Design and Evaluation of an AI-Powered Chatbot for ERP-Based Student Services in Higher Education - Chimpiri, Tirumala Rao (2025 10th International STEM Education Conference (iSTEM-Ed), 2025)
Higher education institutions are increasingly exploring conversational AI to enhance student services, especially in STEM programs where timely support is crucial. This paper presents the design and evaluation of a practical AI-powered chatbot prototype that assists with essential student service functions by accessing ERP-style data. The proposed chatbot leverages natural language processing (NLP) to handle queries related to admissions, course management, and academic advising, providing instant, and round-the-clock conversational support. A prototype was developed in Python and evaluated on key metrics: query resolution accuracy, system response time, task completion rate, and satisfaction score. To provide interpretable and institution-friendly automation, we adopted a rule-based approach using keyword recognition. This study utilized a stimulated data set of 100 student records, and chatbot was tested across 50 queries. The chatbot achieved an accuracy rate of 100 %, a 0.001 second average response time, and an 100 % task completion rate, outperforming traditional support systems (80 % accuracy, 45-second response time). The results show that stimulated user satisfaction reached 4.5/5, indicating measurable enhancement in the student engagement and satisfaction. These results demonstrate that an ERP-integrated chatbot can significantly benefit STEM education by providing on-demand, tailored assistance, reducing staff workload, and supporting the modernization of academic service delivery