Publication
Scalable Mentoring Support with a Large Language Model Chatbot
Hassan Soliman; Milos Kravcik; Alexander Tobias Neumann; Yue Yin; Norbert Pengel; Maike Haag
In: Rafael Ferreira Mello; Nikol Rummel; Ioana Jivet; Gerti Pishtari; José A. Ruipérez Valiente (Hrsg.). Technology Enhanced Learning for Inclusive and Equitable Quality Education. European Conference on Technology Enhanced Learning (EC-TEL-2024), 19th European Conference on Technology Enhanced Learning, EC-TEL 2024, September 16-20, Krems, Austria, Pages 260-266, Lecture Notes in Computer Science (LNCS), Vol. 15160, ISBN 978-3-031-72311-7, Springer, Cham, 9/2024.
Abstract
Education students engage in diverse learning activities requiring appropriate assistance and timely feedback. As their numbers grow, providing them with scalable support is an important challenge. Here, we focus on the development of a didactic chatbot based on a Large Language Model (LLM). The potential of LLMs is enhanced by existing materials and pedagogical course descriptions. Using Retrieval Augmented Generation (RAG), the bot can retrieve and analyse course materials, in order to provide comprehensive answers to specific questions. Preliminary results indicate that it is possible to distinguish between different student contexts and to generate a prompt answer, taking into account the relevant materials. The evaluation results achieved 84.78% accuracy in providing correct answers for seminar materials.