This study aimed to adapt the COVID-19 Stress Scales (CSS) into Turkish and provide evidence for construct validity. For this purpose, firstly, Confirmatory factor analysis (CFA) was applied for the 5-factor model obtained during the development of CSS and the theoretically expected 6-factor model with total of 546 respondents. The findings revealed that the 6-factor model of CSS had a better fit in the Turkish sample. Factor loadings varied between .62 - .95 and correlations between subscales were between .44 - .76. Cronbach's Alpha and McDonald’s ω coefficients for each subscale indicated good-to-excellent internal consistency. To evaluate the criterion-related validity, the Turkish version of The Fear of COVID-19 Scale (FCV-19S) was administered to the participants and the correlation coefficients between this scale and the six subscale of CSS were calculated. We also conducted the Rasch analysis with related items to provide psychometric evidence for their unidimensional structure of each of the six subscales. Lastly, Differential item functioning (DIF) analysis was performed across subgroups by gender, having COVID-19, and being a student. Overall, the results of both CFA and Rasch analyses provided evidence to support the substantive aspect of validity and the appropriateness of the CSS as a measure of COVID-19 stress level in a Turkish sample.
{"title":"Adaptation and psychometric evaluation of the COVID-19 stress scales in Turkish sample","authors":"M. Şahin, S. Şen, Deniz Güler","doi":"10.21449/ijate.1067542","DOIUrl":"https://doi.org/10.21449/ijate.1067542","url":null,"abstract":"This study aimed to adapt the COVID-19 Stress Scales (CSS) into Turkish and provide evidence for construct validity. For this purpose, firstly, Confirmatory factor analysis (CFA) was applied for the 5-factor model obtained during the development of CSS and the theoretically expected 6-factor model with total of 546 respondents. The findings revealed that the 6-factor model of CSS had a better fit in the Turkish sample. Factor loadings varied between .62 - .95 and correlations between subscales were between .44 - .76. Cronbach's Alpha and McDonald’s ω coefficients for each subscale indicated good-to-excellent internal consistency. To evaluate the criterion-related validity, the Turkish version of The Fear of COVID-19 Scale (FCV-19S) was administered to the participants and the correlation coefficients between this scale and the six subscale of CSS were calculated. We also conducted the Rasch analysis with related items to provide psychometric evidence for their unidimensional structure of each of the six subscales. Lastly, Differential item functioning (DIF) analysis was performed across subgroups by gender, having COVID-19, and being a student. Overall, the results of both CFA and Rasch analyses provided evidence to support the substantive aspect of validity and the appropriateness of the CSS as a measure of COVID-19 stress level in a Turkish sample.","PeriodicalId":42417,"journal":{"name":"International Journal of Assessment Tools in Education","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48823657","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study aims to examine the relations and associations between gender, epistemic curiosity (EC), self-regulated learning (SRL), and attitudes toward e-learning in higher education students. The participants were 2438 (862 males, 1576 females) undergraduate students enrolled in a Turkish university. The regression analysis findings showed that although the effect size was low, attitudes towards e-learning can be predicted significantly by gender, EC, and SRL. Datasets are further analyzed using data mining. The findings of the association rule mining revealed that gender plays an influential role. Several association rules among EC, SRL, and attitudes towards e-learning were detected for female students. The results provide recommendations about using data mining as a statistical method in educational and psychological research.
{"title":"The role of individual differences on epistemic curiosity (EC) and self-regulated learning (SRL) during e-learning: the Turkish context","authors":"Ergün Akgün, E. Mede, S. Saraç","doi":"10.21449/ijate.907186","DOIUrl":"https://doi.org/10.21449/ijate.907186","url":null,"abstract":"This study aims to examine the relations and associations between gender, epistemic curiosity (EC), self-regulated learning (SRL), and attitudes toward e-learning in higher education students. The participants were 2438 (862 males, 1576 females) undergraduate students enrolled in a Turkish university. The regression analysis findings showed that although the effect size was low, attitudes towards e-learning can be predicted significantly by gender, EC, and SRL. Datasets are further analyzed using data mining. The findings of the association rule mining revealed that gender plays an influential role. Several association rules among EC, SRL, and attitudes towards e-learning were detected for female students. The results provide recommendations about using data mining as a statistical method in educational and psychological research.","PeriodicalId":42417,"journal":{"name":"International Journal of Assessment Tools in Education","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47663180","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Most researchers investigate the corrected item-total correlation of items when analyzing item discrimination in multi-dimensional structures under the Classical Test Theory, which might lead to underestimating item discrimination, thereby removing items from the test. Researchers might investigate the corrected item-total correlation with the factors to which that item belongs; however, getting a general overview of the entire test is impossible. Based on this problem, this study aims to recommend a new index to investigate item discrimination in two-dimensional structures through a Monte Carlo simulation. The new item discrimination index is evaluated by identifying sample size, item discrimination value, inter-factor correlation, and the number of categories. Based upon the results of the study it can be claimed that the proposed item discrimination index proves acceptable performance for two-dimensional structures. Accordingly, using this new item discrimination index could be recommended to researchers when investigating item discrimination in two-dimensional structures.
