With the rapid development of mobile Internet, vocational English online vocational education has won the favor of a large number of users for its strong practicality and convenience. Students can make up for the limited amount of professional class hours in schools by learning relevant courses. However, due to the uneven pre-school foundation and the ability to learn and master knowledge of vocational education students, many pain points still exist, such as the teaching quality of students cannot be guaranteed in the learning process, and the knowledge learned is out of line with the needs of enterprises. To solve this problem, this paper proposes a solution for vocational education on the vocational English line based on big data and machine learning, which aims to use big data and machine learning methods to improve students' learning effect and enterprise practical ability through adaptive teaching and practical courses, and provide students with opportunities to go to enterprises for practical training by establishing contacts with enterprises, so that students can clearly understand what kind of talents enterprises need, So as to selectively learn the corresponding professional knowledge on the platform, make up for the lack of course hours, and improve the employability.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.