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Examination of Different Item Response Theory Models on Tests Composed of Testlets

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Title: Examination of Different Item Response Theory Models on Tests Composed of Testlets
Language: English
Authors: Kogar, Esin Yilmaz, Kelecioglu, Hülya
Source: Journal of Education and Learning. 2017 6(4):113-126.
Availability: Canadian Center of Science and Education. 1120 Finch Avenue West Suite 701-309, Toronto, OH M3J 3H7, Canada. Tel: 416-642-2606; Fax: 416-642-2608; e-mail: jel@ccsenet.org; Web site: http://www.ccsenet.org/journal/index.php/jel
Peer Reviewed: Y
Page Count: 14
Publication Date: 2017
Document Type: Journal Articles
Reports - Research
Education Level: Elementary Secondary Education
Descriptors: Item Response Theory, Models, Mathematics Tests, Test Items, Item Analysis, Sample Size, Error Patterns, Error of Measurement, International Assessment, Prediction, Correlation, Problem Sets, Test Reliability, Test Validity, Elementary Secondary Education
ISSN: 1927-5250
Abstract: The purpose of this research is to first estimate the item and ability parameters and the standard error values related to those parameters obtained from Unidimensional Item Response Theory (UIRT), bifactor (BIF) and Testlet Response Theory models (TRT) in the tests including testlets, when the number of testlets, number of independent items, and sample size change, and then to compare the obtained results. Mathematic test in PISA 2012 was employed as the data collection tool, and 36 items were used to constitute six different data sets containing different numbers of testlets and independent items. Subsequently, from these constituted data sets, three different sample sizes of 250, 500 and 1000 persons were selected randomly. When the findings of the research were examined, it was determined that, generally the lowest mean error values were those obtained from UIRT, and TRT yielded a mean of error estimation lower than that of BIF. It was found that, under all conditions, models which take into consideration the local dependency have provided a better model-data compatibility than UIRT, generally there is no meaningful difference between BIF and TRT, and both models can be used for those data sets. It can be said that when there is a meaningful difference between those two models, generally BIF yields a better result. In addition, it has been determined that, in each sample size and data set, item and ability parameters and correlations of errors of the parameters are generally high.
Abstractor: As Provided
Number of References: 45
Entry Date: 2017
Accession Number: EJ1145522
Database: ERIC
FullText Text:
  Availability: 0
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  Data: Examination of Different Item Response Theory Models on Tests Composed of Testlets
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  Data: <searchLink fieldCode="AR" term="%22Kogar%2C+Esin+Yilmaz%22">Kogar, Esin Yilmaz</searchLink><br /><searchLink fieldCode="AR" term="%22Kelecioglu%2C+Hülya%22">Kelecioglu, Hülya</searchLink>
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  Data: Canadian Center of Science and Education. 1120 Finch Avenue West Suite 701-309, Toronto, OH M3J 3H7, Canada. Tel: 416-642-2606; Fax: 416-642-2608; e-mail: jel@ccsenet.org; Web site: http://www.ccsenet.org/journal/index.php/jel
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  Data: 14
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  Data: 1927-5250
– Name: Abstract
  Label: Abstract
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  Data: The purpose of this research is to first estimate the item and ability parameters and the standard error values related to those parameters obtained from Unidimensional Item Response Theory (UIRT), bifactor (BIF) and Testlet Response Theory models (TRT) in the tests including testlets, when the number of testlets, number of independent items, and sample size change, and then to compare the obtained results. Mathematic test in PISA 2012 was employed as the data collection tool, and 36 items were used to constitute six different data sets containing different numbers of testlets and independent items. Subsequently, from these constituted data sets, three different sample sizes of 250, 500 and 1000 persons were selected randomly. When the findings of the research were examined, it was determined that, generally the lowest mean error values were those obtained from UIRT, and TRT yielded a mean of error estimation lower than that of BIF. It was found that, under all conditions, models which take into consideration the local dependency have provided a better model-data compatibility than UIRT, generally there is no meaningful difference between BIF and TRT, and both models can be used for those data sets. It can be said that when there is a meaningful difference between those two models, generally BIF yields a better result. In addition, it has been determined that, in each sample size and data set, item and ability parameters and correlations of errors of the parameters are generally high.
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  Data: As Provided
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  Data: 2017
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  Data: EJ1145522
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1145522
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    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 14
        StartPage: 113
    Subjects:
      – SubjectFull: Item Response Theory
        Type: general
      – SubjectFull: Models
        Type: general
      – SubjectFull: Mathematics Tests
        Type: general
      – SubjectFull: Test Items
        Type: general
      – SubjectFull: Item Analysis
        Type: general
      – SubjectFull: Sample Size
        Type: general
      – SubjectFull: Error Patterns
        Type: general
      – SubjectFull: Error of Measurement
        Type: general
      – SubjectFull: International Assessment
        Type: general
      – SubjectFull: Prediction
        Type: general
      – SubjectFull: Correlation
        Type: general
      – SubjectFull: Problem Sets
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      – SubjectFull: Test Reliability
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      – SubjectFull: Test Validity
        Type: general
      – SubjectFull: Elementary Secondary Education
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    Titles:
      – TitleFull: Examination of Different Item Response Theory Models on Tests Composed of Testlets
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