{"title":"To what extent are item discrimination values realistic? A new index for two-dimensional structures","authors":"A. Kılıç, Ibrahim Uysal","doi":"10.21449/ijate.1098757","DOIUrl":"https://doi.org/10.21449/ijate.1098757","url":null,"abstract":"Most researchers investigate the corrected item-total correlation of items when analyzing item discrimination in multi-dimensional structures under the Classical Test Theory, which might lead to underestimating item discrimination, thereby removing items from the test. Researchers might investigate the corrected item-total correlation with the factors to which that item belongs; however, getting a general overview of the entire test is impossible. Based on this problem, this study aims to recommend a new index to investigate item discrimination in two-dimensional structures through a Monte Carlo simulation. The new item discrimination index is evaluated by identifying sample size, item discrimination value, inter-factor correlation, and the number of categories. Based upon the results of the study it can be claimed that the proposed item discrimination index proves acceptable performance for two-dimensional structures. Accordingly, using this new item discrimination index could be recommended to researchers when investigating item discrimination in two-dimensional structures.","PeriodicalId":42417,"journal":{"name":"International Journal of Assessment Tools in Education","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48881421","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study is intended to explore an applicable and effective model of simulated situation for English as a Foreign Language (EFL) learners and also investigate the effects of the simulated environment on Willingness to Communicate (WTC) of the learners. To carry out this study, 300 elementary level EFL learners were chosen. A Key English Test (KET) was administered to ensure homogeneity on the learners. They were divided into two groups of experimental and control. A WTC questionnaire developed by Macintyre, Baker, Clement, and Conrod (2001) was used, after validation through Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA) and Modeling, as an instrument to obtain primary data. The results of Mann- Whitney U test revealed that simulated environment had positive effects on the participants’ WTC. The findings of this study suggest that understanding how a simulated environment affects EFL learners’ success in speaking proficiency can help institutes to provide such environments for EFL learners and instructors. This method can be presented at different levels of English proficiency. The focus of this study was mainly on speaking skill; therefore, similar studies can be conducted regarding other language skills, e.g., writing, listening and reading.
{"title":"Exploring how the use of a simulation technique can affect EFL students’ willingness to communicate","authors":"Houman Bijani, M. Abbasi","doi":"10.21449/ijate.987659","DOIUrl":"https://doi.org/10.21449/ijate.987659","url":null,"abstract":"This study is intended to explore an applicable and effective model of simulated situation for English as a Foreign Language (EFL) learners and also investigate the effects of the simulated environment on Willingness to Communicate (WTC) of the learners. To carry out this study, 300 elementary level EFL learners were chosen. A Key English Test (KET) was administered to ensure homogeneity on the learners. They were divided into two groups of experimental and control. A WTC questionnaire developed by Macintyre, Baker, Clement, and Conrod (2001) was used, after validation through Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA) and Modeling, as an instrument to obtain primary data. The results of Mann- Whitney U test revealed that simulated environment had positive effects on the participants’ WTC. The findings of this study suggest that understanding how a simulated environment affects EFL learners’ success in speaking proficiency can help institutes to provide such environments for EFL learners and instructors. This method can be presented at different levels of English proficiency. The focus of this study was mainly on speaking skill; therefore, similar studies can be conducted regarding other language skills, e.g., writing, listening and reading.","PeriodicalId":42417,"journal":{"name":"International Journal of Assessment Tools in Education","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46434782","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The aim of this study is to investigate the presence of DIF over the gender variable with the latent class modeling approach. Data were 880 students from the USA who participated in the PISA 2018 8th-grade financial literacy assessment. Latent class analysis (LCA) approach was used to determine the latent classes and the data fit the three-class model better in line with fit indices. To obtain more information about the characteristics of the emerging classes, uniform and non-uniform DIF sources were determined by using the Multiple Indicator Multiple Causes (MIMIC) model. The findings are very important in terms of contributing to the interpretation of latent classes. According to the results, the gender variable is a potential source of DIF for latent class indicators. Gathering unbiased estimates for the measurement and structural parameters, it is important to include direct effects in the classes. Ignoring these effects can lead to incorrect determination of implicit classess. An example of the application of Multiple Indicator Multiple Causes (MIMIC) model showed in a latent class framework with a stepwise approach with this study.
