An Enhanced Chatbot for University Admission and Educational Guidance

This study presents evidence to support students to university admission services due to a shortage of staff. The chatbot was developed using machine learning and natural language processing and was tested on the LINE application. The developed chatbot can provide low-cost support for admission, tuition fees, and contextual questions in a personalized and speedy manner. A mixed-method approach was applied, merging qualitative and quantitative data to optimize performance. Further, a usability test of 100 students yielded results of a 92% satisfaction rate. The accuracy assessment results provide 97% accuracy, with an F1 score of 82%. These reflect how effective chatbots are in enhancing user experience while lessening dependence on human advisors, hence smoothing workflow processes when providing educational support. Results show how AI has transformed education through efficiency, integration, and access. This study found a basis for scaling AI applications in higher education and other services focusing on students.

Authors

Institutions

Publication Details

Published
2025-04-02
DOI
https://doi.org/10.1109/icci64209.2025.10987355
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

An Enhanced Chatbot for University Admission and Educational Guidance

Parinya Natho, Nontachai Singhuang
Online Learning and Analytics
article

An Enhanced Chatbot for University Admission and Educational Guidance

Parinya Natho, Nontachai Singhuang
article en

Abstract

This study presents evidence to support students to university admission services due to a shortage of staff. The chatbot was developed using machine learning and natural language processing and was tested on the LINE application. The developed chatbot can provide low-cost support for admission, tuition fees, and contextual questions in a personalized and speedy manner. A mixed-method approach was applied, merging qualitative and quantitative data to optimize performance. Further, a usability test of 100 students yielded results of a 92% satisfaction rate. The accuracy assessment results provide 97% accuracy, with an F1 score of 82%. These reflect how effective chatbots are in enhancing user experience while lessening dependence on human advisors, hence smoothing workflow processes when providing educational support. Results show how AI has transformed education through efficiency, integration, and access. This study found a basis for scaling AI applications in higher education and other services focusing on students.

Rajamangala University of Technology Suvarnabhumi (TH)
Rajamangala University of Technology Suvarnabhumi
Quality Education
Openalex Percentile: Top 90%
Online Learning and Analytics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

An Enhanced Chatbot for University Admission and Educational Guidance — Parinya Natho, Nontachai Singhuang · (2025) | TGRS Research Map | TGRS