Yapay Zekâ-Eğitim İlişkisine Bütüncül Bakış: Bir Bilim Haritalama Çalışması

Year 2024, Volume: 12 Issue: 3, 1080 - 1114, 30.11.2024

Salih Bardakcı

https://doi.org/10.46778/goputeb.1522277

Abstract

Araştırmada bilimsel anlamda yapay zekâ-eğitim ilişkisinin hangi ortak kavramlar ekseninde gelişmekte olduğu incelenmektedir. Bu amaçla bilim haritalama yönteminden yararlanılmaktadır. Veriler Web of Science-Core Collection’dan elde edilmiştir. Tarama terimleri içerisinde “yapay zekâ”, “eğitim”, “öğretim”, “öğretme”, ayrıca “OpenAI”, “ChatGPT” ve “Chatbot” yer almıştır. Böylece erişilen 14.682 bilimsel metne ilişkin bibliyografik bilgi araştırmanın veri setini oluşturmuştur. Analizler VOSviewer yazılım aracı üzerinde gerçekleştirilmiştir. Veri üzerinde ortak bulunuşluk analizleri yürütülmüştür. Bu analizler sonucunda hem ortak bulunuşluk haritalarına hem de detaylı dökümlere erişilmiştir. Bu dökümlerden de yararlanılarak haritadaki genel ve güncel kavramlar belirlenmiştir. Araştırma sonuçlarına göre yapay zekâ-eğitim ilişkisi teknoloji ya da araç bağlamından çok bir öğretim yöntemi bağlamı içerisinde tartışılmaktadır. Bu tartışma özellikle son yıllarda ilişkili alanlar, öğrenme ortamı/bağlamı, öğrenme-öğretmeye ilişkin konular/beceriler ve araştırma gibi boyutlarda zenginleşmekte ve derinleşmektedir. Bu zenginlik; yapay zekâ-eğitim ilişkisini pedagojik entegrasyon, uygulanabilirlik ve etik gibi açılardan desteklemektedir. Bu ilişkinin kuramsal temellerini eğitim teknolojisi alanı ile bağlantılı biçimde ve sosyopsikolojik unsurları da kapsayarak güçlendirmektedir. Bununla birlikte etki durumları ve insan-yapay zekâ iş birliği gibi açılardan gelişime açık yönler barındırmaktadır.

Keywords

Eğitim, Öğretim, Yapay Zekâ, Chatgpt, Chatbot, Bilim Haritalama, Ortak Kavramlar

A Holistic Perspective on the AI-Education Nexus: A Science Mapping Study

Abstract

This study examines how the relationship between artificial intelligence (AI) and education in scientific literature is evolving around common key concepts. For this purpose, the science mapping method was employed. Data were obtained from the Web of Science Core Collection. The search terms included “artificial intelligence,” “education,” “instruction,” and “teaching,” as well as "OpenAI," "ChatGPT," and "Chatbot." Bibliographic data from 14,682 scientific documents were extracted, forming the dataset for this study. Analyses were conducted using the VOSviewer software tool, and co-occurrence analyses were performed on the data. These analyses produced both co-occurrence maps and detailed outputs. With the contribution of these outputs, the general and emerging concepts in the map were identified. The results indicate that the AI-education relationship is predominantly discussed in the context of instructional methods rather than as a technology or tool. In recent years, this discourse has particularly enriched and deepened in related fields, learning environments/contexts, issues/skills related to teaching and learning, and research. This richness supports the AI-education relationship from pedagogical integration, applicability, and ethics perspectives. Additionally, it strengthens the theoretical foundations of this relationship by linking it to educational technology and incorporating socio-psychological elements. However, there remains potential for further development in areas such as impact dynamics and human-AI collaboration

Keywords

Education, Instruction, Artificial Intelligence, ChatGPT, Chatbot, Science Mapping, Common Concepts

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