What question did this study set out to answer?

To develop an AI-based chatbot for academic advising that improves efficiency and student satisfaction.

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

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This system demonstrates improved student advising and satisfaction through AI and ontology in higher education, suggesting enhanced engagement.

To develop an AI-based chatbot for academic advising that improves efficiency and student satisfaction.
Developed using Natural Language Processing techniques and the Fuzzy Wuzzy algorithm.
Utilized the LINE Messaging Application Programming Interface for real-time student interactions.
Organized academic content into five domains: course guidance, registration, internships, cooperative education, and career preparation.
Achieved intent classification performance with accuracy, precision, recall, and F1-scores over 89%.
Rated highly for appropriateness with a mean score of 4.78 from expert evaluations.
Confirmed significant influence of system, information, and service quality on user satisfaction (p < 0.05).

Sudasawan Ngammongkolwong (2025) studied this question.

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View Full Paper

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Authors

This system demonstrates improved student advising and satisfaction through AI and ontology in higher education, suggesting enhanced engagement.

To develop an AI-based chatbot for academic advising that improves efficiency and student satisfaction.
Developed using Natural Language Processing techniques and the Fuzzy Wuzzy algorithm.
Utilized the LINE Messaging Application Programming Interface for real-time student interactions.
Organized academic content into five domains: course guidance, registration, internships, cooperative education, and career preparation.
Achieved intent classification performance with accuracy, precision, recall, and F1-scores over 89%.
Rated highly for appropriateness with a mean score of 4.78 from expert evaluations.
Confirmed significant influence of system, information, and service quality on user satisfaction (p < 0.05).

Sudasawan Ngammongkolwong (2025) studied this question.

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