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    An Investigation of Item Position Effects by Means of IRT-Based Differential Item Functioning Methods
    (Izzet Kara, 2021) Soysal, Sumeyra; Kogar, Esin Yilmaz
    In this study, whether item position effects lead to DIF in the condition where different test booklets are used was investigated. To do this the methods of Lord's chi-square and Raju's unsigned area with the 3PL model under with and without item purification were used. When the performance of the methods was compared, it was revealed that generally, the method of Lord's chi-square identified more items with DIF than did the method of Raju's unsigned area. The differentiation of the booklets with respect to item position resulted in a higher number of items displaying DIF with item purification conditions. Based on the findings of the present study, to avoid the occurrence of DIF due to item position effects, it is recommended to position the same items across different booklets in similar locations when forming different booklets.
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    Examination of response time effort in TIMSS 2019: Comparison of Singapore and Türkiye
    (Izzet Kara, 2023) Kogar, Esin Yilmaz; Soysal, Sumeyra
    In this paper, it is aimed to evaluate different aspects of students' response time to items in the mathematics test and their test effort as an indicator of test motivation with the help of some variables at the item and student levels. The data consists of 4th -grade Singapore and Turkish students participating in the TIMSS 2019. Response time was examined in terms of item difficulties, content and cognitive domains of the items in the mathematics test self -efficacy for computer use, home resources for learning, confident in mathematics, like learning mathematics, and gender variables at the student level. In the study, it was determined that all variables considered at the item level affected the response time of the students in both countries. It was concluded that the amount of variance explained by the student -level variables in the response time varied for each the country. Another finding of the study showed that the cognitive level of the items positively related to the mean response time. Both Turkish and Singaporean students took longer to respond to data domain items compared to number and measurement and geometry domain items. Additionally, based on the criterion that the response time effort index was less than .8, rapid -guessing behavior, and therefore low motivation, was observed below 1% for both samples. Besides, we observed that Turkish and Singaporean students were likely to have rapid guessing behavior when an item in the reasoning domain became increasingly difficult. A similar result was identified in the data content domain, especially for Turkish graders.
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    Item parameter recovery via traditional 2PL, Testlet and Bi-factor models for Testlet-Based tests
    (Ijate-Int Journal Assessment Tools Education, 2022) Soysal, Sumeyra; Kogar, Esin Yilmaz
    The testlet comprises a set of items based on a common stimulus. When the testlet is used in the tests, there may violate the local independence assumption, and in this case, it would not be appropriate to use traditional item response theory models in the tests in which the testlet is included. When the testlet is discussed, one of the most frequently used models is the testlet response theory (TRT) model. In addition, the bi-factor model and traditional 2PL models are also used for testlet-based tests. This study aims to examine the item parameters estimated by these three calibration models of the data properties produced under different conditions and to compare the performances of the models. For this purpose, data were generated under three conditions: sample size (500, 1000, and 2000), testlet variance (.25, .50, and 1), and testlet size (4 and 10). For each simulation condition, the number of items in the test was fixed at i = 40 and 100 replications were made under each condition. Among these models, it was concluded that the TRT model gave less biased results than the other two models, but the results of the bi-factor model and the TRT were more similar as the sample size increased. Among the examined conditions, it was determined that the most effective variable in parameter recovery was the sample size.