Transformer-Based question answering systems for higher education: A comparative study of Turkish and multilingual models
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
References
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Details
Primary Language
English
Subjects
Information Systems User Experience Design and Development
Journal Section
Research Article
Early Pub Date
November 2, 2025
Publication Date
June 5, 2026
Submission Date
October 9, 2024
Acceptance Date
September 5, 2025
Published in Issue
Year 2026 Volume: 32 Number: 3