Eren Halil Özberk

Dezavantajlı Yüksek Başarılı Öğrencilerin Okul ve Öğrenci Düzeyinde Matematik Başarılarını Etkileyen Değişkenlerin İncelenmesi

The main aim of the study is to investigate how the opportunity to learn, school climate, and school resources, when they are considered as variables together, affect the Math achievement of resilient Turkish students by using a Hierarchical Linear Model (HLM). Recent studies state that resilient students are achieving higher than their peers who have low socio-economic status. Therefore, it is important to find out the variables which affect the achievement of students who have a low socio-economic status. In the study, the main characteristics of resilient students are revealed through a literature review in this field; and a model is formed through the factors which affect achievement levels generally at both school and student levels. The study group includes 317 students who are defined as resilient in the PISA 2012 Turkish sample. According to the results of the study, at student level, the variables of Experience with Applied Mathematical Tasks and Mathematics Teaching ; and at school level, the variables of Quality of School Educational Resources and Student-related Factors Affecting School Climate are found to be effective in the mean math achievement of resilient students. When the models are examined, in the one including both school and student level variables together, it is determined that the variables of Experience with Applied Mathematical Tasks, Quality of School Educational Resources and Student-related Factors Affecting School Climate explain 44% of the variability between schools. Besides, it can be seen in the study that the variables at student level have partially meaningful effects.

Software Review of flexMIRT Version 3.5

flexMIRT is a versatile program for unidimensional and multidimensional item response theory (IRT) calibrations, scoring analyses, and model-based simulations. With an adaptable syntax that allows for various combinations of model specifications, estimation constraints, and estimation choices, flexMIRT can handle almost all of the most popular IRT models for dichotomous and polytomous data. The software package also supports diagnostic classification models and multigroup and multilevel analyses. This review evaluates the software from a user’s perspective as well as some of its calibration, scoring, and simulation capabilities. Two simulation studies are included: one demonstrates some basic simulation capabilities and the other provides some direct comparisons with BILOG-MG. The review suggests that flexMIRT is a very good product that is only likely to get better as new features and suggestions for improvement are implemented.