Empowering Student Futures: An AI-driven Approach to Give Personalized Major/Career Recommendations for High School Students
Year: 2024
Type: conference-paper
Abstract: In today's international education, students face great challenges and uncertainties in making career choices. Many struggle to find clear career paths or set long-term goals. Even after choosing a major or a career, many students feel dissatisfied. This leads to frequent changes in their academic and career plans. These changes can cause serious problems and disrupt their future plans. Schools try to help students choose the right academic paths, but the growing demand for education makes it difficult for teachers to provide individualized guidance to each student. In addition, most teachers do not have a complete understanding of students' academic profiles and potential. To solve this problem and help international high school students find the right career paths, advanced technology is needed. These tools can analyze students' academic information and provide fast, personalized advice. This study examines how deep learning neural networks can help students find appropriate careers. By using these algorithms, we aim to create a system that processes student data and provides tailored recommendations, making academic and career choices easier for students.
Authors: Yibo Dang, Muyuan Liu, Boshen Zhang, Xin Luo
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: gold
OpenAlex ID: W4411088772