Semester of Graduation
Fall 2025
Degree Type
Dissertation/Thesis
Degree Name
Masters in Computer Science
Department
Computer Science
Committee Chair/First Advisor
Dr. Selena He
Second Advisor
Dr. Lei Li
Third Advisor
Dr. Hisham Haddad
Abstract
In the modern age of digitization, educational institutions and universities are becoming ever more reliant on innovative technology solutions to facilitate student engagement and administrative services. Conventional chatbots often fall short in addressing the dynamic and multifaceted queries of academic communities, primarily due to limitations in contextual understanding and real-time information retrieval. This research proposes a novel AI-powered chatbot, tailored for Kennesaw State University website, that leverages the Retrieval-Augmented Generation (RAG) framework to overcome these challenges. By combining state-of-the-art natural language processing techniques with efficient knowledge indexing and semantic search capabilities, the proposed chatbot integrates retrieval-based and generative AI techniques to ensure that the responses are both factually grounded and contextually relevant. The methodology includes comprehensive data collection from official university sources, rigorous preprocessing to create high-quality embeddings, and fine-tuning of the generative model for domain-specific language. Evaluation metrics such as answer relevance, context precision, and Faithfulness will be employed to assess performance. This research not only promises to enhance the functionality of digital academic support systems but also contributes to the broader field of AI-driven conversational agents by demonstrating the effectiveness of hybrid retrieval-generation models in real-world educational settings.
Included in
Computer and Systems Architecture Commons, Digital Communications and Networking Commons, Educational Technology Commons, Higher Education Administration Commons
Comments
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