Transforming mentorship: an AI-powered chatbot approach to university guidance
Date
2025-01
Journal Title
Journal ISSN
Volume Title
Publisher
BRAC University
Abstract
Chatbots are agents designed for communicating with humans and mimic the human-
human interaction style. They can understand natural language and communicate
with users through it. In this complicated digital world, university students face
enormous challenges throughout their undergraduate journey. Universities cannot
appoint that many mentors to attend to every student’s query. Even though there
are a notable number of digital tools and platforms to support students, there re-
mains a gap in personalized guidance for newcomers, specifically in the form of
chatbots. A digital mentor to meet the specific demands and difficulties faced by
new students is what will help them handle academic obstacles more effectively.
Filling this crucial gap is essential for the creation of supportive and inclusive ed
ucational technologies. Our research aims to design and develop a corpus-based
chatbot that will primarily serve as a mentor to students. The interactive chatbot
will be able to communicate with the user through informal dialogue generated by
natural language processing. Finally, it will conclude by finding and assessing any
biases that the chatbot may exhibit. This chatbot can assist first-year students by
answering their questions. It can also help students obtain a sense of the topics of
a course and plan an elective class routine for their semesters. Thus, it will assist
students during their academic life of open-credit universities.
Description
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 58-60).
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2025.
Includes bibliographical references (pages 58-60).
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2025.
Keywords
Chatbot, Corpus-based, Natural Language Processing (NLP), Personalized guidance, Interactive chatbot, Educational technology, Informal dialogue, Open-credit universities, Bias assessment
