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Özet
The purpose of this study was to conduct a real-time multidimensional computerized adaptive test (MCAT) using data from a previous paper-pencil test (PPT) regarding the grammar and vocabulary dimensions of an end-of-term proficiency exam conducted on students in a preparatory class at a university. An item pool was established through four separate 50-item sets applied in four different semesters. The fit between unidimensional, multi-unidimensional and bifactor IRT models was compared during item calibration, with the bifactor model providing the best fit for all data sets. This was followed by a hybrid simulation for 36 conditions obtained using six item selection methods, two ability estimation methods and three termination rules. The statistics and graphs obtained indicate D-rule item selection, maximum a posteriori (MAP) ability estimation and standard error termination rule as the best algorithm for the real-time MCAT application. With the minimum number of items to be administered determined as 10, the real-time application conducted on 99 examinees yielded an average number of items of 13.4. The PPT format proficiency exam consists of 50 items, leading to the conclusion that the examinees participating in the real-time MCAT are administered an average of 74.4% fewer items than the PPT. Additionally, 86 of the examinees answered between 10-13 items. The item pool use rate is 30%. Lastly, the correlation between the PPT scores and general trait scores of 32 examinees was calculated as .77.
Abstract
The purpose of this study was to conduct a real-time multidimensional computerized adaptive test (MCAT) using data from a previous paper-pencil test (PPT) regarding the grammar and vocabulary dimensions of an end-of-term proficiency exam conducted on students in a preparatory class at a university. An item pool was established through four separate 50-item sets applied in four different semesters. The fit between unidimensional, multi-unidimensional and bifactor IRT models was compared during item calibration, with the bifactor model providing the best fit for all data sets. This was followed by a hybrid simulation for 36 conditions obtained using six item selection methods, two ability estimation methods and three termination rules. The statistics and graphs obtained indicate D-rule item selection, maximum a posteriori (MAP) ability estimation and standard error termination rule as the best algorithm for the real-time MCAT application. With the minimum number of items to be administered determined as 10, the real-time application conducted on 99 examinees yielded an average number of items of 13.4. The PPT format proficiency exam consists of 50 items, leading to the conclusion that the examinees participating in the real-time MCAT are administered an average of 74.4% fewer items than the PPT. Additionally, 86 of the examinees answered between 10-13 items. The item pool use rate is 30%. Lastly, the correlation between the PPT scores and general trait scores of 32 examinees was calculated as .77.