Computerized Multistage Testing: Principles, Designs and Practices with R
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ERIC Institute of Education Sciences
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| Main Authors: | , |
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| Format: | Recurso educativo Open Access |
| Language: | en |
| Published: |
2023
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| _version_ | 1867181810967904256 |
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| author | Yigiter, Mahmut Sami Dogan, Nuri |
| author_facet | Yigiter, Mahmut Sami Dogan, Nuri Yigiter, Mahmut Sami Dogan, Nuri |
| collection | Education Resources Information Center |
| contents | Computerized Multistage Testing: Principles, Designs and Practices with R Yigiter, Mahmut Sami Dogan, Nuri Programming Languages Monte Carlo Methods Computer Assisted Testing Test Format Academic Ability Adaptive Testing Simulation Test Construction In recent years, Computerized Multistage Testing (MST), with their versatile benefits, have found themselves a wide application in large scale assessments and have increased their popularity. The fact that forms can be made ready before the exam application, such as a linear test, and that they can be adapted according to the test taker's ability level, such as computerized adaptive tests, has brought MST to the forefront. It is observed that simulation studies are often used in research on MST. The R programming language used in the conduct of simulation studies is widely used for statistical calculation, data visualization, and Monte Carlo research. Researchers can perform their analysis according to their own research questions, both by writing their own code in R and by using the packages in the library. This study aims to demonstrate the design and implementation of MST simulation examples using the R programming language. In this context, first of all, the basic components of MST were discussed, then R packages written on MST were examined in terms of advantages, disadvantages and analysis facility. Then, three different MST simulation examples were designed with the R programming language. It is considered that this study will be useful to those who are interested in MST. |
| format | Recurso educativo Open Access |
| id | eric_EJ1401557 |
| institution | ERIC Institute of Education Sciences |
| language | en |
| publishDate | 2023 |
| record_format | eric |
| spellingShingle | Computerized Multistage Testing: Principles, Designs and Practices with R Yigiter, Mahmut Sami Dogan, Nuri Programming Languages Monte Carlo Methods Computer Assisted Testing Test Format Academic Ability Adaptive Testing Simulation Test Construction Computerized Multistage Testing: Principles, Designs and Practices with R Yigiter, Mahmut Sami Dogan, Nuri Programming Languages Monte Carlo Methods Computer Assisted Testing Test Format Academic Ability Adaptive Testing Simulation Test Construction In recent years, Computerized Multistage Testing (MST), with their versatile benefits, have found themselves a wide application in large scale assessments and have increased their popularity. The fact that forms can be made ready before the exam application, such as a linear test, and that they can be adapted according to the test taker's ability level, such as computerized adaptive tests, has brought MST to the forefront. It is observed that simulation studies are often used in research on MST. The R programming language used in the conduct of simulation studies is widely used for statistical calculation, data visualization, and Monte Carlo research. Researchers can perform their analysis according to their own research questions, both by writing their own code in R and by using the packages in the library. This study aims to demonstrate the design and implementation of MST simulation examples using the R programming language. In this context, first of all, the basic components of MST were discussed, then R packages written on MST were examined in terms of advantages, disadvantages and analysis facility. Then, three different MST simulation examples were designed with the R programming language. It is considered that this study will be useful to those who are interested in MST. |
| title | Computerized Multistage Testing: Principles, Designs and Practices with R |
| topic | Programming Languages Monte Carlo Methods Computer Assisted Testing Test Format Academic Ability Adaptive Testing Simulation Test Construction |
| url | https://eric.ed.gov/?id=EJ1401557 |