Kimya Sorularının Cevaplanmasında Yapay Zekâ Tabanlı Sohbet Robotlarının Performansının İncelenmesi

Year 2023, Volume: 21 Issue: 3, 1540 - 1561, 29.12.2023

Ayşe Yalçın Çelik , Özgür K.çoban

https://doi.org/10.37217/tebd.1361401

Abstract

Yapay zekâ son yıllarda sağlık, bankacılık ve finans, teknoloji, endüstri, psikoloji ve eğitim gibi birçok alanda kullanılmaktadır. Özellikle doğal dili anlayan ve dil modellerini etkili bir şekilde kullanarak cevaplar verebilen yapay zekâ tabanlı sohbet robotlarının (chatbot) ortaya çıkmasıyla beraber sohbet robotlarının sorulara verdikleri cevapların doğruluk düzeyi tartışma konusu olmuştur. Bu araştırmanın amacı, iki sohbet robotunun üniversite seviyesinde, Bloom’un bilişsel alan taksonomisi dikkate alınarak, yüzey gerilimi konusu ile ilgili hazırlanmış sorulara verdikleri cevapların doğruluk düzeylerini belirlemektir. Araştırmanın deseni durum çalışması olarak belirlenmiştir. Veri toplama aracı olarak yüzey gerilimi ile ilgili Bloom’un bilişsel alan taksonomisi dikkate alınarak hazırlanmış altı adet açık uçlu sorudan oluşan ölçek kullanılmıştır. Sohbet robotlarının yüzey gerilimi ile ilgili sorulara verdiği cevaplar üç uzman tarafından değerlendirilmiştir. Araştırmanın bulgularına göre sohbet robotlarının 60 puan üzerinden 35 ve 38 puan aldıkları, aynı sorularda aynı puan ortalamalarına sahip oldukları, çözümleme düzeyindeki soruyu yanlış cevapladıkları, yaratma düzeyindeki sorudan en yüksek puanı aldıkları ve cevaplarında yanlışlıklar/eksiklikler olduğu ancak açıklamalarının %66,7 oranında net olduğu belirlenmiştir. Bu sonuçlardan yola çıkarak; sohbet robotlarının performansının zorluk seviyesi kolaydan zora doğru olan farklı konularda belirlendiği, istem (prompt) girişinin birden fazla yapılarak bu uygulamanın daha doğru cevapların üretilmesine etki edip etmediği ve sohbet robotların cevaplarında yanlış kavramaların olup olmadığının belirlendiği çalışmaların yapılması önerilmektedir.

Keywords

Yapay zeka, Sohbet robotu, Kimya eğitimi, Bloom'un bilişsel alan taksonomisi

Investigating the Performance of AI-Based Chatbots in Answering Chemistry Questions

Abstract

Artificial intelligence has developed rapidly in recent years and is used in many fields, such as health, banking and finance, technology, industry, psychology and education. Especially with the emergence of artificial intelligence-based chatbots that understand natural language and can answer using language models effectively, the accuracy level of the answers given by chatbots to questions has been a subject of discussion. This study aims to determine the accuracy levels of the answers provided by two chatbots to the questions prepared about surface tension at university level, taking into account Bloom's cognitive domain taxonomy. The research design was determined as a case study. A scale of six open-ended questions about surface tension prepared using Bloom's cognitive domain taxonomy was used as a data collection tool. Three experts evaluated the answers of chatbots to the questions about surface tension. According to the results of the study, the chatbots scored 35 and 38 out of 60 points, they had the same average scores on the same questions, they answered the question at the analysis level incorrectly, they got the highest score on the question at the creation level, and there was misinformation/insufficient information in their answers, but 66.7% of their explanations were clear. Based on these results, it is recommended to carry out studies in which the performance of chatbots is determined in different subjects with difficulty levels from easy to difficult, whether this application affects the production of more accurate answers by making more than one prompt input, and whether there are misconceptions in the responses of chatbots.

Keywords

Artificial intelligence, Chatbot, Chemistry education, Bloom's cognitive domain taxonomy

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