Mesleki Eğitim ve Ortaöğretim Okullaşmasının Mekânsal Örüntüleri: Türkiye İl Düzeyinde Moran I, LISA Ve Coğrafi Ağırlıklı Regresyon İle Mekânsal Durağanlık Sınaması

Abstract

Bu çalışma, MEB 2024-25 Örgün Eğitim İstatistikleriyle 81 ilde mesleki eğitim oranının mekânsal dağılımını ve ortaöğretim okullaşmasıyla ilişkisini incelemektedir. Global Moran I, LISA, Lagrange Çarpanı (LM) testleri, mekânsal gecikme modeli ve Coğrafi Ağırlıklı Regresyon (CAR) uygulanmıştır. Mesleki eğitim oranı (I=0,179, p<0,01) ve ortaöğretim okullaşması (I=0,611, p<0,001) anlamlı pozitif mekânsal otokorelasyon göstermektedir. LISA, okullaşmada Güneydoğu ve Doğu Anadolu’da on iki illik bir düşük-düşük kümesi saptamıştır; ortalaması %74,5 ile ülke ortalamasının 14,5 puan altındadır. LM hiyerarşisi mekânsal gecikme modelini işaret etmekte; gecikme katsayısı 0,505 (p<0,001) ve artıklardaki otokorelasyon kaybolmaktadır. CAR uyumu iyileştirse de (R²: 0,603'ten 0,662'ye) mesleki eğitim katsayısı hiçbir ilde anlamlı değildir ve değişkenliği de anlamsızdır (Monte Carlo p=0,849). Buna karşılık cinsiyet uçurumu katsayısı 39 ilde anlamlıdır ve değişkenliği anlamlı çıkmaktadır (p=0,002). Bulgular iki metodolojik sonucu birlikte ortaya koymaktadır: model uyumundaki iyileşme tek başına mekânsal heterojenlik kanıtı değildir, heterojenliğin yokluğu da her katsayı ayrı sınanmadan ilan edilemez.

Keywords

• Mesleki eğitim
• Ortaöğretim okullaşma
• Mekânsal otokorelasyon
• LISA
• Coğrafi ağırlıklı regresyon
• Mekânsal durağanlık

Ethical Statement

Bu çalışmanın hazırlanma sürecinde bilimsel araştırma ve yayın etiği ilkelerine riayet edilmiş; yararlanılan tüm kaynaklar eksiksiz biçimde kaynakçada belirtilmiştir.

Spatial Patterns of Vocational Education and Upper-Secondary Enrollment in Turkey: Testing Spatial Stationarity with Moran's I, LISA, and Geographically Weighted Regression

Abstract

This study examines the spatial distribution of the vocational education ratio and its relationship with upper-secondary enrollment across 57 Turkish provinces using Ministry of National Education (MoNE) Formal Education Statistics for 2024-25. Global Moran's I and Local Indicators of Spatial Association (LISA) identify spatial clustering patterns; Lagrange Multiplier (LM) tests guide model selection; Geographically Weighted Regression (GWR) tests the spatial stationarity assumption. Both the vocational education ratio (I=0.171, p<0.01) and upper-secondary enrollment (I=0.210, p<0.01) exhibit significant positive spatial autocorrelation. LISA analysis identifies a low-low (LL) cluster of eight provinces located in the transition zone between the Mediterranean and Central Anatolia regions. Although GWR improves model fit (R²: 0.452 to 0.573), none of the local coefficients exceed the corrected significance threshold, and Monte Carlo tests indicate that coefficient variability is not statistically significant (p=0.485 for vocational education). This finding constitutes a methodological caution: improvement in model fit alone cannot be treated as evidence of spatial heterogeneity.

Keywords

• Vocational education
• Upper-secondary enrollment
• Spatial autocorrelation
• LISA
• Geographically weighted regression
• Spatial stationarity

Ethical Statement

The author confirms that this study was conducted inaccordance with the principles of academic research andpublication ethics, and that all sources used areappropriately cited.

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