PISA 2018 TÜRKİYE MATEMATİK OKURYAZARLIĞINI AÇIKLAYAN DEĞİŞKENLERİN CHAID ANALİZİ İLE İNCELENMESİ

Year 2023, Volume: 7 Issue: 4, 1042 - 1063, 31.12.2023

Evrim Yalçın Şerife Zeybekoğlu Ayşe Bilicioğlu Güneş Ömay Çokluk-bökeoglu

https://doi.org/10.47525/ulasbid.1386408

Abstract

Bu çalışmanın amacı, Türk öğrencilerin Uluslararası Öğrenci Değerlendirme Programı (PISA) 2018 öğrenci anketine verdikleri yanıtlarla matematik okuryazarlığını açıklayan değişkenleri incelemektir. Çalışmanın konusu, eğitim sisteminde tespit edilecek eksikliklerin giderilerek gerekli önlemlerin alınabilmesi için bulgular sağlayacak olması yönüyle önemlidir. İlişkisel tarama modelinde gerçekleştirilen araştırmanın Türkiye örneklemini tabakalı örnekleme deseniyle seçilen 6890 öğrenci oluşturmaktadır. Araştırmanın örneklemini eksik değerleri içeren veriler çıkarıldıktan sonra kalan 5293 kişi oluşturmaktadır. Bu çalışmada veri analizi için veri madenciliği karar ağacı algoritmalarından biri olan Ki-kare Otomatik Etkileşim Tespiti (CHAID) yöntemi kullanılmıştır. Analiz sonucunda Türk öğrencilerin matematik okuryazarlığını en iyi açıklayan değişkenin “evdeki kitap sayısı” olduğu sonucuna ulaşılmıştır. Öğrencilerin Baba Eğitim Düzeyi, En Yüksek Ebeveyn Eğitim Seviyesi, Okulda ve Evde BİT Erişebilirliği, Matematik Dersi için Haftada Ayrılan Öğrenme Zamanı da matematik okuryazarlığını açıklayan diğer değişkenler olarak bulunmuştur.

Keywords

PISA, matematik okuryazarlığı, veri madenciliği, CHAID analizi

THE EXAMINATION OF VARIABLES EXPLAINING MATHEMATICS LITERACY BY CHAID ANALYSIS: PISA 2018 TURKEY

Abstract

This study aims to investigate the variables explaining mathematics literacy of Turkish students who attended at Programme for International Student Assessment (PISA). The topic of the study is at utmost importance due to the potential findings that will identify the variables influencing mathematical literacy in our education system and generate recommendations aimed at addressing shortcomings.This study utilizes the answers given to the PISA student questionnaire, which are analysed by correlational survey design.Stratified sampling design is used in the selection of 6890 students in Turkish sample. After excluding the missing data, the sample of the study consists of 5293 participants. Chi-squared Automatic Interaction Detection (CHAID) method, which is one of the data mining decision tree algorithms, is used for data analysis. According to the results of the study, the most important variable explaining Turkish students’ mathematic literacy is the number of the books at home. Father’s education level, highest parental education level, accessibility of ICT both at home and school, and time allocated per week to study mathematics are other variables explaining mathematics literacy.

Keywords

PISA, mathematics literacy, data mining, CHAID analysis

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