Title | Research of the Innovative Integration of Artificial Intelligence and Vocational Education in the New Ecology of Education |
Publication Type | Conference Paper |
Year of Publication | 2021 |
Authors | Yanrong, Wen |
Conference Name | 2021 2nd International Conference on Education, Knowledge and Information Management (ICEKIM) |
Keywords | artificial intelligence, Decision support systems, Ecology, Education, education ecology, expert systems, Human Behavior, human factors, Innovation, integration, Law, Management information systems, privacy, pubcrawl, Scalability, Software, top-level strategy, vocational education |
Abstract | The development of artificial intelligence will certainly fundamentally change the pattern of human work. With the promotion of top-level strategies, vocational education can only develop sustainably by integrating with science and technology. Artificial intelligence is a branch of computer science that studies the basic theories, methods and techniques of how to apply computer hardware and software to simulate certain intelligent human behaviors. Artificial intelligence applied to vocational education mainly focuses on resource network technology and integrated distributed intelligent system, which organically integrates various different expert systems (ES), management information systems (MIS), intelligent networks, decision support systems (DSS), databases, numerical computing packages and graphics processing programs to solve complex problems. Artificial intelligence will certainly empower vocational education and give rise to a vocational education revolution. In the process of continuous improvement of AI, it is a more practical approach to apply various already mature AI technologies to vocational education practice. Establishing an intelligent vocational education ecology enables traditional education and AI to complement each other's advantages and jointly promote the healthy and sustainable development of vocational education ecology. |
DOI | 10.1109/ICEKIM52309.2021.00109 |
Citation Key | yanrong_research_2021 |