Background/Objectives: The purpose of the study is to find out the factors affecting student readiness for education 4.0. Methods/Statistical analysis: Based on 361 samples, this quantitative research was conducted: reliability testing, exploratory factor analysis, correlation coefficients and linear regression. The result shows that there are four key factors affecting readiness including Self-regulation, Creativity, Upgrade and Attitude. Findings: The result of t-test shows that the group of students who had experienced online learning had higher readiness for the education 4.0 than the others. Improvements/Applications: The advantages that students realize when being involved in the 4.0 education system will help them greatly improve their skills and knowledge.

Background/Objectives: The thesis "Building AI Chatbot to support admissions and career guidance for universities" has been explored, analyzed and understood the difficulties, shortcomings and problems arising in career counseling, enrollment support. Methods/Statistical analysis: Building a chatbot is a perfect solution. A chatbot can be available 24/7 for 365 days. Chatbot also receives and processes requests of students / parents automatically and quickly and uniformly in replying content, especially optimized in repetitive scenarios. Findings: Thus we decided to do research to understand this situation. Then creating a dataset supports vocational guidance and advising education enrollment activities. We also design and integrate chatbot into the school system to support the admissions counseling process. Improvements/Applications: Besides, the thesis has successfully built a structured dataset about enrollment orientation and apply of natural language processing, machine learning to build identification models. The thesis will contribute to overcome and improve the performance of university admissions consulting.