ÖZBu çalışmanın amacı açımlayıcı faktör analizinde kullanılan faktör çıkartma yöntemlerini açıklanan varyans ve çıkartılan faktör sayısı bakımından çeşitli örneklem büyüklüğü ve ortak varyans düzeyi koşullarına göre karşılaştırmaktır. Bu çalışma bir simülasyon (benzetim) çalışmasıdır. Bu bağlamda çalışmada kullanılacak veriler SAS programı kullanılarak örneklem büyüklüğüne (100, 500), ortak varyans düzeylerine (yüksek [0.6-0.8], geniş [0.2-0.8], düşük [0.2-0.4]), sabit faktör sayısına (3), sabit değişken sayısına (20) göre 1000 replikasyonla korelasyon matrisleri biçiminde üretilmiştir. Yapılan karşılaştırmalar sonucunda ortak varyansı yüksek veya düşük olarak üretilen veri için örneklem büyüklüğü arttıkça, açıklanan varyans miktarı da artmaktadır. Fakat ortak varyansı geniş olarak üretilen veri grubu için örneklem büyüklüğü arttıkça açıklanan toplam varyansın azaldığı görülmüştür. Analiz edilen tüm durumlarda toplam varyansı en yüksek açıklayan yöntemin temel bileşen analizi ve en düşük açıklayan yöntemin ise imaj faktör yöntemi olduğu gözlenmiştir. Faktör yükleri bakımından yapılan karşılaştırmalara göre temel bileşen analizi her durum için en yüksek faktör yükünü çıkartmıştır. Öte yandan imaj faktör yöntemi ise en düşük faktör yükünü çıkartmıştır. Ortak varyansın geniş aralıkta ya da yüksek aralıkta üretildiği veri için yöntemler arasında faktör sayıları bakımından bir farklılık yoktur. Ortak varyansın düşük olduğu ve örneklem büyüklüğünün küçük olduğu gruplar için imaj faktör yöntemi istenilen faktör sayısını çıkartamamıştır. Dolayısıyla örneklem sayısının ve ortak varyansın düşük olduğu gruplar için imaj faktör yönteminin kullanılması önerilmemektedir. ABSTRACTThe purpose of this study was to compare factor extraction methods used in exploratory factor analysis in terms of variance and factor number according to sample size and the communality level conditions. In this simulation study, data were generated with respect to two levels of sample sizes (100, 500), three levels of communality (high, wide and low), with 20 variables, 3 factors, and Karaman, Atar & Çobanoğlu Aktan 1174 1000 replications by using SAS program. As a resut of comparisons, it was found that total explained variance increased when sample size increased for data with high or low communality levels. However, total explained variance decreased when sample size increased, for the data with wide communality level. Component analysis yielded the biggest total explained variance compared to other methods, whereas image analysis yielded the lowest explained variance. The rest of the factor extracting methods provided the similar results to each other. Component analysis produced the biggest factor loadings and image analysis yielded the lowest factor loadings and there was no difference concerning factor loadings for the remaining methods. For the data generated with high and wide communality levels, no difference was observed among the extraction methods in terms of number of factors. However, for data generated with low communality level image...

Conceptual understanding is one of the main topics in science and physics education research. In the majority of conceptual understanding studies, students’ understanding levels were categorized dichotomously, either as alternative or scientific understanding. Although they are invaluable in many ways, namely developing new instructional materials and assessment instruments, students’ alternative understandings alone are not sufficient to describe students’ conceptual understanding in detail. This paper introduces an example of a study in which a method was developed to assess and describe students’ conceptual understanding beyond alternative and scientific understanding levels. In this study, six undergraduate students’ conceptual understanding levels of direct current electricity concepts were assessed and described in detail by using their answers to qualitative problems. In order to do this, conceptual understanding indicators are described based on science and mathematics education literature. The students’ understanding levels were analysed by assertion analysis based on the conceptual understanding indicators. The results indicated that the participants demonstrated three intermediate understanding levels in addition to alternative and scientific understanding. This paper presents the method and its application to direct current electricity concepts.

The purpose of this study was to investigate pre-service science teachers’ understanding levels of Kepler’s second and third laws. The participants of the study were 38 pre-service science teachers who attended introductory astronomy class in their teacher education program. The participants’ understandings of Kepler’s laws were examined by their answers to ranking tasks, which required participants to rank the situations given in the question, and then to explain the reasons behind their answers. The findings showed that the participants’ understanding levels ranged from partial understanding with alternative conceptions to sound understanding. Moreover the number of the participants with partial understanding with alternative conceptions exceeded the participants with sound understanding. The participants’ explanations to ranking tasks also indicated that although participants knew the classic statements of Kepler’s laws, they had also alternative conceptions. Five different alternative conceptions were identified from the participants’ explanations. Two of them have not been reported in previous studies. Key words: Kepler’s laws, pre-service science teachers, ranking tasks, understanding levels.

An absence of a scale for measuring exposure to the English language, which has a significant effect on English achievement, was detected in the literature. For this reason, in this study, a six-dimensional scale was developed to detect the level of English language exposure and its construct validity was tested. The factor structure of the scale was determined by exploratory factor analysis with the data collected from 784 university students, 726 of whom are undergraduate and 58 of whom are Master's and Ph.D. students. Confirmation of the factor structure of the scale was carried out with a measurement model specified in a structural equation model. A structural equation modeling study was performed along with 233 students from English preparation classes at a university. In the structural model, the effect of exposure to English on the students' scores received from writing in English, speaking in English and the total score (grammar, vocabulary, reading and listening scores) was examined. It was found that exposure to English has a significant effect on all of the three variables. Exposure to English explained the variance of the speaking variable most, while that effect is the least for the writing variable.

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