Öğretmen Adaylarında Yapay Zeka Farkındalığının Demografik Değişkenler ve Kümeleme Analizi ile İncelenmesi

Öz

Bu çalışma, Mersin Üniversitesi'ndeki öğretmen adaylarının yapay zeka (YZ) farkındalık düzeylerini araştırarak, YZ bilgi ve tutumlarındaki farklılıkları incelemek için hem betimsel hem de çıkarımsal analizler kullanmaktadır. Eğitime YZ'nin giderek daha fazla entegre edilmesiyle, eğitimcilerin YZ okuryazarlığı düzeylerinin anlaşılması kritik bir önem taşımaktadır. Çalışmada, 117 öğretmen adayı, Pratik Bilgi, İnanç ve Tutumlar, Birleştirici Tutum ve Teorik Bilgi boyutlarını ölçen Öğretmenler için Yapay Zeka Farkındalık Ölçeği'ni tamamlamıştır. Demografik değişkenler (cinsiyet, bölüm ve teknoloji kullanım süresi) bazında YZ farkındalık düzeylerini değerlendirmek için betimsel istatistiklerin yanı sıra bağımsız örneklem t-testleri, ANOVA ve Mann-Whitney U testleri uygulanmıştır. Ayrıca, katılımcılar arasında gerçekleştirilen kümeleme analizi sonucunda üç farklı grup ortaya çıkmıştır: (1) tüm boyutlarda ortalama yapay zekâ farkındalığına sahip, orta düzey farkındalık kümesi; (2) sınırlı yapay zekâ bilgisi ve nötrden olumsuza doğru tutum sergileyen, düşük düzey farkındalık kümesi; ve (3) güçlü yapay zekâ bilgisine ve yapay zekâya yönelik olumlu tutumlara sahip, yüksek düzey farkındalık kümesi. Bulgular, teknoloji kullanımının öğretmen adaylarının yapay zekâ farkındalık düzeyleri üzerinde anlamlı bir etkisi olduğunu; ancak cinsiyet ve akademik bölüm gibi demografik faktörlerin anlamlı bir farklılığa neden olmadığını göstermektedir. Elde edilen sonuçlar, öğretmen yetiştirme programları içinde farklı düzeylerdeki yapay zekâ farkındalığına sahip gruplara göre özelleştirilmiş eğitimlere ihtiyaç duyulduğunu, bu bağlamda düşük farkındalığa sahip gruplar için temel düzey yapay zekâ okuryazarlığı eğitiminin, daha yüksek farkındalığa sahip gruplar için ise ileri düzey içeriklerin sunulması gerektiğini ortaya koymaktadır. Bu çıkarımlar, geleceğin eğitimcilerinin sınıflarında yapay zekâ teknolojilerini etkin biçimde kullanmalarına yönelik adaptif öğretim uygulamalarının geliştirilmesine destek sağlayabilir.

Anahtar Kelimeler

• Yapay zeka farkındalığı
• öğretmen adayları
• kümeleme analizi
• öğretmen eğitimi
• eğitimde teknoloji entegrasyonu

Investigation of Artificial Inteligence Awareness Among Pre-Service Teachers With Cluster Analysis

Öz

This study investigates the patterns of artificial intelligence (AI) awareness among pre-service teachers at Mersin University, using both descriptive and inferential analyses to examine the levels of knowledge and attitudes towards AI. Understanding educators' AI awareness is essential as AI is increasingly integrated into education. A sample of 117 pre-service teachers completed the Artificial Intelligence Awareness Scale for Teachers, measuring Practical Knowledge, Beliefs and Attitudes, Attitude to Association, and Theoretical Knowledge. Statistical analysis were conducted to assess differences in AI awareness across demographic variables, including gender, academic department, and technology use. In addition, cluster analysis was performed, revealing three distinct clusters: (1) a moderate-awareness cluster, characterized by average levels of AI knowledge and attitudes across all dimensions; (2) a low-awareness cluster, characterized by limited AI knowledge and neutral-to-negative attitudes; and (3) a high-awareness cluster, characterized by strong AI knowledge and positive attitudes toward artificial intelligence. The findings that technology usage significantly influences pre-service teachers' AI awareness levels, whereas demographic factors such as gender and academic department do not. The results emphasize the need for differentiated AI training within teacher preparation programs, suggesting foundational AI literacy training for lower-awareness groups and more advanced content for those already possessing higher awareness.

Anahtar Kelimeler

• Artificial intelligence awareness
• pre-service teachers
• cluster analysis
• teacher education
• technology integration in education.

Kaynakça

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