PISA 2015 Türkiye Çalışmalarının Karşılaştırmalı Bir İncelemesi: Uluslararası Büyük Ölçekli Değerlendirmeler için Değişken Seçim Yöntemi Önerisi

Öz

Uluslararası büyük ölçekli değerlendirmeler, eğitim, ekonomik ve politik sistemlerin iyileştirilmesinde önemli bir rol oynamaktadır. Ülkeler, bu değerlendirmelerin verilerini kullanarak, eğitim sistemlerinin mevcut durumu hakkında çıkarımlarda bulunmaktadır. Bu verileri kullanan bilimsel çalışmalar ve raporlar, genellikle veri setinde mevcut olan bazı değişkenleri seçerek bu değişkenler arasındaki ilişkileri modellemeyi amaçlar. Bu çalışmada, Türkiye PISA 2015 verisinin tamamını kullanarak ülke verilerini modellemede hangi değişkenlerin dahil edilebileceğine karar vermek amacıyla bir değişken seçim yöntemi denemeyi hedeflenmiştir. PISA 2015 verisinin tamamını kullanarak büzüşme regresyonlarından biri olan elastik net regresyonu kullanılmış ve elde edilen sonuçlar, Türkiye PISA 2015 verilerine dayalı mevcut çalışmaların sonuçları ile karşılaştırılmıştır. Analizler sonucunda, test kaygısı, çevresel farkındalık, geniş kapsamlı bilim konularına ilgi, okul sonrası video oyunları oynama, matematik okuryazarlığı, okuma okuryazarlığı ve işbirlikçi problem çözme becerilerinin öğrencilerin fen okuryazarlığı düzeyine en çok katkı sağlayan açıklayıcı değişkenler olduğu ortaya konulmuştur. Bu çalışma, eğitim bağlamında küçülme yöntemlerinin uygulanmasına bir örnek sunma potansiyeline sahip olup, hangi değişkenlerin dahil edilebileceğine yönelik bir gerekçe sunmak için alternatif bir bakış açısı önermektedir.

Anahtar Kelimeler

• PISA 2015
• Bilimsel Okuryazarlık
• Elastik Net Regresyonu
• Büzüşme tahminleyicisi

A Comparative Analysis of PISA 2015 Türkiye Studies: Introducing A Variable Selection Model to International Large-Scale Assessments

Öz

International large-scale assessments have a key role in improving educational, economical, and political systems. By using the data of these assessments, countries can draw conclusions about the status of educational systems. Studies and reports generally tend to choose variables available in data set to model the relationships among the variables. In this study, we aimed to introduce a variable selection method to analyze large-scale assessments to be able to decide which variables might be included in modelling country data. We used the entire data set of Türkiye PISA 2015 through elastic net regression to decide which variables should be selected for further analysis. We also provided a summary of the available studies based on Türkiye PISA 2015 data and compared the results. Based on the series of analyses, this study revealed that test anxiety, environmental awareness, interest in broad topics in science, playing video games after school, mathematics literacy, reading literacy, and collaborative problem-solving skills were the explanatory variables contributed most to the degree of scientific literacy of students. This study has a potential to provide an example of shrinkage methods applied in educational context and offer another standpoint for providing a rationale to select which variables can be included.

Anahtar Kelimeler

• PISA 2015
• Scientific Literacy
• Elastic Net Regression
• Shrinkage Methods

Kaynakça

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