners were selected by convenience sampling method and answering the English vocabulary size test (Nation and Waring, 1997). Data analysis was performed by qgraph software package under R software. Results: The graph obtained from the communication network of questions based on the Fruchterman-Ringold algorithm was plotted, the parent-child relationship of the questions was determined based on the Bayesian network, and the descriptive features of the test and the indicators of network centrality were extracted. Conclusion: Introducing the technique of analyzing network data and using it for questions analysis process is one of the achievements of this article. Using the advantages of network science such as the ability to simplify, manage, store and collect high-volume data and analyze test questions based on the map and indicators that are fully consistent with it, we can understand the internal relationship between different test questions, and by considering the importance of the questions in the network structure of the net relationship between the questions, it is possible to improve the testing methods. Similar studies and researches are proposed to compare the results of network data analysis with psychometric properties obtained based on conventional and classical methods.

A significant amount of business and scientific data is collected via question and answer reports. However, these reports often suffer from various data quality issues. In many cases, questionnaires contain a number of questions that require multiple answers, which we argue can be a potential source of problems that may lead to poor-quality answers. This paper introduces multifocal questions and proposes a model for identifying them. The model consists of three phases: question pre-processing, feature engineering and question classification. We use six types of features: lexical/surface features, Part-of-Speech, readability, question structure, wording and placement features, question response type and format features and question focus. A comparative study of three different machine learning algorithms (Bayes Net, Decision Tree and Support Vector Machine) is performed on a dataset of 150 questions obtained from the Carbon Disclosure Project, achieving the accuracy of 91%.

Background: Network science as a new field in psychological measurement provides a good platform for test analysis, but in Iran, research on the analysis of test questions using network data analysis has been neglected. Aims: The aim of this study was to introduce network data analysis as a psychometric-mathematical technique and its use in the questionnaire analysis process. Methods: This research is descriptive-analytical, the statistical population of all language learners was the top ten language teaching institutes in Tehran in 2020, from which 1556 language learners were selected by convenience sampling method and answering the English vocabulary size test (Nation and Waring, 1997). Data analysis was performed by qgraph software package under R software. Results: The graph obtained from the communication network of questions based on the Fruchterman-Ringold algorithm was plotted, the parent-child relationship of the questions was determined based on the Bayesian network, and the descriptive features of the test and the indicators of network centrality were extracted. Conclusion: Introducing the technique of analyzing network data and using it for questions analysis process is one of the achievements of this article. Using the advantages of network science such as the ability to simplify, manage, store and collect high-volume data and analyze test questions based on the map and indicators that are fully consistent with it, we can understand the internal relationship between different test questions, and by considering the importance of the questions in the network structure of the net relationship between the questions, it is possible to improve the testing methods. Similar studies and researches are proposed to compare the results of network data analysis with psychometric properties obtained based on conventional and classical methods.

Introduction:
This research aims to investigate the factor structure and Psychometric Properties of Difficulties in Emotion Regulation Scale (DERS) in an Iranian sample.
Method:
The statistical population of this study comprised all the students of Shiraz University. Among them, a total of 363 people (181 male, 182 female) were selected using stratified random sampling. To achieve the study objective and assess convergent validity, the Persian version of DERS and Beck Depression Inventory were used, respectively.
Results:
The results obtained from explratory factor analyses showed that from among eight extracted factors of the scale, six were associated with DERS and two other factors were omitted as a result of loading of just one item. In addition, internal correlations and correlations of all subscales of DERS with BDI were significant. Finally, internal consistency of this scale using Cronbach’s alpha for all subscales ranged from r=0.86 to r=0/88. Furthermore, the one-week test-retest coefficient also ranged from r=0.79 to r=0.91.
Conclusion:
Based on the results obtained from the research, DERS can be applied to attain research and clinical objectives in Iranian society.

