En AI-chattbot som förenklar arbetet för studievägledare

Abstract

As the student population continues to grow, so does the demand for accessible and effective academic guidance. This bachelor’s thesis investigates how AI-based chatbots, powered by large language models (LLMs), can be utilized to support the work of academic advisors. Through interviews with study guidance counselors at the University of Gothenburg, it was found that responses to most student inquiries are already available on the university’s official websites. Accordingly, the project commenced with the collection and structuring of relevant information from these sources through automated web scraping. To develop a domain-specific chatbot based on this data, a Retrieval-Augmented Generation (RAG) system was implemented. Given the focus on addressing frequently asked questions from students, the potential of fine-tuning a large language model was also explored. This was carried out through an automated pipeline that generated question–answer pairs for training purposes. The attempt at using fine-tuning did not yield significant results; however, it holds potential for future experiments given more time and resources. In contrast, the RAG-based system showed promising results, although it requires further development to be practically implemented.