Exploring Preservice Science Teachers’ AI-TPACK Competencies and Perceptions of Artificial Intelligence in Education

Abstract

The primary purpose of this study is to investigate preservice science teachers’ competencies related to AI-TPACK and their perceptions regarding the use of artificial intelligence in education. By examining these constructs, the study aims to provide insights into how preservice teachers integrate AI into their pedagogical and content knowledge and how their perceptions influence this process. This study adopted a quantitative survey research design. Specifically, two standardized instruments, the AI-TPACK and Perceptions of Artificial Intelligence in Education (PAI) scales, were administered simultaneously to preservice science teachers. The participants of this study consisted of 122 undergraduate students enrolled in the science education program at the faculty of education of a public university. The findings indicate that preservice science teachers’ overall performance on the AI-TPACK scale reflected moderate competency in integrating AI into pedagogical practices. The highest mean scores highlighted willingness to integrate AI technologies into self directed learning, self-efficacy in enhancing conceptual understanding, and competence in using AI-based simulations. The findings revealed that preservice science teachers’ overall results on the PAI indicated generally positive perceptions toward AI integration in education. Preservice science teachers particularly valued AI’s contribution to efficiency, rapid assessment, and ease of access to information while noting potential drawbacks such as reduced student engagement and dependency. The analysis revealed a statistically significant positive correlation between preservice teachers’ AI-TPACK competencies and their perceptions of AI. Results also indicated that male preservice teachers scored significantly higher in several AI-TPACK subscales. At the same time, prior AI training enhanced technological knowledge but did not necessarily improve pedagogical or content-related competencies. Overall, the findings highlight the need for targeted training opportunities emphasizing hands-on, pedagogically integrated use of AI to foster more comprehensive AI-TPACK competencies.

Keywords

• Preservice Science Teachers
• Artificial Intelligence in Education
• AI-TPACK
• Perceptions of AI.

Fen Bilimleri Öğretmen Adaylarının YZ-TPAB Yeterlikleri ve Eğitimde Yapay Zekaya İlişkin Algılarının İncelenmesi

Abstract

Bu çalışmanın temel amacı, fen bilimleri öğretmen adaylarının yapay zeka teknolojik pedagojik alan bilgisi (AI-TPACK) yeterliklerini ve eğitimde yapay zeka kullanımına ilişkin algılarını (PAI) incelemektir. Bu amaç doğrultusunda öğretmen adaylarının yapay zekayı teknolojik pedagojik alan bilgileriyle nasıl bütünleştirdikleri ve algılarının bu süreci nasıl etkilediğini incelemek hedeflenmiştir. Araştırmada nicel tarama deseninden yararlanılmıştır. Bu kapsamda, AI-TPACK ve PAI ölçekleri fen bilimleri öğretmen adaylarına eşzamanlı olarak uygulanmıştır. Araştırmanın çalışma grubunu, bir devlet üniversitesinin eğitim fakültesi fen bilimleri öğretmenliği programına kayıtlı 122 lisans öğrencisi oluşturmaktadır. Bulgular, fen bilgisi öğretmen adaylarının AI-TPACK ölçeğinde yapay zekayı teknolojik pedagojik alan uygulamalarına entegre etme konusunda orta düzeyde yeterlik sergilediklerini ortaya koymuştur. En yüksek ortalama puanlar, öğretmen adaylarının yapay zeka teknolojilerini öz düzenlemeli öğrenmeye entegre etme isteklilikleri, kavramsal anlamayı geliştirme konusundaki özyeterlikleri ve yapay zeka tabanlı simülasyonları kullanma becerileri üzerine yoğunlaşmıştır. Bulgular ayrıca, PAI ölçeği sonuçlarının öğretmen adaylarının genel olarak eğitimde yapay zeka entegrasyonuna ilişkin olumlu algılara sahip olduklarını göstermiştir. Fen bilimleri öğretmen adayları özellikle yapay zekanın verimlilik, hızlı değerlendirme ve bilgiye erişimde kolaylık sağlama katkılarını değerli bulurken; öğrenci katılımında azalma ve bağımlılık gibi potansiyel olumsuzlukları da vurgulamışlardır. Analizler, öğretmen adaylarının AI-TPACK yeterlikleri ile yapay zekaya ilişkin algıları arasında istatistiksel olarak anlamlı ve pozitif bir ilişki bulunduğunu ortaya koymuştur. Ayrıca, erkek öğretmen adaylarının AI-TPACK ölçeğinin bazı alt boyutlarında anlamlı biçimde daha yüksek puanlar aldıkları belirlenmiştir. Diğer taraftan, önceki yapay zeka eğitiminin teknolojik bilgiyi artırdığı, ancak pedagojik ya da alan bilgisi ile ilgili yeterlikleri yeterince geliştirmediği saptanmıştır. Genel olarak bulgular, AI-TPACK yeterliklerini daha kapsamlı biçimde geliştirmek için uygulamalı ve pedagojik bütünleşmeye dayalı branşa özel eğitim fırsatlarının gerekliliğine işaret etmektedir.

Keywords

• Fen Bilimleri Öğretmen Adayları
• Eğitimde Yapay Zeka
• Yapay Zeka Teknolojik Pedagojik Alan Bilgisi (YZ-TPAB)
• Yapay Zekaya İlişkin Algı

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