A Non-AI Homework Support Tool to Enhance Achievement and Interest in Science Education: BilgeCan Bot

Yıl 2025, Cilt: 12 Sayı: 3, 249 - 273, 30.09.2025

Taner Yılmaz , İlbilge Dökme

https://doi.org/10.31202/ecjse.1726783

Öz

Homework helps students learn and develop independent study skills, but they often need extra guidance and reliable information sources, especially in science where abstract concepts can be challenging. Traditional resources may not match students’ cognitive levels and can lead to information overload. To address this, non-AI rule-based (NARB) educational chatbots can provide focused, essential information with minimal cognitive load. This study explores the effects of BilgeCan Bot, a NARB chatbot designed to help middle school students with astronomy homework, based on Cognitive Load Theory. Conducted during the 2022–2023 academic year with 52 fifth-grade students in Türkiye, the research used an explanatory sequential mixed-methods approach. Students were divided into an experimental group using BilgeCan Bot and a control group using textbooks. Data was collected through tests, interest scales, interviews, chatbot records, and teacher feedback. Results showed that students using BilgeCan Bot achieved higher scores and had greater interest in science. They described the chatbot as effective and engaging, helping them grasp difficult concepts. Overall, the findings suggest that NARB chatbots can offer targeted, reliable support for homework in science education without overwhelming students.

Anahtar Kelimeler

Non-AI Rule-Based Educational Chatbot , Science Education , Academic Achievement , Cognitive Load Theory , Student Interest

BilgeCan Bot: Fen Eğitiminde Başarıyı ve İlgiyi Artırmaya Yönelik Yapay Zeka Destekli Olmayan Bir Ödev Destek Aracı

Öz

Ev ödevleri, öğrencilerin bağımsız çalışma becerilerini öğrenmelerine ve geliştirmelerine yardımcı olur, ancak özellikle soyut kavramların zorlayıcı olabileceği fen bilimlerinde genellikle ekstra rehberliğe ve güvenilir bilgi kaynaklarına ihtiyaç duyarlar. Geleneksel kaynaklar öğrencilerin bilişsel seviyelerine uymayabilir ve aşırı bilgi yüklenmesine yol açabilir. Bunu ele almak için, yapay zeka dışı kural tabanlı (NARB) eğitim sohbet robotları, minimum bilişsel yük ile odaklanmış, temel bilgiler sağlayabilir. Bu çalışma, Bilişsel Yük Teorisine dayalı olarak ortaokul öğrencilerine astronomi ödevlerinde yardımcı olmak için tasarlanmış bir NARB sohbet robotu olan BilgeCan Bot'un etkilerini araştırmaktadır. 2022-2023 eğitim-öğretim yılında Türkiye'de 52 beşinci sınıf öğrencisiyle yürütülen araştırmada açıklayıcı sıralı karma yöntem yaklaşımı kullanılmıştır. Öğrenciler BilgeCan Bot'un kullanıldığı deney grubu ve ders kitaplarının kullanıldığı kontrol grubu olarak ayrılmıştır. Veriler testler, ilgi ölçekleri, görüşmeler, chatbot kayıtları ve öğretmen geri bildirimleri yoluyla toplanmıştır. Sonuçlar, BilgeCan Bot kullanan öğrencilerin daha yüksek puanlar elde ettiğini ve fene daha fazla ilgi duyduğunu gösterdi. Öğrenciler, sohbet robotunu etkili ve ilgi çekici olarak tanımladılar ve zor kavramları anlamalarına yardımcı olduğunu belirttiler. Genel olarak bulgular, NARB chatbotlarının fen eğitiminde öğrencileri bunaltmadan ev ödevleri için hedefli ve güvenilir destek sunabileceğini göstermektedir.

Anahtar Kelimeler

Yapay Zekasız Kural Tabanlı Sohbet Botu , Fen Eğitimi , Akademik Başarı , Bilişsel Yük Kuramı , Öğrenci İlgisi

Kaynakça

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