Author Information
Maria Eleni Koutsiaki, International Hellenic University, GreeceMarina Delianidi, International Hellenic University, Greece
Chaido Mizeli, International Hellenic University, Greece
Konstantinos Diamantaras, International Hellenic University, Greece
Iraklis Grigoropoulos, International Hellenic University, Greece
Nikolaos Koutlianos, Aristotle University of Thessaloniki, Greece
Abstract
The integration of AI chatbots into educational settings has opened new pathways for transforming teaching and learning, offering enhanced support to both educators and learners. This study investigates the design and application of an AI chatbot as an educational tool in higher education. The chatbot was developed utilizing instructional materials from the course Family Psychology offered by the Department of Early Childhood Education and Care at the International Hellenic University, in conjunction with curricular resources from Sports Medicine courses by the School of Physical Education and Sport Science at the Aristotle University of Thessaloniki. Designed to operate in the Greek language, the chatbot addresses linguistic challenges unique to Greek while delivering accurate, context-grounded support aligned with the curriculum. The AI chatbot is built on the Retrieval Augmented Generation (RAG) framework by grounding its responses in specific course content. RAG architecture significantly enhances the chatbot’s reliability by providing accurate, context-aware responses while mitigating common challenges associated with large language models (LLMs), such as hallucinations and misinformation. The AI chatbot serves a dual purpose: it enables students to access accurate, on-demand academic support, and assists educators in the rapid creation of relevant educational materials. This dual functionality promotes learner autonomy and streamlines the instructional design process. The study aims to evaluate the effectiveness, reliability, and perceived usability of RAG-based chatbots in higher education, exploring their potential to enhance educational practices and outcomes as well as supporting the broader adoption of AI technologies in language-specific educational contexts. Findings from this research are expected to contribute to the emerging field of AI-driven education by demonstrating how intelligent systems can be effectively aligned with pedagogical goals.
Paper Information
Conference: BCE2025Stream: Design
This paper is part of the BCE2025 Conference Proceedings (View)
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To cite this article:
Koutsiaki M., Delianidi M., Mizeli C., Diamantaras K., Grigoropoulos I., & Koutlianos N. (2025) From Textbook to Talkbot: A Case Study of a Greek-Language RAG-Based Chatbot in Higher Education ISSN: 2435-9467 – The Barcelona Conference on Education 2025: Official Conference Proceedings (pp. 171-182) https://doi.org/10.22492/issn.2435-9467.2025.15
To link to this article: https://doi.org/10.22492/issn.2435-9467.2025.15
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