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Conference proceeding
Academic Advising Chatbot Powered with AI Agent
ACMSE 2025: Proceedings of the 2025 ACM Southeast Conference, pp.195-202
ACM Other Conferences
ACMSE 2025: 2025 ACM Southeast Conference (Cape Girardeau, Missouri, USA, 04/24/2025–04/26/2025)
05/08/2025
Web of Science ID: WOS:001494357600022
Abstract
Academic advising plays a crucial role in fostering student success. However, challenges such as limited advisor availability can hinder effective support. Generative AI, particularly AI-powered chatbots, offers the potential to enhance student advising in higher education by providing personalized guidance. These technologies help college students find the information and resources needed to create degree plans aligned with their academic goals. This research introduces ARGObot, an intelligent advising system that facilitates student navigation of university policies through automated interpretation of the student handbook as its primary knowledge base. ARGObot enhances accessibility to critical academic policies and procedures, supporting incoming students' success through personalized guidance. Our system integrates a multifunctional agent enhanced by a Large Language Model (LLM). The architecture employs multiple external tools to enhance its capabilities: a Retrieval-Augmented Generation (RAG) system accesses verified university sources; email integration facilitates Human-in-the-Loop (HITL) interaction; and a web search function expands the system's knowledge base beyond predefined constraints. This approach enables the system to provide contextually relevant and verified responses to various student queries. This architecture evolved from our initial implementation based on Gemini 1 Pro, which revealed significant limitations due to its lack of agent-based functionality, resulting in hallucination issues and irrelevant responses. Subsequent evaluation demonstrated that our enhanced version, integrating GPT-4 with the text-embedding-ada-002 model, achieved superior performance across all metrics. This paper also presents a comparative analysis of both implementations, highlighting the architectural improvements and their impact on system performance.
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Details
- Title
- Academic Advising Chatbot Powered with AI Agent
- Publication Details
- ACMSE 2025: Proceedings of the 2025 ACM Southeast Conference, pp.195-202
- Resource Type
- Conference proceeding
- Conference
- ACMSE 2025: 2025 ACM Southeast Conference (Cape Girardeau, Missouri, USA, 04/24/2025–04/26/2025)
- Publisher
- Association for Computing Machinery (ACM); New York
- Series
- ACM Other Conferences
- Number of pages
- 8
- Copyright
- © 2025 Copyright is held by the owner/author(s). Publication rights licensed to ACM.
- Identifiers
- WOS:001494357600022; 99381356649306600
- Academic Unit
- Cybersecurity and Information Technology; Mathematics and Statistics; Hal Marcus College of Science and Engineering
- Language
- English