PISA Türkiye Uygulamalarında Düşük ve Temel Performans Düzeylerindeki Öğrenci Başarısının Yordayıcıları

Abstract

Bu çalışmanın amacı PISA 2012, 2015 ve 2018 yılları Türkiye uygulamalarında okuduğunu anlama alanında düşük ve temel performans düzeylerinde performans gösteren öğrencilerin, kendi özelliklerinin ve aile özelliklerinin yıldan yıla değişiminin tespit edilmesidir. Bu çalışma ilişkisel tarama modelinde tasarlanmıştır ve aynı zamanda bir ikincil veri analizi çalışmasıdır. Veri OECD resmi internet sayfasından elde edilmiştir. Veri çözümleme süreci için betimsel istatistikler ve lojistik regresyon analizi kullanılmıştır. Araştırma bulgularına dayalı olarak, düşük performans gösteren öğrencilerin yıldan yıla daha iyi eğitimli ve daha yüksek sosyoekonomik ve kültürel düzeye sahip olan ailelerden gelmeye başladıkları görülmektedir. Uygulama yılları boyunca öğrenciler için mevcut imkanlar gelişim göstermiştir. Lojistik regresyon analizi sonuçları her bir uygulama yılı için sınıflayıcı olan değişkenlerin çeşitli olduğunu ortaya çıkartmıştır. Anne eğitim düzeyi ve eğitsel yazılım gibi değişkenlerin yordayıcı rolüne ilişkin bazı bulguların alanyazınla çelişkili olduğu görülmüştür. Bulgulara dayalı yorumlar öğrenci düşük performansının en azından temel performans düzeyine doğru geliştirilebilmesi hususu göz önünde tutularak yapılmıştır.

Keywords

• Aile özellikleri
• Lojistik regresyon
• Düşük başarılı öğrenciler.

Predictors of Students’ Low and Basic Performance Levels in PISA Turkey Implementations

Abstract

The aim of this study is to determine the year-by-year change of family and student characteristics of whose performance is at or below basic proficiency level in domain of reading comprehension on PISA Turkey 2012, 2015 and 2018 implementations. This study is designed as a correlational survey research and also covers a secondary data analysis. Data was obtained from the official website of OECD. For data analysis, descriptive statistics and logistic regression analysis were used. Based on the research findings, it was seen that low performing students have started to come from better educated families as well as families with higher ESCS index. Resources available to students increased by years. Logistic regression analysis revealed that various variables are classifiers for students’ performance levels for each implementation years. Some findings are found to be contradictory with the literature such as predictive role of maternal education level and educational software. Suggestions are made based on the findings to improve students’ performances from low to at least basic proficiency levels.

Keywords

• Family characteristics
• Logistic regression
• Low performing students.

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