İçerik Ağırlıklandırmasının Maddeler-Arası Boyutluluk Modeline Dayalı Çok Boyutlu Bilgisayar Ortamında Bireyselleştirilmiş Test Yöntemleri Üzerindeki Etkisinin İncelenmesi

• Main Authors: Burhanettin Özdemir, Selahattin Gelbal
• Format: Article
• Language: English
• Published: EPODDER 2015-11-01
• Series: Journal of Measurement and Evaluation in Education and Psychology
• Subjects: : Multidimensional adaptive testing; between-item dimensionality model; content balancing
• Online Access: http://dergipark.ulakbim.gov.tr/epod/article/view/5000156293

The purpose of this study is to compare the performance of Between-item dimensionality-based Multidimensional CAT designs and to examine the effect of content balancing on different MCAT designs. For this purpose, real data set obtained from English Proficiency Test (EPT), which was administered by Hacettepe University between 2009 and 2013 academic years, was used. The three dimensional item pool consisted of real items measuring students’ listening, grammar and reading abilities. Item pool consisted of 555 items which was calibrated with 2PL between-item MIRT model. In this study, two different theta estimation (Fisher scoring and Bayesian MAP) methods, three different fisher information based item selection methods (A-optimality, D-optimality and Random) and three different precision based termination methods were used in order to determine the best MCAT design. In addition, results of MCAT algorithms with content distribution and without content distribution were compared so as to examine the effect of content balancing in the context of MCAT. The results of each MCAT condition were compared with respect to, reliability index, SEM, RMSD values associated with each dimension. According to results, both Bayesian MAP and Fisher’s scoring methods yielded similar results when A-Optimality item selection method was used. However, Fisher’s scoring method appeared to be affected from item selection methods and content balancing. Moreover, average number of items tended to increase and reliability coefficients tended to decrease somewhat, while standard error and RMSD values tended to decrease when content balancing was applied in MCAT.