Yapay Zekâ Öğrenme Niyeti Ölçeği’nin Türk Kültürüne Uyarlanması: Geçerlik ve Güvenirlik Çalışması

Abstract

Bu çalışmada Chai ve ark. tarafından geliştirilen Yapay Zekâ Öğrenme Niyeti Ölçeği'nin Türkçe'ye uyarlanması ve psikometrik özelliklerinin öğretmen adayı ve öğretmen adaylarından oluşan bir örneklemde incelenmesi amaçlanmıştır. Uyarlama sürecinde dilsel eşdeğerliği sağlamak amacıyla çift yönlü çeviri yöntemi kullanılmış ve içerik geçerliliğini sağlamak amacıyla uzman görüşlerine başvurulmuştur. Ölçeğin yapısını incelemek amacıyla 403 öğretmen adayı ile açımlayıcı faktör analizi (AFA) ve 419 ortaokul öğretmeni ile doğrulayıcı faktör analizi (DFA) yapılmıştır. Öğretmen adayları yeni teknolojilere açık olmaları nedeniyle AFA için seçilirken, öğretmen adayları ise istikrarlı mesleki tutumları nedeniyle DFA için seçilmiştir. AFA sonuçlarına göre ölçeğin toplam varyansın %62,44'ünü açıkladığı görülmüştür. DFA bulguları iyi bir model uyumunu doğrulamıştır (örn., χ²/sd = 2,81, RMSEA = .066, CFI = .96). Cronbach alfa, Omega, Guttman ve Spearman-Brown katsayıları kullanılarak yapılan güvenilirlik analizleri .70 ile .85 arasında değişmiştir. Alt boyutlar arasındaki korelasyonlar ise .202 ile .456 arasında değişmiştir. Genel olarak, bulgular ölçeğin Türkçe versiyonunun hem hizmet öncesi hem de hizmet içi öğretmenler arasında yapay zekâ öğrenme niyetini değerlendirmek için geçerli ve güvenilir bir araç olduğunu göstermiştir.

Keywords

• Ölçek Uyarlama
• Yapay Zekâ
• Yapay Zekâ Öğrenme Niyeti.

Adaptation of Artificial Intelligence Learning Intention Scale to Turkish Culture: Validity and Reliability Study

Abstract

This study aimed to adapt the Artificial Intelligence Learning Intention Scale, originally developed by Chai et al., into Turkish and to examine its psychometric properties in a sample of pre-service and in-service teachers. During the adaptation process, the bidirectional translation method was used to ensure linguistic equivalence, and expert opinions were consulted to establish content validity. To examine the scale’s structure, exploratory factor analysis (EFA) was conducted with 403 pre-service teachers, while confirmatory factor analysis (CFA) was performed with 419 in-service secondary school teachers. Pre-service teachers were selected for EFA due to their receptiveness to new technologies, whereas in-service teachers were chosen for CFA because of their stable professional attitudes. The EFA results indicated that the scale explained 62.44% of the total variance. CFA findings confirmed a good model fit (e.g., χ²/df = 2.81, RMSEA = .066, CFI = .96). Reliability analyses using Cronbach’s alpha, Omega, Guttman, and Spearman-Brown coefficients ranged from .70 to .85. Correlations between sub-dimensions varied from .202 to .456. Overall, the findings demonstrated that the Turkish version of the scale is a valid and reliable instrument for assessing AI learning intention among both pre-service and in-service teachers.

Keywords

• Artificial Intelligence
• Artificial Intelligence Learning Intention
• Scale Adaptation.

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