Digital Module 25: Testlet Response Theory

2021 ◽  
Vol 40 (2) ◽  
pp. 110-111
Author(s):  
Hong Jiao ◽  
Manqian Liao
Keyword(s):  
Response Theory ◽  
Testlet Response Theory ◽  
Digital Module

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

2017 ◽  
Vol 6 (4) ◽  
pp. 113
Author(s):  
Esin Yilmaz Kogar ◽  
Hülya Kelecioglu
Keyword(s):  
Item Response Theory ◽  
Sample Size ◽  
Item Response ◽  
Data Sets ◽  
Meaningful Difference ◽  
Response Theory ◽  
Size Change ◽  
Data Set ◽  
Testlet Response Theory ◽  
Item Response Theory Models

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.

scholarly journals An Extension of Testlet-Based Equating to the Polytomous Testlet Response Theory Model

2022 ◽  
Vol 12 ◽  
Author(s):  
Feifei Huang ◽  
Zhe Li ◽  
Ying Liu ◽  
Jingan Su ◽  
Li Yin ◽  
...  
Keyword(s):  
Item Response Theory ◽  
Sample Size ◽  
Item Response ◽  
Theory Model ◽  
Response Theory ◽  
Polytomous Items ◽  
Testlet Response Theory ◽  
Accurate Performance ◽  
The Impact ◽  
Item Response Theory Models

Educational assessments tests are often constructed using testlets because of the flexibility to test various aspects of the cognitive activities and broad content sampling. However, the violation of the local item independence assumption is inevitable when tests are built using testlet items. In this study, simulations are conducted to evaluate the performance of item response theory models and testlet response theory models for both the dichotomous and polytomous items in the context of equating tests composed of testlets. We also examine the impact of testlet effect, length of testlet items, and sample size on estimating item and person parameters. The results show that more accurate performance of testlet response theory models over item response theory models was consistently observed across the studies, which supports the benefits of using the testlet response theory models in equating for tests composed of testlets. Further, results of the study indicate that when sample size is large, item response theory models performed similarly to testlet response theory models across all studies.

Testlet Response Theory and Its Applications

2007 ◽  
Author(s):  
Howard Wainer ◽  
Eric T. Bradlow ◽  
Xiaohui Wang
Keyword(s):  
Response Theory ◽  
Testlet Response Theory
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