In this study, it was aimed to scale the importance level of the criteria that can be taken into consideration in determining the exam anxiety of 8 th grade students by means of pairwise comparison. Descriptive survey model was used in the research. The study group of the research consists of 100 8 th grade students studying at a randomly selected secondary school in Kilis. The data collection tool was a questionnaire in which the students in the study group were compared in pairs, that consisted of six criteria that affect exam anxiety, including the thought of failing in lessons, the effect of the social environment (family, friends and relatives), students's self-perceptions, teacher attitudes, social and physical characteristics of the school, and the thought of not being prepared for exams adequately. Data analysis was performed on a full data matrix by using equation of case III. As a result of the research, the first two criteria that most affect the exam anxiety of 8 th grade students are respectively; social and physical characteristics of the school and how students see themselves. These stimulators are respectively followed by the idea of failing in lessons and the effect of the social environment. The two criteria, which they think are the least effective on exam anxiety, are the attitudes of teachers and not being prepared for exams adequately.

The present study aims to compare the Kernel equating and Kernel local equating methods in observed score equating. Functions and error estimates regarding the difference between raw and equated scores and the scores equated by Stocking-Lord and Haebara true-score equating methods in Kernel local equating and Kernel equating were examined in Item Response Theory Observed Score Equating. Therefore, 5, 10, and 15 external anchor items were used, and scores were obtained from two forms based on the 2PL model. R (version 3.5.3.) programming software was used for IRT assumptions, item parameters, calibration, and equating analyses. The results revealed that Stocking-Lord and Haebara true-score equating methods yielded similar results. Moreover, if the equating method is the same, estimation errors decreased when the number of anchor items increased. The mean scores obtained by Kernel equation 5 and 15 anchor items were lower than Kernel local equating, while means of Kernel equating of 10 anchor items were higher. As the number of items increased, estimation errors decreased, and Kernel local equating revealed the lowest errors in the medium score scale. Kernel equating can be used based on the related ability level if the individual's ability distribution is known.