{"title":"Differential item functioning across gender with MIMIC modeling: PISA 2018 financial literacy items","authors":"F. Saatçi̇oğlu","doi":"10.21449/ijate.1076464","DOIUrl":"https://doi.org/10.21449/ijate.1076464","url":null,"abstract":"The aim of this study is to investigate the presence of DIF over the gender variable with the latent class modeling approach. Data were 880 students from the USA who participated in the PISA 2018 8th-grade financial literacy assessment. Latent class analysis (LCA) approach was used to determine the latent classes and the data fit the three-class model better in line with fit indices. To obtain more information about the characteristics of the emerging classes, uniform and non-uniform DIF sources were determined by using the Multiple Indicator Multiple Causes (MIMIC) model. The findings are very important in terms of contributing to the interpretation of latent classes. According to the results, the gender variable is a potential source of DIF for latent class indicators. Gathering unbiased estimates for the measurement and structural parameters, it is important to include direct effects in the classes. Ignoring these effects can lead to incorrect determination of implicit classess. An example of the application of Multiple Indicator Multiple Causes (MIMIC) model showed in a latent class framework with a stepwise approach with this study.","PeriodicalId":42417,"journal":{"name":"International Journal of Assessment Tools in Education","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68257894","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The purpose of this study is to identify which scale short-form development method produces better findings in different factor structures. A simulation study was designed based on this purpose. Three different factor structures and three simulation conditions were selected. As the findings of this simulation study, the model-data fit and reliability coefficients were reported for each factor structure in each simulation condition. All analyses were conducted under the R environment. According to the findings of this study, the increase in the level of misspecification and the decrease in the sample size can significantly affect the model-data fit. In a situation where the factor structure of the scale is getting more and more complex, model-data fit and Omega coefficients decrease. For scales with a unidimensional factor structure, all of the scale short-form development methods are recommended. For scales with multidimensional factor structure, Ant Colony Optimization, and Stepwise Confirmatory Factor Analysis algorithms and for scales with bifactor factor structure, the ACO algorithm is recommended. When viewed from the framework of metaheuristic algorithms, it has been identified that ACO produces better findings than Tabu Search.
{"title":"Which scale short form development method is better? A Comparison of ACO, TS, and SCOFA","authors":"Hakan Koğar","doi":"10.21449/ijate.946231","DOIUrl":"https://doi.org/10.21449/ijate.946231","url":null,"abstract":"The purpose of this study is to identify which scale short-form development method produces better findings in different factor structures. A simulation study was designed based on this purpose. Three different factor structures and three simulation conditions were selected. As the findings of this simulation study, the model-data fit and reliability coefficients were reported for each factor structure in each simulation condition. All analyses were conducted under the R environment. According to the findings of this study, the increase in the level of misspecification and the decrease in the sample size can significantly affect the model-data fit. In a situation where the factor structure of the scale is getting more and more complex, model-data fit and Omega coefficients decrease. For scales with a unidimensional factor structure, all of the scale short-form development methods are recommended. For scales with multidimensional factor structure, Ant Colony Optimization, and Stepwise Confirmatory Factor Analysis algorithms and for scales with bifactor factor structure, the ACO algorithm is recommended. When viewed from the framework of metaheuristic algorithms, it has been identified that ACO produces better findings than Tabu Search.","PeriodicalId":42417,"journal":{"name":"International Journal of Assessment Tools in Education","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44016408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The purpose of this study was to investigate the Type I Error findings and power rates of the methods used to determine dimensionality in unidimensional and bidimensional psychological constructs for various conditions (characteristic of the distribution, sample size, length of the test, and interdimensional correlation) and to examine the joint effect of the conditions (effect of the interaction of conditions) as well as the main effect of each condition. The simulative data were generated for the study using the SAS program. Within the scope of the study, the data were analyzed using the DIMTEST T statistic and the Dimensionality DETECT IDN index, which is one of the non-parametric methods. The Nonlinear Factor Analysis (NOHARM) method was preferred from among parametric methods. As a result of the study, it was noted that the most consistent results in making the unidimensionality decisions belong to the Nonlinear Factor Analysis method showing standard normal distribution according to the shape of the distribution. When the power study results were examined, it was noted that the DIMTEST T statistic gave more accurate results in conditions with large samples, consisting of data with standard normal distribution. On the other hand, while results of the DETECT IDN index and Nonlinear factor analysis were more internally consistent, it was noted that in conditions where the sample size was 1000 and above, the DIMTEST T statistic also made the right decisions in determining dimensionality.
