{"title":"大学英语词汇智能推荐学习模型设计框架","authors":"Miao Yu","doi":"10.1109/ECICE55674.2022.10042823","DOIUrl":null,"url":null,"abstract":"At present, the college English vocabulary is continuously updated with the development of Internet technology. Especially, the occurrence of major news events increases the number of news vocabulary (e.g., new professional terms). However, the existing vocabulary textbooks, limited by the publishing cycle, are designed with limited English word resources. In addition, to meet the vocabulary learning demands of different user groups, English word-learning software relies on professional vocabulary books for users to practice vocabulary repeatedly. This hinders the users who rely on memorizing software from using the vocabulary in business communication or academic writing. In this context, this study proposed the design framework of the intelligent vocabulary recommendation and learning model for college English. The overall design strategy of the model is first analyzed, and the system design mechanism of the model is articulated. This system presented the design elements and mechanism of the personalized learning system of college English vocabulary. The results of this study provide customized English vocabulary resources for college English learners with different needs, interest characteristics, and starting abilities.","PeriodicalId":282635,"journal":{"name":"2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Design Framework of College English Vocabulary Intelligence Recommendation and Learning Model\",\"authors\":\"Miao Yu\",\"doi\":\"10.1109/ECICE55674.2022.10042823\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"At present, the college English vocabulary is continuously updated with the development of Internet technology. Especially, the occurrence of major news events increases the number of news vocabulary (e.g., new professional terms). However, the existing vocabulary textbooks, limited by the publishing cycle, are designed with limited English word resources. In addition, to meet the vocabulary learning demands of different user groups, English word-learning software relies on professional vocabulary books for users to practice vocabulary repeatedly. This hinders the users who rely on memorizing software from using the vocabulary in business communication or academic writing. In this context, this study proposed the design framework of the intelligent vocabulary recommendation and learning model for college English. The overall design strategy of the model is first analyzed, and the system design mechanism of the model is articulated. This system presented the design elements and mechanism of the personalized learning system of college English vocabulary. The results of this study provide customized English vocabulary resources for college English learners with different needs, interest characteristics, and starting abilities.\",\"PeriodicalId\":282635,\"journal\":{\"name\":\"2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE)\",\"volume\":\"60 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-10-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ECICE55674.2022.10042823\",\"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 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ECICE55674.2022.10042823","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Design Framework of College English Vocabulary Intelligence Recommendation and Learning Model
At present, the college English vocabulary is continuously updated with the development of Internet technology. Especially, the occurrence of major news events increases the number of news vocabulary (e.g., new professional terms). However, the existing vocabulary textbooks, limited by the publishing cycle, are designed with limited English word resources. In addition, to meet the vocabulary learning demands of different user groups, English word-learning software relies on professional vocabulary books for users to practice vocabulary repeatedly. This hinders the users who rely on memorizing software from using the vocabulary in business communication or academic writing. In this context, this study proposed the design framework of the intelligent vocabulary recommendation and learning model for college English. The overall design strategy of the model is first analyzed, and the system design mechanism of the model is articulated. This system presented the design elements and mechanism of the personalized learning system of college English vocabulary. The results of this study provide customized English vocabulary resources for college English learners with different needs, interest characteristics, and starting abilities.