Background and Aim: Studies have found that deaf individuals have higher rates of psychiatric disorders, such as behavioral problems, than those who can hear. The aim of this review was to provide a summary of the literature on behavioral problems, with specific reference to deaf individuals. The objectives of the review were to establish the prevalence of behavioral problems in deaf populations; describe the risk factor for behavioral problems in deaf populations; and describe approaches to intervention and behavioral problems prevention that have been used in deaf populations. Recent Findings: A review of articles published between 1991 and 2013 showed that the prevalence of behavioral problems in deaf people is higher than that of hearing people. Risk factors for behavioral problems in deaf populations include language impairments, communication problems, the role of parents, and the community's beliefs and attitudes regarding the issue. Conclusion: Given the high prevalence of behavioral problems in deaf people, the effectiveness of prevention strategies should be examined. Consequently, it would be advantageous to increase the availability of specialist mental health services, promote deaf awareness including their abilities, promote awareness and skills development among teachers, staff, and specialists and implement behavior change programs.

Background and Aim: Studies have found that deaf individuals have higher rates of psychiatric disorders, such as behavioral problems, than those who can hear. The aim of this review was to provide a summary of the literature on behavioral problems, with specific reference to deaf individuals. The objectives of the review were to establish the prevalence of behavioral problems in deaf populations; describe the risk factor for behavioral problems in deaf populations; and describe approaches to intervention and behavioral problems prevention that have been used in deaf populations. Recent Findings: A review of articles published between 1991 and 2013 showed that the prevalence of behavioral problems in deaf people is higher than that of hearing people. Risk factors for behavioral problems in deaf populations include language impairments, communication problems, the role of parents, and the community's beliefs and attitudes regarding the issue. Conclusion: Given the high prevalence ...

An important element in question answering systems is the analysis and interpretation of questions. Using the NTCIR 5 Cross-Language Question Answering (CLQA) question test set we demonstrate that the accuracy of deep question analysis is dependent on the quantity and suitability of the available linguistic resources. We further demonstrate that applying question analysis tools developed on monolingual training materials to questions translated Chinese-English and English-Chinese using machine translation produces much reduced effectiveness in interpretation of the question. This latter result indicates that question analysis for CLQA should primarily be conducted in the question language prior to translation.

Objective: Due to the lack of electronic scale for screening elementary students based on Iranian culture, this study provides a short online version of the mental health scale-teacher report to increase accuracy and speed of screening and reduce costs of it.
Methods: The sample of the study was 22845 students (11545 female, 11300 male) of all provinces of Iran, who filled the long version of the Children's Psychological Health Scale (Akbari Zardkhaneh et al., 2018), including eighty items and eight subscales.
Results: Item analysis with eight criteria showed that almost all items have good features. Factor analysis suggested that an eight-component model with forty items could be considered as a final structure for the short version. Examination of the measurement invariance between the gender groups indicated a suitable fitness that showed this scale assesses the same construct in both gender groups. Internal consistency was sufficiently good and Cronbach's alpha coefficients for the whole scale was 0.97 and for subscales ranged between 0.75-0.93 and 0.80- 0.93, for female and male group respectively. Composite reliability coefficients ranged between 0.70 and 0.93 for girls and between 0.74 and 0.93 for boys. Measurement errors of the scale and subscales showed a suitable range. Standard path coefficients showed a suitable convergent validity of scale. Divergent validity of scale evaluated by average variance extracted and by HTMT method showed the necessary internal consistency and the construct validity within the scale.
Conclusion: This scale is eligible enough to screen primary school students in Iran; however, further evidence is needed.

In recent years, learning objects have been playing a crucial role in the teaching process. However, research focused on the analysis of science learning objects is particularly limited. The present study aims to analyze the science learning objects of the Greek Digital Learning Object Repository that are intended for primary school from a learning activities perspective. A total of 178 learning objects were analyzed. The analysis of learning objects from the perspective of the learning activities (cognitive and metacognitive) they activate in the students was carried out in line with the analysis framework of Overman, Vermunt, Meijer, Bulte and Brekelmans (2013). The analysis of learning objects showed that they are dominated by low level cognitive learning activities, while the learning objects that activate high level cognitive learning activities are limited. Finally, no learning objects activating metacognitive learning activities in the students were detected.