{"title":"A Comparison of Type I Error and Power Rates in Procedures Used Determining Test Dimensionality","authors":"Gülru Güler, Nükhet Çikrikçi","doi":"10.21449/ijate.1059628","DOIUrl":"https://doi.org/10.21449/ijate.1059628","url":null,"abstract":"The purpose of this study was to investigate the Type I Error findings and power rates of the methods used to determine dimensionality in unidimensional and bidimensional psychological constructs for various conditions (characteristic of the distribution, sample size, length of the test, and interdimensional correlation) and to examine the joint effect of the conditions (effect of the interaction of conditions) as well as the main effect of each condition. The simulative data were generated for the study using the SAS program. Within the scope of the study, the data were analyzed using the DIMTEST T statistic and the Dimensionality DETECT IDN index, which is one of the non-parametric methods. The Nonlinear Factor Analysis (NOHARM) method was preferred from among parametric methods. As a result of the study, it was noted that the most consistent results in making the unidimensionality decisions belong to the Nonlinear Factor Analysis method showing standard normal distribution according to the shape of the distribution. When the power study results were examined, it was noted that the DIMTEST T statistic gave more accurate results in conditions with large samples, consisting of data with standard normal distribution. On the other hand, while results of the DETECT IDN index and Nonlinear factor analysis were more internally consistent, it was noted that in conditions where the sample size was 1000 and above, the DIMTEST T statistic also made the right decisions in determining dimensionality.","PeriodicalId":42417,"journal":{"name":"International Journal of Assessment Tools in Education","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2022-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45926584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Recently, adaptive test approaches have become a viable alternative to traditional fixed-item tests. The main advantage of adaptive tests is that they reach desired measurement precision with fewer items. However, fewer items mean that each item has a more significant effect on ability estimation and therefore those tests are open to more consequential results from any flaw in an item. So, any items indicating differential item functioning (DIF) may play an important role in examinees' test scores. This study, therefore, aimed to investigate the effect of DIF items on the performance of computer adaptive and multi-stage tests. For this purpose, different test designs were tested under different test lengths and ratios of DIF items using Monte Carlo simulation. As a result, it was seen that computer adaptive test (CAT) designs had the best measurement precision over all conditions. When multi-stage test (MST) panel designs were compared, it was found that the 1-3-3 design had higher measurement precision in most of the conditions; however, the findings were not enough to say that 1-3-3 design performed better than the 1-2-4 design. Furthermore, CAT was found to be the least affected design by the increase of ratio of DIF items. MST designs were affected by that increment especially in the 10-item length test.
{"title":"The Effect of Ratio of Items Indicating Differential Item Functioning on Computer Adaptive and Multi-Stage Tests","authors":"Başak ERDEM KARA, Nuri Doğan","doi":"10.21449/ijate.1105769","DOIUrl":"https://doi.org/10.21449/ijate.1105769","url":null,"abstract":"Recently, adaptive test approaches have become a viable alternative to traditional fixed-item tests. The main advantage of adaptive tests is that they reach desired measurement precision with fewer items. However, fewer items mean that each item has a more significant effect on ability estimation and therefore those tests are open to more consequential results from any flaw in an item. So, any items indicating differential item functioning (DIF) may play an important role in examinees' test scores. This study, therefore, aimed to investigate the effect of DIF items on the performance of computer adaptive and multi-stage tests. For this purpose, different test designs were tested under different test lengths and ratios of DIF items using Monte Carlo simulation. As a result, it was seen that computer adaptive test (CAT) designs had the best measurement precision over all conditions. When multi-stage test (MST) panel designs were compared, it was found that the 1-3-3 design had higher measurement precision in most of the conditions; however, the findings were not enough to say that 1-3-3 design performed better than the 1-2-4 design. Furthermore, CAT was found to be the least affected design by the increase of ratio of DIF items. MST designs were affected by that increment especially in the 10-item length test.","PeriodicalId":42417,"journal":{"name":"International Journal of Assessment Tools in Education","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2022-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47490891","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this study, the phonographic view of the acceleration of scientific publishing in Türkiye has been revealed with TÜBİTAK/DergiPark data and the values of the measurements of the impact factors of scientific journals have been sampled with the SOBIAD Index data. SOBIAD Index dataset was used in the study. Using the "full count" research method, the data were analyzed by providing access to the entire mass, which is the research population, based on purpose-oriented descriptive analysis. In the calculation of the impact factors of the articles in the SOBIAD index, multiple parameters such as the total number of citations of the articles in the journal, citation comparison (percentage) and area-weighted citation impact, new metric joint values and the similarity criteria in the content evaluation were determined. In the study, the measurement and evaluation standards of international impact factor measuring institutions (WOS-SSCI, Google Scholar, Eigenfactor Metrix and Elsevier/Scopus Index) were also used. According to the results of the research, while the average value of the impact factors of scientific journals in Türkiye is 0.19, this is seen as 6,19 in WOS-SSCI. With the research, the examination of the impact factors of scientific journals and articles in Türkiye was presented as an original review through the SOBIAD index sample. In order to increase the quality and impact factor of journal/article in academic publishing in Türkiye, qualified growth is required rather than quantitative growth.
