Characterizing giftedness through generative Artificial Intelligence: Insights from ChatGPT and Gemini

Abstract

This study examines how generative artificial intelligence (AI) models define giftedness, specifically OpenAI’s ChatGPT-3.5 and Google’s Gemini. Considering the potential opportunities of generative AI, which is increasingly used in education today, for gifted education, the study reveals the definition of the giftedness term created by widely used generative AI models. The study analyses the definitions of ChatGPT-3.5 and Gemini about the term giftedness through content analysis, compares the responses of these two models, and relates the findings to the existing literature. It reveals that both generative AI models emphasize multidimensionality and high achievement relative to peers in the definitions of the giftedness term. Gemini additionally highlights natural abilities, asynchronous development, and the complex interplay of cognitive, emotional, and motivational factors, which ChatGPT-3.5 did not address. The study draws attention to the necessity of critically examining data-driven biases and algorithmic constraints embedded in generative AI systems. It offers a basis for future research on the effective and ethically grounded use of generative AI models in identifying and supporting gifted individuals.

Keywords

• Giftedness
• Gifted Education
• Generative Artificial Intelligence
• ChatGPT
• Gemini

Characterizing giftedness through generative Artificial Intelligence: Insights from ChatGPT and Gemini

Abstract

Bu çalışma, üretken yapay zekâ (YZ) modellerinin özel yetenekliliği nasıl tanımladığını incelemekte; özellikle OpenAI tarafından geliştirilen ChatGPT-3.5 ve Google’ın Gemini modellerine odaklanmaktadır. Günümüzde eğitim alanında giderek daha fazla kullanılan üretken YZ’nin özel yetenekli bireylerin eğitimi açısından sunduğu olanaklar dikkate alınarak, çalışmada yaygın biçimde kullanılan bu modellerin özel yeteneklilik kavramına dair tanımları ortaya konulmaktadır. ChatGPT-3.5 ve Gemini modellerinin özel yeteneklilik kavramına ilişkin tanımları içerik analizi yöntemiyle incelenmiş, bu yanıtlar karşılaştırılmış ve elde edilen bulgular mevcut literatürle ilişkilendirilmiştir. Çalışma, her iki modelin de özel yetenekliliği çok boyutluluk ve akranlara kıyasla yüksek başarı düzeyi üzerinden tanımladığını ortaya koymaktadır. Bununla birlikte, Gemini modelinin doğal yetenekler, eşzamanlı olmayan gelişim ve bilişsel, duygusal ve motivasyonel faktörler arasındaki karmaşık etkileşim gibi unsurları da vurguladığı; ChatGPT-3.5’in ise bu boyutlara yer vermediği görülmüştür. Çalışma, üretken YZ sistemlerine gömülü veri temelli önyargıların ve algoritmik sınırlılıkların eleştirel bir biçimde incelenmesi gerekliliğine dikkat çekmektedir. Ayrıca, üretken YZ modellerinin özel yetenekli bireylerin tanılanması ve desteklenmesinde daha etkili ve etik temelli kullanımı için gelecekteki araştırmalara kuramsal bir zemin sunmaktadır.

Keywords

• Özel Yeteneklilik
• Özel Yeteneklilerin Eğitimi
• Üretken Yapay Zekâ
• ChatGPT
• Gemini

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