Transformer-Based question answering systems for higher education: A comparative study of turkish and multilingual models

Year 2026, Volume: 32 Issue: 3

Halenur Sazak , Muhammed Kotan

https://doi.org/10.5505/pajes.2025.44459

Abstract

This study presents a question answering system developed for higher education using transformer-based models. Five pretrained models were evaluated including BERTurk Base cased/uncased, ELECTRA-Turk, mBERT and XLM-R. The models were fine-tuned on the THQuAD dataset and tested on a frequently asked questions dataset constructed from official university sources and student queries. In addition to standard evaluation metrics such as Exact Match and F1 score, an extended evaluation approach was applied to better capture semantically appropriate answers. ELECTRA-Turk achieved the highest F1 score of 0.8936 and an Exact Match score of 0.8478. The results show that transformer-based approaches can effectively support automated question answering in academic domains and improve information access for students.

Keywords

Question-Answering System , Transformer Models , Information Retrieval , Turkish Language Models , Natural Language Processing

Yükseköğretim İçin Transformer Tabanlı Soru-Cevap Sistemleri: Türkçe ve Çok Dilli Modellerin Karşılaştırmalı Bir İncelemesi

Abstract

Bu çalışma, yükseköğretimde kullanılmak üzere geliştirilen bir soru cevap sistemi sunmaktadır. BERTurk Base cased/uncased, ELECTRA-Turk, mBERT ve XLM-R olmak üzere beş önceden eğitilmiş model değerlendirilmiştir. Modeller, THQuAD veri kümesi üzerinde ince ayarlanarak eğitilmiş ve resmi üniversite kaynakları ile öğrenci sorularından oluşturulan bir sıkça sorulan sorular veri kümesi üzerinde test edilmiştir. Tam Eşleşme ve F1 gibi standart metriklere ek olarak anlam açısından doğru yanıtları da dikkate alan genişletilmiş bir değerlendirme yöntemi uygulanmıştır. En yüksek F1 skoru 0.8936 ve Tam Eşleşme skoru 0.8478 ile ELECTRA-Turk modeli tarafından elde edilmiştir. Bulgular, transformer tabanlı yaklaşımların akademik ortamda otomatik soru cevaplama görevlerinde etkili olduğunu ve öğrenci odaklı bilgiye erişimi artırabileceğini göstermektedir.

Keywords

Soru-Cevap Sistemi , Transformer Modeller , Bilgi Edinme , Türkçe Dil Modelleri , Doğal Dil İşleme

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