{"title":"基于深度学习模型的大学生日常思想政治教育创新研究","authors":"Xianwei Zhang, Yueyan Zhang","doi":"10.17993/3ctecno.2023.v12n1e43.108-125","DOIUrl":null,"url":null,"abstract":"Various network information is mixed, which has a great impact education, with continuous development informatization. However, development of informatization has provided convenience for the daily ideological political education, effectively solved time and space limitation daily ideological, and sustainable development. Therefore, positively influence formation of college students' noble morality. The informatization education resources can be effectively integrated, and the utilization rate resources improved. Information resources of ideological and political education, we propose a complete block diagram of the daily ideological system of college students. First, design a complete interactive analysis questionnaire for college student’s role of daily ideological and political education. Through questionnaire survey method, the survey and statistical weight scores were conducted to analyze the proportion of each indicator. Then, the framework of education in the network environment is adopted, which includes, class tutoring learning, class interactive learning, class in-depth study, process evaluation and feedback evaluation. Learn through a period of ideological and political education. Collect data as our training corpus. Finally, the training prediction model BERT-BiLSTM-CRF-based trained. Prediction of F1 BERT-BiLSTM- CRF -based can reach 91.09%.","PeriodicalId":210685,"journal":{"name":"3C Tecnología_Glosas de innovación aplicadas a la pyme","volume":"193 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Research on Innovation of Daily Ideological and Political Education for College Students based on Deep Learning Model\",\"authors\":\"Xianwei Zhang, Yueyan Zhang\",\"doi\":\"10.17993/3ctecno.2023.v12n1e43.108-125\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Various network information is mixed, which has a great impact education, with continuous development informatization. However, development of informatization has provided convenience for the daily ideological political education, effectively solved time and space limitation daily ideological, and sustainable development. Therefore, positively influence formation of college students' noble morality. The informatization education resources can be effectively integrated, and the utilization rate resources improved. Information resources of ideological and political education, we propose a complete block diagram of the daily ideological system of college students. First, design a complete interactive analysis questionnaire for college student’s role of daily ideological and political education. Through questionnaire survey method, the survey and statistical weight scores were conducted to analyze the proportion of each indicator. Then, the framework of education in the network environment is adopted, which includes, class tutoring learning, class interactive learning, class in-depth study, process evaluation and feedback evaluation. Learn through a period of ideological and political education. Collect data as our training corpus. Finally, the training prediction model BERT-BiLSTM-CRF-based trained. Prediction of F1 BERT-BiLSTM- CRF -based can reach 91.09%.\",\"PeriodicalId\":210685,\"journal\":{\"name\":\"3C Tecnología_Glosas de innovación aplicadas a la pyme\",\"volume\":\"193 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-03-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"3C Tecnología_Glosas de innovación aplicadas a la pyme\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.17993/3ctecno.2023.v12n1e43.108-125\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"3C Tecnología_Glosas de innovación aplicadas a la pyme","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.17993/3ctecno.2023.v12n1e43.108-125","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research on Innovation of Daily Ideological and Political Education for College Students based on Deep Learning Model
Various network information is mixed, which has a great impact education, with continuous development informatization. However, development of informatization has provided convenience for the daily ideological political education, effectively solved time and space limitation daily ideological, and sustainable development. Therefore, positively influence formation of college students' noble morality. The informatization education resources can be effectively integrated, and the utilization rate resources improved. Information resources of ideological and political education, we propose a complete block diagram of the daily ideological system of college students. First, design a complete interactive analysis questionnaire for college student’s role of daily ideological and political education. Through questionnaire survey method, the survey and statistical weight scores were conducted to analyze the proportion of each indicator. Then, the framework of education in the network environment is adopted, which includes, class tutoring learning, class interactive learning, class in-depth study, process evaluation and feedback evaluation. Learn through a period of ideological and political education. Collect data as our training corpus. Finally, the training prediction model BERT-BiLSTM-CRF-based trained. Prediction of F1 BERT-BiLSTM- CRF -based can reach 91.09%.