L. Ni, Qiang Huang, Jing Ye, Bin Hu, Ni Zhang, Xiangqian Chang, Zhihao Su
{"title":"基于智能管理系统的职业教育发展模式","authors":"L. Ni, Qiang Huang, Jing Ye, Bin Hu, Ni Zhang, Xiangqian Chang, Zhihao Su","doi":"10.1109/ICEIT54416.2022.9690746","DOIUrl":null,"url":null,"abstract":"Intelligent management system centered on artificial intelligence algorithms, cloud computing technology, mobile Internet technology, and big data applications have made remarkable achievements in various industries. The intelligent management system designed in this project is to apply these technologies to explore a vocational education development model that adapts to the current Internet society. Vocational education needs to be oriented to the professional needs of the society, it needs to be oriented to students' vocational choices, and it needs to be oriented to the skill range of teachers. This project collects students' learning data and teaches students in accordance with their aptitude in the course of students' daily classes, matches students with appropriate vocational and technical elective courses and teachers, and records students' feedback during their studies, and in the future career development of students, to help students make better career choices. At the same time, the needs of students, companies, and teachers in vocational education will be collected, and artificial intelligence algorithms will be used to process student data and corporate recruitment data, automatically matching the most suitable combination of students and companies. The biggest core innovation of this system is the latest deep learning algorithm, and according to the actual situation of vocational education, the residual neural network is improved to create an improved residual neural network suitable for students' professional development recommendations. The final result of this algorithm, the auxiliary role in the process of student vocational education and development is far greater than the traditional vocational education management system, and in the C University student education and professional development database, there is about 90% satisfaction rate and the 85% occupational matching accuracy rate is far higher than the performance of the traditional vocational education management system.","PeriodicalId":285571,"journal":{"name":"2022 11th International Conference on Educational and Information Technology (ICEIT)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Vocational Education Development Model Based on Intelligent Management System\",\"authors\":\"L. Ni, Qiang Huang, Jing Ye, Bin Hu, Ni Zhang, Xiangqian Chang, Zhihao Su\",\"doi\":\"10.1109/ICEIT54416.2022.9690746\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Intelligent management system centered on artificial intelligence algorithms, cloud computing technology, mobile Internet technology, and big data applications have made remarkable achievements in various industries. The intelligent management system designed in this project is to apply these technologies to explore a vocational education development model that adapts to the current Internet society. Vocational education needs to be oriented to the professional needs of the society, it needs to be oriented to students' vocational choices, and it needs to be oriented to the skill range of teachers. This project collects students' learning data and teaches students in accordance with their aptitude in the course of students' daily classes, matches students with appropriate vocational and technical elective courses and teachers, and records students' feedback during their studies, and in the future career development of students, to help students make better career choices. At the same time, the needs of students, companies, and teachers in vocational education will be collected, and artificial intelligence algorithms will be used to process student data and corporate recruitment data, automatically matching the most suitable combination of students and companies. The biggest core innovation of this system is the latest deep learning algorithm, and according to the actual situation of vocational education, the residual neural network is improved to create an improved residual neural network suitable for students' professional development recommendations. The final result of this algorithm, the auxiliary role in the process of student vocational education and development is far greater than the traditional vocational education management system, and in the C University student education and professional development database, there is about 90% satisfaction rate and the 85% occupational matching accuracy rate is far higher than the performance of the traditional vocational education management system.\",\"PeriodicalId\":285571,\"journal\":{\"name\":\"2022 11th International Conference on Educational and Information Technology (ICEIT)\",\"volume\":\"50 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-01-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 11th International Conference on Educational and Information Technology (ICEIT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICEIT54416.2022.9690746\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 11th International Conference on Educational and Information Technology (ICEIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEIT54416.2022.9690746","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Vocational Education Development Model Based on Intelligent Management System
Intelligent management system centered on artificial intelligence algorithms, cloud computing technology, mobile Internet technology, and big data applications have made remarkable achievements in various industries. The intelligent management system designed in this project is to apply these technologies to explore a vocational education development model that adapts to the current Internet society. Vocational education needs to be oriented to the professional needs of the society, it needs to be oriented to students' vocational choices, and it needs to be oriented to the skill range of teachers. This project collects students' learning data and teaches students in accordance with their aptitude in the course of students' daily classes, matches students with appropriate vocational and technical elective courses and teachers, and records students' feedback during their studies, and in the future career development of students, to help students make better career choices. At the same time, the needs of students, companies, and teachers in vocational education will be collected, and artificial intelligence algorithms will be used to process student data and corporate recruitment data, automatically matching the most suitable combination of students and companies. The biggest core innovation of this system is the latest deep learning algorithm, and according to the actual situation of vocational education, the residual neural network is improved to create an improved residual neural network suitable for students' professional development recommendations. The final result of this algorithm, the auxiliary role in the process of student vocational education and development is far greater than the traditional vocational education management system, and in the C University student education and professional development database, there is about 90% satisfaction rate and the 85% occupational matching accuracy rate is far higher than the performance of the traditional vocational education management system.