The Development of an Intelligent Academic Consulting Chatbot for Bachelor’s Degree Students Based on Ontology in Higher Education Institutions in Thailand

Abstract

This study develops an Artificial Intelligence (AI)-based academic consulting system using Natural Language Processing (NLP) techniques and the Fuzzy Wuzzy algorithm to enhance academic advising in Thai higher education. Designed for undergraduate students, the system supports real-time interactions via the LINE Messaging Application Programming Interface (API), thereby facilitating effective student engagement. The chatbot’s NLP module demonstrated strong intent classification performance, achieving accuracy, precision, recall, and F1-scores all exceeding 89%. The ontology framework organized academic content into five domains: course guidance, registration, academic progress, internships and cooperative education, and career and further study preparation. Expert evaluations rated the system’s appropriateness at a mean score of 4.78 (SD = 0.38), indicating a “very high” level. Hypothesis testing, based on the Information Systems (IS) Success Model, confirmed that system quality, information quality, and service quality significantly influenced both system use and user satisfaction (statistically significant at p < 0.05). These findings suggest that an ontology-based intelligent chatbot can improve academic advising efficiency, reduce advisor workload, and enhance student satisfaction. This study contributes to educational technology by demonstrating the effectiveness of integrating semantic knowledge with Natural Language Processing (NLP) techniques to support student services. Future enhancements may include ensemble modeling and contextual embeddings to further improve semantic understanding and personalization in academic dialogue systems.

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