{"title":"Evaluation of Impact Factors of Articles in Scientific Open Access Journals in Turkey","authors":"Orhan Alav","doi":"10.21449/ijate.1076989","DOIUrl":"https://doi.org/10.21449/ijate.1076989","url":null,"abstract":"In this study, the phonographic view of the acceleration of scientific publishing in Türkiye has been revealed with TÜBİTAK/DergiPark data and the values of the measurements of the impact factors of scientific journals have been sampled with the SOBIAD Index data. SOBIAD Index dataset was used in the study. Using the \"full count\" research method, the data were analyzed by providing access to the entire mass, which is the research population, based on purpose-oriented descriptive analysis. In the calculation of the impact factors of the articles in the SOBIAD index, multiple parameters such as the total number of citations of the articles in the journal, citation comparison (percentage) and area-weighted citation impact, new metric joint values and the similarity criteria in the content evaluation were determined. In the study, the measurement and evaluation standards of international impact factor measuring institutions (WOS-SSCI, Google Scholar, Eigenfactor Metrix and Elsevier/Scopus Index) were also used. According to the results of the research, while the average value of the impact factors of scientific journals in Türkiye is 0.19, this is seen as 6,19 in WOS-SSCI. With the research, the examination of the impact factors of scientific journals and articles in Türkiye was presented as an original review through the SOBIAD index sample. In order to increase the quality and impact factor of journal/article in academic publishing in Türkiye, qualified growth is required rather than quantitative growth.","PeriodicalId":42417,"journal":{"name":"International Journal of Assessment Tools in Education","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2022-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48528296","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The purpose of this study is to develop Education Value Perception Scale (EVPS) based on Bronfenbrenner's Ecological Theory and to investigate its psychometric properties according to Classical Test Theory (CTT) and Item Response Theory (IRT). The data were collected from 2872 secondary school students by stratified purposeful sampling method. Measurement invariance of EVPS was tested by multigroup confirmatory factor analysis based on gender, and scalar invariance was observed to have been provided. The estimations based on IRT were conducted based on Graded Response Model. While high positive correlations were found between the item discriminations estimated according to different test theories, high negative correlations were identified between item means. McDonald’s Omega was calculated to be .79 according to CTT from reliability estimation methods, marginal reliability coefficient was determined to be .77 according to IRT. In the test-retest applications performed at 20-day intervals, the stability coefficient was found to be.81.
{"title":"Investigation of education value perception scale's psychometric properties according to CTT and IRT","authors":"Harun Di̇lek, Ufuk Akbaş","doi":"10.21449/ijate.986530","DOIUrl":"https://doi.org/10.21449/ijate.986530","url":null,"abstract":"The purpose of this study is to develop Education Value Perception Scale (EVPS) based on Bronfenbrenner's Ecological Theory and to investigate its psychometric properties according to Classical Test Theory (CTT) and Item Response Theory (IRT). The data were collected from 2872 secondary school students by stratified purposeful sampling method. Measurement invariance of EVPS was tested by multigroup confirmatory factor analysis based on gender, and scalar invariance was observed to have been provided. The estimations based on IRT were conducted based on Graded Response Model. While high positive correlations were found between the item discriminations estimated according to different test theories, high negative correlations were identified between item means. McDonald’s Omega was calculated to be .79 according to CTT from reliability estimation methods, marginal reliability coefficient was determined to be .77 according to IRT. In the test-retest applications performed at 20-day intervals, the stability coefficient was found to be.81.","PeriodicalId":42417,"journal":{"name":"International Journal of Assessment Tools in Education","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2022-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46881240","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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